Session N00: Poster Session II (11am-2pm PST)

Predicting Polymer Grafted Nanoparticles Assembly using Deep Learning

Grafting polymer chains on nanoparticles' surfaces is a well-known route to control their self-assembly and distribution in a polymer matrix. A wide variety of self-assembled structures are achieved by changing the grafting patterns on an individual nanoparticle's surface. However, accurate estimation of the effective potential of mean force between a pair of grafted NPs that determines their assembly and distribution in a polymer matrix is an outstanding challenge in nanoscience. Here, we propose a new Deep-Learning (DL) method that learns the interaction between a pair of grafted nanoparticles from the MD trajectory of a cluster of polymer-grafted nanoparticles. Subsequently, we carry out the DL potential of mean force-based molecular simulation that predicts the self-assembly of a large number of polymer-grafted NPs into various anisotropic superstructures, including percolating networks and bilayers depending on the nanoparticles' concentration in three dimensions. The deep learning potential of mean force-predicted self-assembled superstructures is consistent with the actual superstructures of polymer-grafted NPs. This DL framework is very generic and can accelerate the characterization and prediction of the self-assembly and phase behavior of polymer-grafted and un-functionalized NPs in free space or a polymer matrix.   

Molecular modeling, simulation, and machine learning of polymer nanocomposites containing nanorod fillers

Polymer nanocomposites (PNCs) with nanorods as fillers exhibit morphologies (e.g., percolation of nanorods) that are not easily accessible for spherical fillers, making them more desirable for applications requiring conductive and transport properties. Past studies have established the phase diagram of PNC morphologies obtained with homogeneous nanorods; in contrast studies on PNCs with nanorods with physically or chemically heterogeneous functionalization are lacking. In this poster we will present our recent work with coarse-grained molecular dynamics (MD) simulations to predict PNC morphologies with chemically patchy¹ and physically rough² nanorods. In this poster we will also present a machine learning (ML) approach for automatically classifying nanowire/nanorod morphologies (e.g., dispersed/aggregated/percolated nanowires) from transmission electron microscopy (TEM) images DOI: 10.1039/D2DD00066K. Our ML approach uses a small number of labeled microscopy images for training and performs as effectively as methods trained on significantly larger image datasets. 

 

(1) Lu, S.; Wu, Z.; Jayaraman, A. Molecular Modeling and Simulation of Polymer Nanocomposites with Nanorod Fillers. The Journal of Physical Chemistry B 2021, 125 (9), 2435-2449.

(2) Lu, S.; Jayaraman, A. Effect of Nanorod Physical Roughness on the Aggregation and Percolation of Nanorods in Polymer Nanocomposites. ACS Macro Lett 2021, 10 (11), 1416-1422. DOI: 10.1021/acsmacrolett.1c00503.   

Developing machine learning interaction potentials for polyolefins

In the field of molecular modeling and simulation, machine learning (ML) methods are increasingly employed to represent the potential energy surface (PES) of molecular systems, as they allow us to bridge the long-standing speed and accuracy gap between quantum and classical modeling approaches. In this regard, polymeric materials are particularly challenging, due to the range of length and time scales inherent to the physics of polymer chains. Providing a faithful representation of detailed atomic-level interactions (including possible chemical reactions) across these scales is, therefore, computationally expensive, thus opening the door for ML-based approaches to potentially solve this challenge. In this study, we aim to use the deep learning-based Deep Potential Molecular Dynamics (DeePMD) scheme [NeurIPS pp. 4436 - 4446 (2018)] to build ML-potentials for polyolefins. However, best practices for assembling the ML-potential training data in polymeric systems are essentially unknown. As a first attempt, we used the TraPPE united atom forcefield to generate MD simulation trajectories of isolated polyethylene chains and amorphous polyethylene melts and used them to train DeePMD models. We evaluate the ML-potentials’ ability to predict polyethylene's chain-level structure and physical properties, to develop rules-of-thumb for polymeric ML model development. We then discuss our ongoing efforts to build models targeted for studying polyolefin thermal degradation.   

Study of structural and phase behaviour of a polymer electrolyte using molecular simulation

There is a growing demand for high energy density, long-durable, highly stable and environmentally sustainable batteries. Polymer electrolyte-based batteries have the potential to meet these demands due to their ability to combine the solid-like stability of polymers with the high ion conductivity of ionic liquids[1]. However, the realization of commercially viable polymer electrolytes requires addressing fundamental polymer science problems. First, the conductivity of ions is appeared to be intimately coupled with the segmental dynamics of polymers. Second, both ion conductivity and mechanical properties of ionic liquids are strongly related to the glass-forming behaviour of polymers. These factors lead to an inverse correlation between ion conductivity and mechanical properties of polymer electrolytes. Therefore, designing polymer electrolytes with high ion conductivity and high mechanical property is an outstanding challenge[2]. Understanding how conductivity and stability of the materials are connected to the exact location of ionic moiety in a polymer architecture, spacer length, and ion pair volume, hierarchical architecture such as block copolymer and telechelic polymers are vital to address this problem. Here we use coarse-

grained molecular simulation[3] of a phenomenological model to understand how the composition of a polymer matrix is correlated to its conductivity. In this model system, a polymer is represented as a Kremer-Grest FENE chain. Ions are modelled as spherical LJ particles with varying size. All the calculations are done in the LJ unit. Particularly, we have systematically analysed ion distribution in a polymer matrix. Ion distribution, which is strongly connected to the material’s conductivity, is shown to beimpacted by the medium's ion-pair size ratio and dielectric constant[4]. We have proposed a phase diagram [5]  from the simulated results based on Fractal dimensions  which shows variations in three regions from dispersion ,  Percolated and complete phase seperation of ions in a polymermatrix as a function of ion pair size ratio and dielectric constant.   

Autonomous Mapping of Ternary Polymer Solution Phase Diagrams

Ternary polymer-solvent phase diagrams are technologically important, enabling synthesis, self-assembly, formulation, and coating processes. Recently, machine learning (ML) models have demonstrated the ability to predict co-existence curves within 1-3 °C, both interpolating within, and extrapolating beyond, the polymer-solvent training data. Expanding the utility of such models however requires expansive formatted datasets based on FAIR data principles. The goal of this work is to develop an instrument that autonomously and efficiently maps polymer 1-polymer 2-solvent phase diagrams to generate such databases that can be augmented with literature to train an accurate ML model. The design, software, function, and algorithms of the autonomous instrument are described, and demonstrated on the polyacrylamide-poly(ethylene glycol)-water system.   

Polymer Characterization during Continuous Flow Synthesis

The ability to characterize polymers in solutions during synthesis will transform materials design and synthesis strategies. Here, we demonstrate how to use scaling of semidilute polymer solutions to determine evolution of the chain weight average degree of polymerization, N_w, undergoing the step-growth polymerization. The developed approach takes advantage of the scaling relationship between the solution correlation length ξ=lg^ν/B and number of monomers g per correlation volume for polymers with monomer projection length l. The B-parameter and scaling exponent ν defining chain statistics at different length scales assume values B_g, B_th and 0.588, 0.5, respectively. Specifically, the combination of these parameters and the relationship between viscosity, monomer concentration c and N_w provides mean for in-line determination of the time evolution of the weight-average molecular weight of the poly(urethane) during the continuous-flow polymerization in tetrahydrofuran. This approach reduces the time for obtaining the weight-average degree of polymerization for a given polymer/solvent pair to a matter of seconds, enabling the quality control and rapid optimization of the synthesis process.   

Author not Attending

Organic electronic devices are commonly manufactured from a solution using far-out-of-equilibrium processing. The efficiency of these devices depend strongly on the solidified morphology that emerges spontaneously during manufacturing. Although it is well established that the rate of solvent evaporation is one of the important processing conditions, a theoretical understanding on how it influences the morphologies in these devices remains lacking. We apply classical nucleation theory to model how the onset of solidification is influenced by transient effects due to solvent evaporation. Our work shows that the nucleation rate lags behind its quasi-steady-state value, and that the magnitude of this effect depends non-trivially on the evaporation rate. In contrast, the induction time for the onset of nucleation decreases with increasing evaporation rate. Our findings might be relevant for the rational design of organic electronic devices.

    

Understanding the effect of vibronic interactions in organic molecules for polaritons

A molecular exciton polariton is a hybrid light and matter state which forms from the coupling of a photon and an exciton, the photoexcited state of an organic semiconductor or dye. Typically, these states are studied by confining a layer of dye between closely spaced mirrors in a Fabry-Perot microcavity. In the case of a simple polariton system, the interaction between one photon state and one exciton state in resonance can produce an upper and lower polariton band. This resonance is known to be collective across all dipoles available inside the cavity and the formed coherent states delocalize over the field volume. The newly formed hybrid states possess angular dispersion from the photonic mode of the cavity, which forces an anticrossing at the exciton-photon resonance. When more excitons are coupled to the photonic mode of the cavity, these interactions can give rise to a ladder of polariton states with varying degrees of photonic versus exciton character. In this study, we consider three different organic molecules with prominent vibronic structure, and thus multiple strong absorbing exciton transitions, in their steady-state absorption. The molecules DPP, PDI, and PTCDA were deposited via thermal evaporation within silver mirrors. Strong coupling was attained in all structures, and we used angle-dependent reflectivity measurements to determine the dispersions of the polaritonic states for comparison to optical modeling. Studying the relation between the vibronic structure and the dispersion of the polariton branches is useful to aid in the development of devices based on exciton polaritons, like low-threshold lasers, and lays the groundwork for future studies with more sophisticated cavity architectures.

    

Conjugated polymers as ribbon-like chains

Conjugated polymers (CPs) are important for applications in flexible electronics and light-weight energy storage devices. The key property that enables their widespread commercial deployment is high electronic conductivity, which has been demonstrated to correlate strongly with the morphology and conformations of CPs. Here, all-atom molecular dynamics (MD) simulations are applied to reveal the connection between chain conformational statistics and monomer chemistry. The conformational statistics are described by the ribbon-like chain (RLC) model, which generalizes the worm-like chain model by incorporating bending anisotropy and twisting stiffness of CPs. Using MD simulations, we confirm the predictions of the RLC model and parameterize the model parameters for representative polymer chemistries. The results and the established methodology provide the basis for building coarse-grained models to study mesoscopic morphology.   

Characterization of charge transport in organic field effect transistors using modulated amplitude reflectance spectroscopy

Due to their mechanical flexibility and low cost, organic semiconductors are used as the active element in a range of optoelectronic devices; however, low charge mobility in these materials limits further application. In this work, we use modulated amplitude reflectance spectroscopy (MARS) to generate high-resolution, spatially-mapped images of the carrier distribution in operating organic polymer field effect transistors. In the region outside of the contacts channel, carrier mobility values extracted from the measured drift distance of the carriers from the contacts are consistent with mobilities measured using conventional bulk transfer curve analysis. MARS can be used to investigate charge carrier mobility and its dependence on charge carrier density and electric field, as well as to examine the effects of device geometry, defects, and electrical contacts on charge mobility and device efficiency. Supported by NSF award #1919282.   

Approach of Studies on Magnetic Properties of a 3-Armed Nonconjugated Radical Macromolecule

Nonconjugated radical polymers (i.e., macromolecules with aliphatic backbones possessing stable open-shell sites on their pendant groups) have arisen as an intriguing complement to π-conjugated polymers in organic electronic applications, due to their low optical density and easy-tunable structure. Moreover, conjugated dendritic macromolecules have shown significant promise in terms of their response under magnetic fields; however, the molecular design of nonconjugated radical polymers has focused on linear polymers. Therefore, we have synthesized a 3-armed nonconjugated radical macromolecule through a single step reaction and evaluated the electronic and magnetic behavior in both experimental and computational approach. The conductivity value of this macromolecule is on par with many previous linear radical polymers. Additionally, this macromolecule showed shifting magnetic behavior from paramagnetic (300 K) to antiferromagnetic (5 K) at low temperatures due to local ordering. Computational predictions support tighter packing of nitroxides groups for higher-generation dendrimers, which promotes enhanced spin interactions. Thus, this dendritic radical macromolecule affords a promising, high-performance system for the next generation of dendrimers of this type.

    

Imaging Methods for Polysaccharide Material Network Structure

Polysaccharide biopolymers in the extracellular space form ubiquitous, diverse biomaterials such as wood, superhydrophobic structures in insects, and food gels like carrageenan. These systems can tune a broad range of physicochemical parameters such as monomer type, branching topology, rigidity, cross-link density, and interaction energy. We do not understand how these parameters contribute to the observed equilibrated or arrested nonequiliberium materials. To develop a picture of biopolysaccharide materials using the lens of polymer physics, we are using unicellular and multicellular red algae as a model system. We show results from rheometry, light microscopy, small angle x-ray scattering (SAXS), cryo-EM, and NMR to study the polygalactose carrageenan polymers which can take on many material forms, from sparse gels, to optically resonant nematic liquid crystals, to mechanically complex solids. We aim to link polymer biophysics in these organisms to material properties across length scales from the atomic to the organismal. Our approach illuminates the branching topology over nano to microscopic length scales of biological carrageenan that we reconcile with the macroscopic properties of the network and physiology of the organism. With this comprehensive characterization, we begin to see knobs that biological systems can tune in their biopolymers to modify the collective behavior of it. Understanding how biology tunes its polymers creates a framework for the material development of polymers.   

Influence of topology on polymer dynamics in high shear rate flows

Polymers can be used as additives to manipulate the properties of lubricating fluids. These additives must be able to withstand high shear rate flows without degradation of their influence on the fluid properties. It has been found that changing the topology of the polymers can be used to improve the effectiveness of the additives. But the mechanism is not fully understood. Here we use coarse-grained simulations of polymers of varying topology in high shear rates. Changes in topology lead to changes in the structure and thereby their ability to withstand high shear rates.   

Elucidating the Roles of Grafting Density and Bonding Types on the Tethered Polymer Dynamics in Nanoparticle Organic Hybrid Material System

In this study, molecular dynamics and structure of nanoparticle organic hybrid material (NOHMs) system comprising silica nanoparticle-tethered polyetheramine were

investigated by broadband dielectric spectroscopy (BDS), X-ray scattering (SAXS), and thermal analysis techniques (TGA and DSC). Grafting density and chemical bonding

(ionic and covalent) are controlled during the synthesis process to understand the effect of these parameters on the structure and molecular dynamics of NOHMs. Thermal

analysis showed that covalently bonded samples have higher thermal stability and glass transition temperature (Tg) than ionic counterparts. The Tg is enhanced by increasing

grafting density in both ionic and covalent NOHMs. With decreasing grafting density, the SAXS characteristic peak shift to higher q values revealing center-to-center interparticle distance reduction. Dielectric spectroscopy results revealed the slowing down of -relaxation time is controlled by grafting density and bonding so that higher relaxation time is obtained in the highly grafted sample with the covalent bond. Broadening the relaxation time distribution implied heterogeneous structural dynamics governed by grafting density and bonding type. These results demonstrate the role of grafting density and bonding types on the rational design of NOHMs for desired properties

    

Enhancing chiroptical response of chiral polymers with plasmonic nanoparticles well incorporated within the helical assembly

We are studying conformationally modified thin films of polymers comprising fluorene monmomers with chiral side-chains copolymerized with thiophene units to generate high chiral optical activity. The synthesized polymers have varying number of thiophene units, which affects the rotational strength of the polymers owing to the changes in the helicity of their conformations as well as their electronic structure. Upon annealing, the polymer films attain a greater degree of helicity which enhances their chiral optical activity. Further, we are doping the polymer films with gold nanoparticles of 3-5 nm diameter, synthesized directly in a solution of the polymer. Nanoparticle synthesis in the presence of the thiophene-containing polymer, and without other ligands, promotes incorporation of the gold nanoparticles in the polymer helical fibers. This method of doping with gold nanoparticles reduces aggregation of the nanoparticles during annealing. These polymer-gold nanocomposite thin films show substantially higher optical rotatory dispersion i.e., 20 times higher than pure polymer films. The combination of methods employed here allow tuning the backbone conjugation, chiral conformation, and local plasmonic enhancement to achieve enhanced optical chirality.

    

Interfacial dynamics of polymer nanocomposites: the roles of chemical heterogeneity

Polymer at the interface is the key to the mechanical and viscoelastic properties of polymer nanocomposites. Significant efforts have been performed in the past on polymer dynamics near inorganic solid interfaces. In contrast, polymer dynamics at the soft interface have received much less attention. In this contribution, we synthesize and prepare poly(methyl methacrylate) (PMMA) grafted Fe₃O₄ nanoparticles and disperse them in a poly(methacrylate) (PMA) matrix with different polymer molecular weights. Broadband dielectric spectroscopy has been employed to quantify the interfacial dynamics over a wide range of temperatures. Significant broadening of dielectric dispersion of the segmental relaxation of the PMA is observed which can be attributed to the interface slowing down in contact with glassy PMMA, which also exhibits a strong dependence on the molecular weight of the PMA matrix. Interestingly, only a mild slowing down in structural relaxation of PMA is observed over the temperature range of our measurements. On the other hand, significant acceleration has been observed in both the secondary relaxation and the glassy dynamics of grafted PMMA. These observations highlight an interesting interplay between the dynamics of grafted PMMA and that of PMA that is not anticipated in polymer/solid interface.   

Polymer-particle interfacial effect on the bond exchange rate of vitrimer composites

Recently, polymer networks with dynamic covalent bonds, called vitrimers or covalent adaptable networks, have attracted significant attention for their reprocessability owing to the transient characteristics of the dynamic bonds in crosslinked networks. For enhancing mechanical properties, highly tunable silica particles can lead to widened possibilities of chemical reactions on polymer-particle interfaces. Also, the tunable structures of the crosslinked network will allow control of the relaxation behavior of the crosslinked network to improve reprocessability. However, the covalently crosslinked or confined polymer-particle interface will alter the resulting properties abruptly.

In order to understand the bulk reprocessability of multicomponent composite systems, we need to deconvolute the interfacial effect of polymer-particle interface from bulk polymer-polymer domains. We designed mechanically resilient and reprocessable polymer composites by introducing surface-functionalized silica particles as a dual tunable moiety. We modify the surface of particles with functionalities that allow them to dynamically crosslink into the network themselves and study the kinetics of crosslinking and degradation. We use Aza-Michael adducts with the silica particles modified to have amine surface functional groups. The trimethylolpropane triacrylate (TMPTA) and various molecular amine crosslinkers form a dynamic covalent crosslinking network and particles are added that also bond with the resin through the additional Aza-Michael reaction. We examine how the functionalized particles affect not only the bond exchange rates of the composites but also detect how the polymer-particle interface impacts the overall bond exchange rates and mechanical properties. In addition to the insights gained by designing new composite systems with dynamically bonding particles, our studies of polymer-particle and polymer-polymer interfaces will play a large role in moving this work towards applications.

    

Effect of Extreme Nanoconfinement and Polymer-Nanoparticle Interactions on the Thermodynamics of Multiphasic Nanocomposite Films

Polymer blends are often immiscible, leading to the formation of chemically dissimilar phases. Novel compatibilization techniques are required to maximize the synergistic properties of these blends. In this work, we evaluate the effect of confinement and polymer-nanoparticle interactions on the phase behavior of polystyrene (PS) and polymethyl methacrylate (PMMA) confined within the interstitial pores of a dense SiO₂ nanoparticle (NP) packing. A blend of PS and PMMA with SiO₂ NPs is annealed at 150-200°C for up to 24hr. The confinement ratio (Γ), which is the ratio of a polymer’s radius of gyration to the NP packing’s pore radius, is varied between 0.25 and 8 by changing the molecular weight of the polymers between 7 and 99 kg/mol, and the size of the NPs from 7 to 61nm. Systems with Γ<1.5 display macroscopic phase separation, with globular PMMA domain sizes around 10 microns as characterized by both optical and scanning electron microscopy. When the system is confined further to Γ>2, macroscopic phase separation is suppressed down to a length scale of at least 500nm. Passivation of SiO₂ NPs with chlorotrimethylsilane, which weakens the interactions between PMMA and SiO₂, leads to macroscopic phase separation at all tested Γ up to 5. These results provide new insights into the interplay between confinement and polymer-NP interactions on the miscibility of two polymers, which could be useful for designing blend-based nanocomposite films with novel properties.   

Author not Attending

Co-assembly of nanoparticles with different shapes and sizes provides an exciting platform to produce multi-functional optical materials and devices. Cellulose nanocrystals (CNCs) self-assemble in a way to form left-handed cholesteric films with high reflectivity due to the Bragg reflection. Creating such helicoidal structures with plasmonic materials can lead to the development of meta-surfaces and security features. However, the experimental work on combining the self-assembly of Au-NRs with CNCs had limited success at a 3% maximum concentration of AuNRs was possible without disrupting the cholesteric order.

To understand the physical and theoretical limitations of this co-assembly system, we used molecular dynamic coarse-grained methods with Gay-Berne potential with particle systems of different sizes and densities. Our experimental and modeling work has a strong agreement that the charge and the density of Au-NRs have a significant influence on the co-assembly. Negatively charged AuNRs can distribute uniformly and align in the same direction with CNCs and the particle systems with higher aspect ratio distributions would have successfully co-assembled, as AuNRs would prefer to fill the vacancy between the cholesteric structures formed by CNC particles. Our further studies explain the limit of maximum concentration from density, as lighter particles (CNCs) would reach assembly conditions compared to the AuNRs. Our work sheds new light on the understanding of the self-assembly of multi-component systems with polydispersity and charge variations and takes our understanding one step further in developing optical materials.

Using carbon nanotubes for photothermal treatment of cancer

CNTs functionalized with the protein annexin V (AV) can be used to kill cancer cells via photothermal therapy. Such CNTs bind specifically to anionic phospholipids on the surface of the cancer cells. Subsequential heating of these CNTs with near infrared radiation or radio frequency fields can damage the metastatic cancer cells. We are study heat transfer from CNTs to the cell, using energy conservative Dissipative Particle Dynamics (DPDe) from Large-Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). Coarse-grained CNTs (a Cylinder consisting of beads) are modelled in a water bead medium, to simulate heat transfer from CNT to the medium. Heat transfer from the CNTs to the protein, medium and the membrane will be studied in the same manner. Our goal is to optimize the functionalized CNT for this application.

    

Freeze-Burn: Fabrication of Porous Carbon Networks via Polymer-Templated Rapid Thermal Annealing

Porous carbons are a valued class of materials widely applied from CO₂ capture to energy storage, but existing fabrication methods are tedious and require multiple steps. We introduce “freeze-burn” as a simple method for creating porous carbon networks by polymer-templated rapid thermal annealing (> 50 °C/sec). This technique leverages thermally induced phase separation for templating and fixes the templated structure by instantaneous polymer degradation. As a model system, particles of reduced graphene oxide were mixed with a polystyrene/poly(vinyl methyl ether) blend to probe the resulting morphologies. We determined that the dependence of macropore formation on particle loading and annealing ramp rate is captured by a single parameter, glass transition temperature, which is indicative of polymer mobility. Without changing the template composition or processing conditions, we demonstrated the applicability of freeze-burn to other carbon materials, such as graphene oxide, carbon black, carbon nanopowder, and carbon nanotubes. This method was improved with a carbonizable polyacrylonitrile-based blend system to generate nanopores and improve the mechanical integrity of prepared porous networks for supercapacitor applications. We anticipate this work to inspire simple, scalable approaches for creating porous materials.   

Molecular Dynamics Simulation of Xanthan Gum and Locust Bean Gum Blends

Xanthan gum (XG) and locust bean gum (LBG) are naturally occurring polysaccharides that display non-Newtonian and high-viscosity behavior in aqueous solutions. When mixed together, they demonstrate dramatic increase in rheological properties as compared to their individual solutions. Despite the large number of experimental studies on such polymer blends and their individual components, little is known about the mechanism of gel formation when the polymers are mixed. Here, we use coarse-grained molecular dynamics simulations to investigate the mechanical properties of solutions of XG and LBG; as well as a binary mixture of polymers to study the effects of polymer chain concentration and interaction on the structure formation and gelation of these systems. We model polymers as linear chains, with XG being five times longer than LBG. We also studied the effect of adding inorganic sheet-like fillers to each of these polymer systems where addition of nanofillers demonstrated a much larger increase in viscosity due to physical crosslinks between polymer chain and nanofillers. Our results show that the assembly between nanofillers is an important determinant of the final properties of the gel which is facilitated by the types and interactions of the polymers used.

    

Nanoparticle and Polymer Diffusion Measured by ToF-SIMS

Existing methods of measuring NP diffusion include dynamic light scattering (DLS) and Rutherford backscattering (RBS) but are greatly limited in the materials they can evaluate and the accessible length scales. Here, we apply time-of-flight secondary ion mass spectroscopy (ToF-SIMS) to separately measure NP and polymer diffusion. For nanoparticle diffusion, we fabricate trilayer polymer-nanocomposite-polymer samples and measure the cross-section with ToF-SIMS to extract the NP distribution in 3D. Processing the 3D data corrects for sample tilt, deconvolutes the beam resolution, and integrates the data to extract a 1D NP concentration profile, to which a diffusion equation is fit. By comparing diffusion coefficients measured by our ToF-SIMS method and RBS for the same poly(2-vinylpyridine) (P2VP) and silica NP system, we validate our experimental methodology.  Polymer diffusion was similarly measured using a trilayer sample of polystyrene (PS)-deuterated PS-PS; the PS diffusion coefficients for 69k and 423k are in excellent agreement with prior results. This work establishes ToF-SIMS as a reliable and versatile tool for measuring diffusion coefficients.

    

Effects of Film Thickness and Nanoparticle Loading on Surface Wetting of Grafted Nanoparticles in Polymer Nanocomposites

Polymer nanocomposites (PNCs) allow for a broad range of applications owing to their versatile properties, which are directly correlated to the spatial arrangement of the nanoparticles in the polymer matrix. For instance, surface properties such as wettability, friction, and durability depend on the wetting behavior of nanoparticles in PNCs. Previously, we determined the diffusion coefficient of poly(methyl methacrylate) grafted silica nanoparticles (PMMA-NPs) in a poly(styrene-ran-acrylonitrile) (SAN) matrix using time-of-flight secondary ion mass spectrometry (ToF-SIMS). In this work, we continue to study the effect of film thickness and nanoparticle loadings on the PNC structure and PMMA-NP diffusion in SAN using ToF-SIMS, along with techniques such as atomic force microscopy and grazing-incidence small-angle x-ray scattering. To decouple the surface and thermodynamic contributions, we investigate the effect of confinement on PNC structure using films with a thickness from 100 to 1500 nm. By adding 10 wt.% of PMMA-NPs to SAN compared to prior studies with 25 wt.%, we study how decreased NP loadings affect nanoparticle diffusion to the surface. The results allow for greater control over NP dispersions and PNC morphologies, which are crucial in tailoring PNC properties.   

Photothermal Heating of Gold Nanorods in Poly(ethyl cyanoacrylate)

We are interested in thermally-driving chemical reactions in small volumes within a solid material, where diffusion of reactants and products is limited. Photothermal heating of nanoparticles in polymers is a potential path to better understanding and controlling polymer degradation and generating useful carbonaceous by-products. In photothermal heating, nanoparticles absorb light that enters the material and convert the energy to heat. This forms high-temperature pockets around each nanoparticle and can lead to localized chemical reactions. Poly(ethyl cyanoacrylate) (PECA) degrades by depolymerizing and in confinement the monomer will repolymerize to form oligomers. A reaction side product in this process is carbonaceous. To study this reaction, gold nanorods in PECA were photothermally heated. The resultant degradation was characterized through optical analysis of the carbonaceous by-products, which are initially luminescent, TEM analysis, and Raman spectroscopy. Outcomes from photothermal degradation are compared with those from homogeneous heating.   

Compatibilization of a Crystalline Polymer Blend by Molecular Design and Control of Crystallization

Managing end-of-life plastics is a challenging problem for a variety of reasons, including the complexity of recycling mixed waste streams. Most polymer pairs don’t mix, and any product made from such a mixture will exhibit poor properties. These polymer mixtures can be enhanced by their compatibilization with proper polymeric interfacial modifiers. A compatibilizer strengthens the interface between immiscible polymers to stabilize the blend. Previous research by our group has examined the ability of chlorinated polyethylene (cPE) to compatibilize PVC and polyolefin elastomers (POE). However, the correlation of cPE and POE crystallinity on the compatibilization process is not fully understood.  We will report on the correlation of annealing temperature to the strength of a POE/PVC interface that is compatibilized with a blocky cPE.  These results show a correlation of interfacial strength to the rate of crystallization of each component, i.e., where the annealing temperature sits relative the Tg and Tm of the blend components.  This presentation will therefore provide insight into the molecular design and thermal processing protocols needed to rationally control crystallization for phase separated crystalline polymer blends, including those that are most relevant for mixed waste streams in polymer recycling.

    

Enhancing Polyolefin Recycling with Cellulose Nanocrystals

Recycling and reuse of polyolefin waste are limited due to loss of properties after recycling and complicated by the presence of differing polymers which are not compatible and differing microstructures (e.g., high- and low-density polyethylenes or varying types of polypropylenes). Hence, upcycling of polyolefin waste to engender new properties that are retained during multiple recycling cycles is a major challenge and interest. Here, cellulose nanocrystals (CNCs), nanoparticles derived from cellulose, were functionalized and investigated as compatibilizers for immiscible polyethylene and polypropylene blends. CNCs were functionalized in the melt with grafted polypropylene chains and the polymer functionalization and grafting density were quantified with chemical and thermogravimetric analyses. Preliminary morphology characterization showed droplet size reduction with the addition of functionalized CNCs to the polyethylene/polypropylene blend. Nanoparticle compatibilization mechanisms are currently under exploration, such as droplet coalescence suppression and interfacial tension reduction.   

Limiting Side-Reaction Impact on Recyclability of Diels-Alder Networks Containing Furan-Maleimide Resins

Among recyclable polymers, those functionalized with furan-maleimide chemistry using a Diels-Alder (DA) mechanism are a popular choice. Due to the retro-DA (rDA) reaction at high-temperature (80-140°C), a range of re-processable thermoplastic and thermosetting polymers are possible. However, potential side reactions are undesirable in the development of multiple self-healing, processing, and recyclable polymers. Hydroquinone (HQ), a well-known free-radical inhibitor, is often added to prevent the maleimide free-radical homopolymerization mechanism that occurs above 110°C, the predominantly cited side reaction. We demonstrate HQ’s inhibiting ability through spectral, thermal, and rheological analyses of thermosetting furan-maleimide polyethers (4+2 or 4+3 functionalities). FTIR and NMR confirm the epoxy-amine reaction is near completion, which is involved with furfuryl functionalization, ruling out amine-maleimide reaction. Further, by using non-stoichiometric ratios of the reactive groups and longer chain lengths, which changes the network connectivity and properties, the rate of maleimide homopolymerization is also affected.

    

A mesoscale approach to model polyethylene degradation under a local temperature gradient

A major focus in recycling plastics has been towards chemically synthesizing monomers for low ceiling temperature polymers instead of controlled depolymerization of abundantly used polyethylene. Controlled depolymerization can be achieved by introducing microwave absorbing nanosheets in the bulk of the polymer. Under microwave irradiation, local temperature gradients are introduced in the vicinity of the nanosheets. In this work, we develop a framework for modeling the thermal random scission of polyethylene under the action of such local temperature gradients. We use the energy conserving dissipative particle dynamics (eDPD) approach along with the modified segmental repulsive potential (mSRP) and model bond breaking via a stochastic approach that simulates first order degradation reaction kinetics. We first simulate melts with various degrees of polymerization at various constant temperatures and measure the static and dynamic properties of the polymer chains. Then, we subject the equilibrated melt to depolymerization under constant temperature and track evolution of dispersity and average molecular weights in the system. The time evolution of these properties follows previously known analytical trends. Under the action of a temperature gradient, faster depolymerization near the high temperature region results in formation of shorter polymer fragments with higher diffusivity compared to the longer chains in the low temperature region.   

Synthesis and characterization of reversible epoxies for recyclable 3D printing by aphotothermal conversion

Photothermal conversion using plasmonic nanomaterials for reversible epoxies based on the Diels-Alder

reaction is a promising approach for targeted self-healing materials and recyclable 3D printing materials.

In the presentation, reversible epoxies and their composite with plasmonic nanomaterials will be

studied for their 3D printability and mechanical properties before and after recycling processes. Various

formulations of reversible epoxies will be examined for 3D printing, for example, architecture, molecular

weight, the mixing ratio between precursors, and concentration of plasmonic nanomaterials. Processing

parameters for 3D printing of a selected formulation. Recycle processes will be carried

out by a solution method (i.e., dissolution in hot solvent and recovery) and a thermal cycle using bulk

heating or light. Their mechanical properties will be characterized and compared before and after

the recycling processes.   

Fabrication of High Aspect Ratio Nanoconfined Environments for Single-Molecule Experiments

High aspect ratio (width to height) nanoconfined environments create a slit-like environment that can be used to mimic interfaces, making them valuable tools for investigating the physics of single polymeric molecules. In this study we demonstrate the fabrication of optically transparent nanofluidic devices using borosilicate glass substrates. We use photolithography and wet etching to pattern multiple nanochannels with aspect ratios between 20 and 100× onto a single, standard size glass wafer. We characterize all etched nanochannels with optical profilometry, providing detailed statistics about channel dimensions and roughness. We use a combination of ammonium hydroxide activated, low temperature bonding and high temperature thermal annealing to add glass covers to nanochannels without causing channel collapse. We laser cut inlet/outlet ports into glass covers to produce fully functional fluidic devices, and finally dice multiple nanofluidic devices out of a single glass wafer, allowing for the processing of multiple nanoconfined environments in parallel. These optically transparent nanofluidic devices enable measurements of dynamic confined polymer behavior using single-molecule fluorescence microscopy.   

Zwitterionic unimolecular bottlebrushes for mucosal transport

Mucus is a viscoelastic and adhesive gel that protect organs from allergens, bacteria, and viruses. On the other hand, it also acts as an obstacle to effective mucosal drug delivery. Particles targeted to specific sites can be efficiently trapped and removed by mucus, thereby limiting the effectiveness of drug delivery. Recent studies have observed higher diffusivity of rodlike particle leading to deeper mucus penetration than that of spherical ones with equivalent surface chemistry. Therefore, we discuss the use of rod-like unimolecular bottlebrushes and evaluate the effects of shape, size, surface chemistry, and rigidity for mucosal transport. Our strategy for generating mucopenetrating polymers is by using functionalized zwitterionic bottlebrushes copolymers. We will discuss the effects of backbone length, grafted side-chain length, backbone rigidity, and surface functionalization on transport. Analysis of bottlebrush copolymers’ properties were done by DLS, AFM, SAXS, TIRF (Total Internal Reflection), and confocal microscopy. The effects of the molecular properties of these bottlebrushes on their transport through mucus was evaluated using MUC5AC samples.

    

Effect of Ionic Liquids on the Conformation of Ionizable Polymers from a Single Molecule to an Assembly

Ionizable polymers have been incorporated successfully into light weigh energy applications.  However, the mobility of ions, critical to the function these polymers is rather low. To overcome this issue, highly mobile salts have been added, among them are ionic liquids. Though salts enhance mobility, they interact with the polymers, affecting their structure and dynamics. Here we probe the effects of a model ionic liquid family, 1-alkyl 3-methylimidazolium bis (trifluoromethyl sulfonyl) imide), on the conformation of  polystyrene sulfonate (PSS) in the ionomers and the polyelectrolyte regimes, using molecular dynamics simulations. Starting with single PSS molecules, with sulfonation fraction f ranging from 0 to 0.96, and building to more complex assemblies of multi-component polymers with containing a PSS block, the polymers were dissolved in the ionic liquids. Results for radius of gyration, the static and dynamic structure factors S(q) and S(q,t) of all components, the residence time as of each of the ions by the polymers will be discussed. 

    

Enzyme-mediated polyprotein conjugation for single-molecule force spectroscopy

Single-molecule force spectroscopy (SMFS) is a powerful tool for investigating the energy landscapes of protein folding and unfolding. However, performing precise measurements with SMFS-based tools such as an atomic force microscope (AFM) is challenging due to nonspecific interactions between the AFM tip and sample, which obscure signatures of proteins of interest in force–extension curves. Polyproteins comprising multiple, covalently linked proteins often improve the statistics of single-molecule AFM measurements and provide fingerprints to filter force–extension curves from nonspecific interactions. We demonstrate enzyme-mediated polyprotein synthesis of ion-responsive proteins in a one-pot reaction using Sortase A. We monitor polyprotein reactions using polyacrylamide gel electrophoresis and validate polyprotein products using ion-exchange chromatography and MALDI mass spectroscopy. Ion-responsive polyproteins with varying amino acid sequences enable investigations with single-molecule AFM to probe the sequence dependence of ion-driven protein folding.   

Thermoelastic behavior of thermally crosslinked high-cis-1,4-polybutadiene

Polymers exhibiting reversible elongation upon cooling (EUC) and contraction upon heating (CUH) can be used to develop actuators, fasteners, dampers, grippers, swimmers, sealants, etc. In this work, the thermoelastic behavior of a thermally crosslinked elastomer, high-cis-1,4-polybutadiene has been investigated over a range of strain and temperature. Above ambient temperatures EUC and CUH are observed under load due to the phenomenon of thermoelastic inversion. At sub-ambient temperatures, the crystallization of the polymer produces additional additive contributions to these effects. Efforts to achieve EUC and CUH in this elastomer in the absence of an external load using bilayer films and competitively crosslinked double networks will be discussed.  

 

 

    

Programmable shape morphing of all-hydrogel-based sheet by acousto-photolithography

Shape-morphing hydrogels with stimuli-responsiveness have been extensively studied over decades due to non-contact control by external stimuli. One of the most common methods is to fabricate multilayer sheets with different materials to induce anisotropic volume changes. To date, however, combining swellable hydrogel layers with non-swellable layers results in issues with interface adhesion and structural integrity. Therefore, programming shapes of hydrogels by the spatial control of rigid particles to generate heterogeneous structures are in demand. Here, we develop the all-hydrogel-based actuators by integrating photothermal particles within the hydrogel matrix through acoustically driven particle assemblies to reach programmable shape deformation through temperature and light actuation. We anticipate this approach to program shape morphing in a single hydrogel sheet will open a new path for promising applications of composite hydrogels in the fields of biomimetic system, biomedical devices and soft robotics.

    

Tunable Swelling Behaviors and Transparency of Stimuli-responsive Supramolecular Hydrogels for Multi-actuation

Smart hydrogels are promising candidates for use in actuation and sensing due to their stimuli-responsive shape morphing and their easy integration with other functional materials. However, the development of multifunctional integration of stimuli-responsive hydrogels for various actuations has not been well unveiled. In this work, we synthesize a novel 3D printable multi-stimuli-responsive poly(N-isopropylacrylamide-co-acrylamide-g-ureidopyrimidinone) (PNAU) supramolecular hydrogel. The swelling behavior, mechanical strength and transparency of PNAU hydrogels can be adjusted by external temperature and solvent micro-environment owing to the molecular design of these supramolecular hydrogels, thus leading to the shape morphing and transparency camouflage. Moreover, the rheological property is studied to optimize the 3D printability of PNAU hydrogels thus the demonstration for multi-actuation with complicated structures is prepared and tested.   

Photomechanical Hydrogels from Visible Light Responsive Supramolecular Complexes

Stimuli-responsive hydrogels are an attractive material platform to create functional devices with applications that include soft robots and biomedical materials. Light-responsive hydrogels are of interest due to the fine spatiotemporal control that light affords. There has been considerable work in this area focused on inclusion of photothermal particles in a thermoresponsive hydrogel matrix, and, while these materials do achieve significant volume change upon light exposure, they suffer from decreased resolution and nonpersistent response due to heat dissipation in the system. Leveraging photochemical response in hydrogels alleviates these issues, however, this is typically achieved using either azobenzene, which relies on a relatively small change in polarity upon isomerization to drive volume change, or spiropyrans, which generally have narrow pH ranges in which they operate. Our group has previously addressed these shortcomings by including photoswitchable supramolecular complexes between azobenzene and cyclodextrin, which enable rewritable shape changes in hydrogels using spatially patterned light. Here, we build upon that work by developing supramolecular hydrogels that include visible-light responsive photoswitches. We characterize the resulting host-guest interactions and demonstrate photochemically driven shape change using only visible light, which increases penetration depth and improves compatibility with biological materials.

    

Title: Cellular proliferation-driven curvature changes in stimuli-responsive engineered living materials

Abstract: Stimuli-responsive engineered living materials, ELMs, are of interest due to their ability to actuate and display a physical response, which can be harnessed for application in soft robotics and bioremediation. Typically, stimuli-responsive ELMs have been prepared using a one-pot synthesis approach where living cells are incorporated into a monomer precursor solution followed by crosslinking. Here we synthesize a stimuli-responsive ELM using a new approach, diffusing cyanobacteria cells (Synechococcus elongatus PCC 7942) into a crosslinked thermo-responsive hydrogel, poly (N-isopropylacrylamide) (PNIPAm). We show that introducing living cells via diffusion creates a pseudo-bilayer and subsequent curvature change of the stimuli-responsive ELM as the cells proliferate. We anticipate that the understanding of cyanobacteria-PNIPAm system will spur the development of more advanced stimuli-responsive ELMs capable of complex actuation.

Funding Acknowledgement: This work was supported by the National Science Foundation through University of California San Diego Materials Research Science and Engineering Center (UCSD MRSEC), grant number DMR-2011924.

    

Light-powered solution-state osmotic actuators

Amongst the variety of actuators developed to date, solution-state osmotic actuators show unique promise for use in photomechanical devices because of the possibility of using optically thick samples without sacrificing photochemical conversion. The efforts made to realize solution-state actuators to date have relied on saturated osmolytes, or electrolytes, to drive solvent flux, but have suffered from irreversibility, slow response speeds, and/or the need to be tethered to additional electrical equipment. We have demonstrated that the osmotic pressure of a solution containing an azobenzene polymer and α-cyclodextrin molecules can be tuned between a 'high' and 'low' value cyclically by exploiting the photo-addressable host-guest interactions between the two species. We find that the resulting change in osmotic pressure can reversibly drive volume changes in a microfluidic system. These actuators could potentially find applications in light controlled micropumps, underwater shape-changing surfaces, and biomedical devices.   

Formation of Mesoglobules and Phase Separation at Variable Pressure in Aqueous Poly(N-isopropylacrylamide) Solutions Probed with Very Small-Angle Neutron Scattering

Thermoresponsive polymers featuring lower critical solution temperature (LCST) behavior in aqueous solution may serve as simple model system to investigate the effect of pressure on hydration and mesoscopic rearrangement during phase separation. We present structural studies of the size and water-content of the mesoglobules formed in a semidilute aqueous solution of Poly(N-isopropylacrylamide) (PNIPAM) in dependence on pressure at temperatures above the coexistence line. To characterize the large sizes of the mesoglobules as well as their water content, we use very small-angle neutron scattering (VSANS). The transition behavior between small mesoglobules (sub-micron) observed in semidilute PNIPAM solutions at low pressure and the large micron-scale aggregates at high pressure is investigated along various pathways in the pressure-temperature plane.

    

Unravelling the Mechanism of Viscoelasticity in Linear and Pendant Polymers with Phase Separated Dynamic Bonds

Incorporation of dynamic bonds within polymer structure enables properties such as self-healing and recyclability. These dynamic bonds, referred to as stickers, can form clusters by phase-segregation from the polymer matrix. These systems exhibit interesting viscoelastic properties with an unusually high and extremely long rubbery plateau. Understanding how viscoelastic properties of these materials are controlled by the hierarchical structure is crucial for engineering of materials for various future applications. Here we studied such systems made from telechelic polydimethylsiloxane chains, as well as pendant functionalized chains by employing a broad range of experimental techniques. We demonstrate that formation of a percolated network of interfacial layers surrounding clusters enhances mechanical modulus in these systems, whereas stickers hopping between the clusters results in terminal flow. Analysis also reveals that the concentration of stickers plays the critical role in viscoelastic properties of these materials, while specific placement of the stickers (chain ends or along the chain) only impacts the behavior on time scale between pulling the sticker out of the cluster and terminal relaxation. From our results, we formulate a general scenario describing viscoelastic properties of polymers with phase-separated dynamic bonds, including the role of architecture. This understanding will foster development of recyclable materials with tunable rheological properties.

    

The role of soft segments on the stress relaxation of thermoplastic elastomers

Thermoplastic elastomers (TPEs) are mostly block copolymers or polymer blends that consist of hard (HS) and soft (SS) segments. Hard segments form crystallites, which act as thermo-reversible crosslinkers. On the other hand, the glass temperature of soft segments is usually lower than room temperature, which enhances processability. Even though TPEs have been used commercially since 1950s, their deformation mechanism is not understood fully at a molecular level. Two players are involved: a crystalline structure and a soft segment. In semi-crystalline homopolymers, tie chain fraction determines the mechanical response. In addition, in TPEs, soft segments can readily dissipate stress due to their higher mobility. Therefore, it is important to understand how each segment contributes to total stress. In this work, we conduct molecular dynamics simulations with a modified Kremer-Grest model. We consider triblock copolymers (HS-SS-HS) with different SS lengths. After cooling, we apply uniaxial and constant engineering strain on these systems. We find that Young's modulus and stress decrease with an increase in SS length. Interestingly, the transition in the deformation mechanism occurs: HS contributes dominantly to stress with short SS while SS contributes dominantly with long SS. To understand this transition, we also calculate nonaffine displacements, and the reorientation and breakage of crystallites during deformation.   

The Effect of Lipid Phase Behavior on Polymer Binding to Liposomes

PEO-PPO block polymers interact with lipid bilayers and can have a stabilizing effect on cell membranes under stress. The stabilization mechanism is unknown but prior studies have found that numerous cell signaling pathways are upregulated and downregulated. Liposomes are useful membrane models because they can be prepared with custom compositions to probe the effect of different membrane components on polymer-lipid interactions. Prior research has shown that ternary mixtures with saturated/unsaturated lipids and cholesterol lead to phase coexistence. In this work, we leverage published ternary phase diagrams to explore the impact of lipid phase behavior on the binding of F127 to different membrane compositions of POPC, PSM, and cholesterol. Unimodal liposomes were prepared with vesicle extrusion diameter of 50 nm. Dynamic light scattering was used to validate the prepared liposomes, and PFG-NMR was used to quantify the amount of F127 bound to liposomes. We observed that cholesterol significantly reduced polymer binding to the liposomes relative to the POPC control. Addition of PSM also decreased binding non-monotonically. Compositions with Ld/Lo/So coexistence showed maximal binding of polymer, possibly because phase boundaries on the lipid bilayer are attractive binding sites.   

PEO-Grafted Gold Nanopore: Grafting Density, Chain Length, and Curvature Effects

Polymer-grafted nanopores have found various nanotechnological applications such as separation membranes and nanopore-gated control of materials transportation (e.g., nanofluidic devices). The morphological change of the grafted polymers facilitates precise control of materials transportation, making them promising in numerous fields. In order to design these nanomaterials with desired properties, a good understanding of the structural and hydration properties of grafted layers and the interaction between polymers and solvents is essential. Here, by atomistic molecular dynamics simulations of poly(ethylene oxide) grafted gold nanopore, we elucidate the effects of polymer grafting density and chain length, as well as the curvature of the nanopore on the properties of the grafted PEO layer. We show that the polymer layer starts from an adsorbed pancake shape at a low grafting density, transitions to a mushroom-like or overlapped chain at a moderate grafting density, and to a densely packed brush at a high grafting density. Correspondingly, PEO transforms from a well-hydrated state to a dehydrated state when grafted at low to high grafting densities. The layer thickness follows the scaling found in a planar brush when the height is less than the pore radius (weak confinement) while when confined in a nanopore with high curvature, PEO chains rearrange themselves into a conical shape (strong confinement). Different regimes of polymer layers have been identified and a unified diagram of states is provided which could be used as guidance for polymer-grafted nanopore design.

    

Precise Control of Nanoparticle/Polyelectrolyte Brush Interactions by Tuning the Polymer Charge Fraction

Controlling the interactions between nanoparticles and surfaces in complex media is crucial to realizing a variety of nanoparticle-based applications reliant on tuning nanoparticle transport and diffusion. Creating a weak polyelectrolyte brush is a promising technique to control the nanoparticle/polymer brush interactions by tuning the pH. However, it is challenging to precisely control their interactions due to the sharp transition of the polymer brush properties with pH. In this study, we demonstrate that the nanoparticle/polymer brush interactions can be effectively and finely controlled by adjusting the polymer charge fraction. To control the charge fraction, quaternization of polystyrene-b-poly(2-vinylpyridine) (PS-b-P2VP) was performed with 1-bromoethane (1-BE). FT-IR and NMR spectroscopy demonstrated that the charge fraction was readily tuned by adjusting the stoichiometric ratio between the monomer concentration of P2VP blocks and 1-BE. The quaternized P2VP brushes with various charge fractions were prepared using quaternized PS-b-P2VP. Quartz crystal microbalance with dissipation monitored the nanoparticle adsorption and desorption dynamics as a function of charge fraction and demonstrated that the nanoparticle/polymer brush interactions were controlled. This precise control of their interactions suggests potential applications of the quaternized P2VP brush for functional devices that adsorb and desorb nanoparticles.

    

Structure and Organization of Amphiphilic Mikto-Grafted Molecular Brushes at Oil/Water Interfaces: A Dissipative Particle Dynamics Study.

It has been recently found that amphiphilic molecular bottlebrush polymers are able to stabilize oil/water interfaces at extremely low concentrations, creating a pathway to develop stable oil-in-water emulsions for applications in cosmetics, oil, food, and pharmaceutical industries. An understanding of the effect of the different molecular parameters on the structure and organization of these polymers at oil/water interfaces is an important step towards the molecular engineering of advanced bottlebrush-stabilized emulsions. Amphiphilic mikto-grafted molecular brushes possess tunable architectural parameters, including the backbone length, N_bb, and the lengths of the hydrophilic and hydrophobic sidechains, N_A and N_B, respectively. All of these are expected to have a considerable effect on the conformation of these bottlebrushes at the oil/water interface. In this work, we have performed extensive numerical simulations using Dissipative Particle Dynamics to investigate the role of side chain size-asymmetry and backbone molecular weight on the structure and organization of bottlebrush polymers at planar oil/water interfaces. The effect of the polymer concentration was also investigated. To characterize polymer structure, we computed the gyration tensor, G_M, which was used to calculate the radius of gyration, R_g, the relative shape anisotropy parameter, A₃ and the asphericity, b; end-to-end distances of sidechains and backbone were also computed. In addition, an orientational order parameter tensor was computed to quantify the organization of the bottlebrushes at the interfaces.   

Smart membranes produced through lyotropic liquid crystal templating

In this study, we present the synthesis of smart membranes, which can change their pore size in response to an external stimulus, through lyotropic liquid crystal (LLC) templating. Transcriptive and synergistic templating is used to create membranes with different pore sizes. We show that mesoporous thermoresponsive membranes can be created through transcriptive templating, whereas thermoresponsive membranes with a pore size of 2-3 nm can be readily obtained using synergistic templating. The experimental results reveal that dynamic selectivity as well as improved cleaning efficiency of the synthesized membranes can be achieved via changing the pore size with temperature.      

    

Malleable mesoatom reactions in tubular networks

Mesoatoms in soft-matter crystals consist of large groups of flexible molecules whose sub-unit-cell configurations couple strongly to supra-unit-scale symmetry and differ strongly from conventional hard matter atoms by their ability to deform easily into new shapes and sizes. Recently, twin boundary (TB) mirror defects have been quantified in the tubular double diamond (DD) and double gyroid (DG) network phases^1,2 and new types of mesoatoms identified by employing scanning electron microscopic tomography. Moreover, the order-order transition (OOT) between the DD and DG phases has also been investigated with new types of transitional mesoatom structures visualized. Such data allows extraction of mesoatom reactions occurring within these transition zones. Various nodes split and then recombine to achieve the structural changes. In terms of node functionality, the number of struts f connected to a node, the f = 4 DD nodes transform into pairs of f = 3 DG nodes in the DD-DG OOT.  In the DD twin, one f = 3 node and one f = 4 node create a pair of f = 5 and f = 3 nodes at the grain boundary. Such 3D structural data motivates theoretical investigations of the role of malleable, self-assembled soft crystal mesoatoms in phase transitions and defect formation.   

Investigating Structural Effect of Quaternizing Additives on ShapeTransition of Block Copolymer Particles

Co-assembly of block copolymers (BCPs) and organic/inorganic additives affords the design of various hierarchical nanostructures. In this work, we investigate the shape-changing capabilities of poly(styrene-block-2-vinylpyridine) (PS-b-P2VP) BCP particles upon quaternization with a series of bromoalkyl benzene additives with different alkyl spacer lengths. The bromoalkyl benzene additives exhibit different hydrolyzing and quaternizing behaviors depending on their chemical structures. When benzyl bromide (BB) is used, the PS-b-P2VP BCP particles exhibit a dramatic shape transition from ellipsoids to ellipsoids with swelled discs, swelled buds, and vesicles. These morphological transitions are attributed to the synergistic quaternization and protonation of the P2VP chains via the hydrolysis of BB in aqueous media. Upon increasing the molar ratio of BB to 2VP units, the pH of the surrounding aqueous solutions significantly decreases, and the protonated P2VP domains are swelled by the surrounding water, resulting in interfacial instability of the emulsion interface. When the additives contain longer alkyl spacers, the additives lead to a narrower range of quaternization-dependent particle morphologies due to the absence of the hydrolysis of the additives. We carefully investigate the structural effect of the quaternizing additives on the change of pH, degree of quaternization, and interfacial tension to elucidate the mechanism of the additive-driven particle morphology transitions.

    

Polyethylene Oxide – Polytetrafluorethylene Blends and their Nanofibers

Blends of (PEO) – Polytetrafluorethylene (PTFE) were obtained by adding PEO powder to the submicron water suspension of PTFE. Eventually, deionized water was added to facilitate the homogenization and to achieve an overall viscosity capable to sustain nanofiber production by force spinning. The PEO – PTFE mixture was homogenized by sonication. Films of PEO-PTFE were obtained by the removal of water in a vacuum oven at 50 °C, overnight. Mats of nanofibers of PEO-PTFE were obtained by force spinning of water solutions of PEO-PTFE blends at various concentrations.  PEO has a glass transition of – 35 °C and a melting temperature of about 65 °C, while PTFE has a low glass transition of about – 100 °C and a very high melting temperature (about 335 °C). There is a controversy about the glass transition in PTFE with eventually an additional relaxation at about 116 °C. PTFE is among the few polymers that exhibit ferroelectric, piezoelectric, and pyroelectric capabilities. The stretching of the polymer solution (and implicitly of PTFE) during the force spinning is expected to result in the alignment of the PTFE chains within the mats. Because PTFE contains a larger number of F atoms per monomer than PVDF, it is expected that the local order in mats of PEO-PTFE will be stronger than in mats of PEO-PVDF, at the same spinning rate. Consequently, extended spectroscopic studies (by X – Ray diffraction, Raman and FTIR spectroscopy) were focused on the PEO-PVDF films and mats.

Electron microscopy images complemented by elemental analysis provided information about the morphology and composition of PEO-PTFE films and mats with emphasize on the distribution of F atoms.

Acknowledgments: We acknowledge the financial support for this research by National Science Foundation PREM Grant DMR 2122178.

    

Antifouling and antimicrobial properties of surface micelle structures fabricated by the self-assembly of block copolymers on solids

Surface topology is of great interest to develop bactericidal surfaces in place of traditional

chemical-based approaches that are often toxic to human beings and environments. Many

experimental and computational studies reported a concept of engineered topographies to

produce surfaces with controlled interactions with proteins and bacteria. Here we focus on

engineered nanosurfaces inspired by the naturally occurring ones found on the surface of insect

wings (i.e., hexagonal arrays of cylindrical nanopillars). We use the self-assembled micelle

structures of block copolymers on silicon substrates using spin-coating and dip-coating as a

rational model. We characterize the surface structures and physical properties using a suite of

experimental tools including water contact angle measurements, atomic force microscopy,

scanning electron microscopy, and grazing incidence small-angle X-ray scattering. The

antifouling properties of the micelle structures against model proteins (i.e., Bovine Serum

Albumin and fibrinogen) and bacteria (Escherichia coli and Listeria monocytogenes) will be

discussed. We will also discuss the effects of the geometric parameters of the micelle structures

on the properties.   

Understanding Ionomer Membrane Morphology through Computational Analysis of Small Angle Scattering Experiments

Nafion™ membranes are widely used in fuel cells and water electrolyzers due to their superior mechanical and ion transport properties. The morphology within these membranes dictates the ion transport through their ionomer hydrophilic domains. While it is known that the structure of ionomer hydrophilic domains changes with different extents of hydration and processing techniques, the structural evolution of these domains during processing is still not fully understood. Small-angle scattering (SAS) measurements are used to characterize structure at multiple length scales and can provide insights into the structural evolution of ionomer domains at various processing conditions. In this poster, we will present our ongoing work to extend the 'Computational Reverse Engineering Analysis for Scattering Experiments' (CREASE) algorithm, previously developed for analysis of one-dimensional SAS profiles, towards analysis and interpretation of two-dimensional SAS profiles. Specifically, we will demonstrate the steps involved in the development of CREASE for analysis of two-dimensional SAS profiles and its application to interpreting the structure of Nafion™ ionomer films.   

Investigating the impact of ionic correlations on selective salt transport in ligand-functionalized polymer membranes

Functionalizing polymer membranes with ligands can be used as a method for imparting host-guest interactions into the membrane, thereby enabling selective transport of a particular ionic species over others. Prior experimental/computational studies on membrane transport have assumed an ideal salt transport scenario by neglecting any correlations between the constituent ions. However, ionic correlations can have a profound impact on salt diffusivity within the membranes, especially at high salt concentrations. We conduct coarse-grained molecular dynamics (CGMD) simulations of salt transport in ligand-functionalized polymer membranes for both single and mixed salt systems (binary salt mixture sharing a common anion). We specifically consider ligands that can bind to cations, and conduct a parametric study by systematically varying the ligand-cation interaction strength across our simulations. Our results indicate that ionic correlations speed up salt transport at high cation-ligand interaction strengths by promoting correlated hopping of the cations between the ligands. Furthermore, mixed salt systems exhibit much more selective salt transport than their single salt counterparts until a critical value of the cation-ligand interaction strength.   

Engineering the enhanced Li+/Na+ separation efficiency through ionic liquid swollen block copolymer membranes

Lithium (Li) is a key component for the Li-ion batteries desired for sustainable energy storage devices. However, the separation of Li from natural sources is a very costly and laborious process. Membrane separations can potentially provide alternate means for the cost-effective and scalable separation of Li from mixed solutions. However, the separation efficiency of membrane-based Li separation is usually low, owing to the similar size of the ions such as sodium (Na) and magnesium. Here, we demonstrate enhanced separation of Li vs Na using ionic liquid swollen block copolymer membranes. We observe that the ionic liquid is confined to one of the blocks of the block copolymer and the membranes can be designed with high loading of ionic liquids. These ‘gel’ phase block copolymer domains embedded in the glassy matrix are responsible for the permeation of water, which is confirmed by no water permeation in the ionic-liquid free glassy block copolymer films. Furthermore, the presence of these ionic liquid-polymer domains introduces charge-based repulsions, thereby rejecting ~40-50% NaCl. However, these membranes reject LiCl ~2-5%, thus resulting in the enhanced selectivity of Li permeation over Na. We believe these membranes would serve as a platform for other ion separations as well.

    

Comparison of Various Methods to Analyze Aperiodic Percolated Nanostructures in Molecular Dynamics simulations

Aperiodic percolated structures (APS) exist in various systems ranging from polymer blends to mixtures of metallic alloys. Although the length scales of these materials differ, the same methods can be used to analyze their structural features. Transport properties in hydrated membranes depend on the detailed structure of the APS material. Therefore, it is important to establish methods of measuring morphology of APS. For this study, various APS are built by changing the compositions of acid-containing terpolymers at a fixed hydration using all-atom molecular dynamics simulation. Water diffusivity is the transport feature of interest. Thus, geometric, fractal, and network analysis methods are used to analyze APS to uncover the influence structure has on the diffusivity of water. This comparative study demonstrates the strengths and weaknesses of each analysis method and provides a platform for correlating APS with transport properties.   

Cation-polymer interactions and local heterogeneity govern the relative order of alkali cation diffusion coefficients in PEGDA hydrogels

Selective separation of monovalent cations from complex mixtures is an industrially relevant procedure necessary for the recovery of many commodity materials, such as lithium from salt brines. Unfortunately, most conventional membranes lack selectivity between monovalent ions, rendering their use in such applications infeasible. One approach to endowing membranes with ion-ion selectivity is to incorporate ion-polymer interactions into materials to bias the selective partitioning and or diffusivity of one species over another. However, little is known about the impact of such interactions on the mechanisms of ion transport. In this work, we probe the influence of cation-polymer interactions on cation, anion, and salt diffusivity in a model membrane material, poly(ethylene glycol) diacrylate (PEGDA). We do this by modeling concentrated poly(ethylene oxide) solutions via molecular dynamics simulations and compare the results to published experimental observations of LiCl, NaCl, and KCl diffusion in PEGDA. Experimentally, the order of salt and cation diffusion coefficients for LiCl, NaCl, and KCl are seen to deviate from the aqueous solution order. Molecular simulations attribute this deviation to cation-EO coordination in the membrane. Both the fraction of bound cations and the average lifetime of binding is observed to increase with decreasing hydration free energy of cations (moving down the alkali series), leading to different diffusivity trends in the membrane compared to solution. The experimentally observed diffusion order for cations and salt is recovered once membrane heterogeneity is explicitly included in our simulations. Our results reveal that cation-polymer interactions, as well as spatial heterogeneity within the membrane, play a critical role in dictating the order of alkali cation and salt diffusion coefficients in membranes.

    

Understanding the effect of polarizability on Li+ cation transport in PEO electrolytes by using molecular dynamics simulation

 Nonpolarizable force fields have been employed successfully to study a wide range of electrolyte systems of low salt concentrations. These force fields provided important insights into the structure of ionic systems. However, they showed much slower dynamics compared to experiments. Despite the expensive computational cost, therefore, it is important to consider polarizability. In this study, we aim to demonstrate the importance of polarizability in the computational simulations for ion dynamics by comparing the diffusion of Li⁺ cations. We perform all-atom molecular dynamics simulations with APPLE&P force field, and turn on and off the polarizability. We employ PEO polymer electrolytes composed of 10 chains of PEO of 54 EO monomers and 54 LiTFSI salts. We find that the coordination numbers of Li⁺ cations and PEO chains vary depending on the presence of polarizability of each component. If polarizability is properly applied, the coordination number ranges from 5 to 6. With polarization ignored, the coordination number decreases significantly. In addition to these structure differences, the diffusion of Li⁺ cations is much faster with polarizability. Interesting is that while the diffusion of Li⁺ cations becomes slower with polarizability, cooperative motion of Li⁺ cations and PEO leads to the faster diffusion of Li⁺ cations. This indicates that the diffusion of Li⁺ cations is not only affected by the polarizability but also by the structures.   

Freeze-tolerant and high-stretchable lithium acrylate-based hydrogel polymer electrolyte for superior hybrid supercapacitors

Hydrogels are an attractive material for all-solid-state supercapacitors due to their flexibility and high-ionic conductivity. However, maintaining the electrochemical performance of supercapacitors in harsh environments, such as mechanical stress or sub-zero temperature operation, is still a prominent issue to be solved. We demonstrate self-healable and freeze-tolerant fiber supercapacitors (FSCs) constructed from heteronetwork polymer electrolytes (NPEs) and metal-organic framework-derived carbon-coated carbon nanotube yarn hybrid electrodes. The NPE, composed of silica nanoparticles as stress buffers and poly(lithium acrylate) containing mobile lithium countercations, are prepared via sol-gel reaction and radical polymerization. The NPE possesses high conductivities of ~10^-1 at 25 °C and 4 x 10^-3 S/cm even at 0 °C. This is due to the Li⁺ binding strongly to water, thereby preventing water evaporation and crystallization. The FSC exhibits a high specific capacitance of 51 F/g, a high power density of 6 kW/kg, a high energy density of 44 Wh/kg, and a wide voltage range of 2.5 V. The electrochemical performance of FSC remains stable under stretching, bending, and cutting/healing cycles, and still retains ~ 92% capacity even at a low temperature (-10 °C). Our study of the combination of heteronetwork polymer electrolytes and hybrid electrodes can provide an effective strategy for the optimal design of supercapacitors, sufficiently stretchable and reliable for use in extreme environments.

    

High Conductive, Adhesive, Flexible Dual-cured Hybrid Ion-gel Polymer Electrolyte for Self-powered Energy Storage Device to Apply on Electric Vehicles

 To adress the demanding issues of achieving both high mechanical strength and stability, a solid-state electrolyte (SSE) is one of the promising strategies of next-generation electrolyte systems. This approach has attracted significant attention due to rigid mechanical strength and stability under various environmental conditions. However, a relatively low ionic conductivity ( < 10^-5 S cm^-1) of SSE, compared to a liquid electrolyte, cannot be suited for actual applications on high-performance energy storage devices. Concerning the trade-off relationship between conductivity and mechanical properties, Ionic-gel polymer electrolytes (IGPE) have been spotlighted as a useful strategy to achieve high ionic conductivity and robust stability. hybrid IGPEs which adopted dual-curing process of thermal and UV treatments can achieve highest ionic conductivity (~5 mS cm^-1), ultra-stable flexibility, and even strong adhesion to the substrates. Furthermore, microsupercapacitors based on hybrid IGPEs show multifunctional advantages for higher energy and power densities (~10¹ µWh cm^-2 and ~10¹ mW cm^-2) with higher flexible-adhesive properties. Therefore, all the results can provide useful insights to fabricate self-powered energy storage devices to apply on electric vehicles which require high adhesion strength, stability, and high energy density.

    

Electrospun polyampholyte nanofibers with different hydrophobic and ionic chain densities

We have successfully electrospun highly-tunable neutral, positively charged, and negatively charged polyampholyte copolymers into fibrous membranes, with an emphasis on understanding the entanglement, solubility, fiber morphology, and fiber diameter characteristics of these copolymers. These polyampholyte copolymer variants contain hydrophobic, anionic, and cationic side chains of different molar concentrations that alter material properties, in part due to the differences in monomeric unit charge and chain-entanglement mechanisms. The hydrophobicity of nanofibrous mats was investigated using sessile drop water contact angle measurements, for their targeted application as filtration membranes. For producing nanofibers, a horizontal electrospinning set-up with a rotating collector plate was utilized. Using specific solvent mixtures for each copolymer variant, repeatable electrospinning methods for producing polyampholyte nanofibers were achieved. Electrospun fibers of the neutral charged copolymer have diameters ranging from 0.2 µm to 8.0 µm, with distinct morphologies under different experimental and solvent conditions, such as circular cross-section, flat, and beaded fibers. In this study, the solubilities of the polyampholyte copolymer variants were studied closely in various solvent mixtures for the purpose of creating ideal solutions for electrospinning through an evaluation of viscosity, surface tension, and perceived electrohydrodynamic behavior.   

Effect of chemical defects on enhanced piezoelectric property of poly(vinylidene fluoride) by high-power ultrasonication

Although high piezoelectric coefficients have recently been observed in poly(vinylidene fluoride-co-trifluoroethylene) [P(VDF-TrFE)] random copolymers, they have low Curie temperatures, which makes their piezoelectricity thermally unstable. It has been challenging to achieve high piezoelectric performance from the more thermally stable PVDF homopolymer. In this report, we describe how high-power ultrasonic processing was used to induce a hard-to-soft piezoelectric transition and improve the piezoelectric coefficient d₃₁ in neat PVDF. After high-power ultrasonication for 20 min, a uniaxially stretched and poled PVDF film exhibited a high d₃₁ of 50.2 ± 1.7 pm V⁻¹ at room temperature. Upon heating to 65 °C, the d₃₁ increased to a maximum value of 76.2 ± 1.2 pm V⁻¹, and the high piezoelectric performance persisted up to 110 °C. The enhanced piezoelectricity was attributed to the relaxor-like secondary crystals in the oriented amorphous fraction, broken off from the primary crystals by ultrasonication, as suggested by differential scanning calorimetry and broadband dielectric spectroscopy studies.   

Co-continuous Porous Carbon from Randomly End-linked Copolymer Network Templates

Microphase separated polymers can develop morphologies with co-continuous phase percolation, which in turn have been widely exploited to template nanostructures of other non-polymeric materials. For example, co-continuous nanoporous carbons have shown potential in supercapacitor and electrocatalytic applications. Here, we exploit the tendency of randomly end-linked copolymer networks to form disordered co-continuous phases across wide composition ranges to impart co-continuity into a porous carbon monolith. After polymerizing, via copper-catalyzed free radical chemistries, the bromide end-groups of α-ω telechelic polyacrylonitrile (PAN) and polystyrene (PS) were converted to azide moieties. Subsequent azide-alkyne ‘click’ reactions, followed by solvent removal and thermal annealing, yield a microphase separated network. Finally, thermal treatment removes the PS, while simultaneously cyclizing the PAN, and at higher temperatures, yielding graphitic carbon structures with inherent nitrogen doping. These nanoporous carbons are expected to offer promise in applications including supercapacitors and catalysts, specifically for hydrogen evolution and oxygen reduction.

    

Solute Diffusivity and Local Free Volume in Cross-Linked Polymer Network: Implication of Optimizing the Conductivity of Polymer Electrolyte

The diffusion behavior of small molecules and ions within polymer material is the key property of polymeric materials, such as polymer electrolytes, gas separation membranes, and separators, etc. Cross-linking is a common strategy to modulate solute diffusion and the mechanical properties of polymer hosts. However, the reported effects of cross-linking on the ion transport or solute diffusivity within polymer networks are divergent. Here, we utilized coarse-grained molecular dynamics simulation to investigate the effect of cross-linking density and polymer rigidity on solute diffusive behavior within polymer network. Above the glass transition temperature T_g, the diffusion of solute follows Vogel-Tammann-Fulcher equation, D=D₀exp(-E_a/R(T-T₀)). Our simulation results revealed that the pre-exponential factor D₀ and the pseudo activation energy E_a exhibit the conventional compensation correlation. Furthermore, we identified an additional correlation between E_a and Vogel temperature T₀ and an empirical relation between T₀ and cross-linking density. Integrating these newly determined correlations with the VTF equation, we derived a relation linking the solute diffusivity and the cross-linking density to identify the criteria for the optimal diffusivity. The combined results provide valuable guidance for the optimization of polymeric materials for various applications, particularly novel polymer electrolytes for energy devices.

    

Exploring and tuning the morphologies in coarse-grained polymerized ionic liquids: a molecular dynamics study

Many experimental and simulation studies over the past few decades have shown that block copolymers in bulk can self-assemble into fascinating ordered structures, such as Frank–Kasper (FK) (σ, A15, C14) and dodecagonal quasicrystalline morphologies. Recently, it has been shown that polymerized ionic liquids (PILs) can also undergo microphase separations that result in ionic conductivities over an order of magnitude higher than those in disordered PILs. However, the possible morphologies in PILs, the mechanisms of their formation, and their structural and dynamic properties are still not fully understood.

In our work, we construct and use a soft coarse-grained model with smeared electrostatic interactions to study the different morphologies and phase transitions in PILs. We observe bulk microphase separation in a pure PIL system as the oppositely charged chains become more chemically incompatible, and a spontaneous surface charge separation when metallic electrodes are added, a phenomenon previously reported in coarse-grained monomeric ILs. We show how the ordered structures change as the PIL is mixed with salt or monomeric ILs, as asymmetry is introduced between the polycations and polyanions, and when a potential difference is applied. Furthermore, we examine the ion transport properties in these materials. Our findings may aid the development of PILs for use in energy storage applications and nanostructured functional materials.

    

Mechanisms of Ion Transport in Lithium Salt-doped Block Copolymeric Ionic Liquid Electrolytes

We used multiscale simulations to study the mechanisms of ion transport in salt-doped block copolymeric ionic liquid electrolyte and compared with the homo polyIL and monomeric IL counterparts. Consistent with the experimental observations, our simulations indicate that lithium transference number is negative throughout the investigated lithium concentrations when using the polymer center of mass as the reference frame. Further, the mobility of all mobile ions decreases with increase in lithium salt concentration, regardless of the system. In contrast, the lithium transference number in block copolymeric IL and polyIL exhibits completely different trend in comparison with the monomeric system. Further, the Nernst-Einstein conductivities and the true conductivities, which were obtained through non-equilibrium simulations, are presented and compared. We rationalize the observations by presentation of the radial distribution functions, the ion pair associations, hopping frequency analyses. Together, our results demonstrate that the (co-)polymeric ionic liquid electrolytes exhibit different ion transport mechanisms in comparison with the monomeric ionic liquid electrolytes, and the reference frame should be chosen with caution when evaluating the lithium transference number.

    

A Rheological Study of Ion-Conducting Ceramic-Polymer Composites as Hybrid Solid-State Electrolytes

As the search for the next generation of Lithium-ion batteries continues, solid state electrolytes, especially those based on highly ion-conductive inorganic oxides and polymers, have garnered considerable attention. Lithium lanthanum zirconium oxide (LLZO) and polyethylene oxide (PEO) have been under particular scrutiny. Hybrid electrolytes composed of ceramic and polymer materials have complementary strengths and weaknesses: LLZO is highly ion-conductive, but mechanically brittle, while PEG is less conductive, but mechanically flexible for easy processing. Yet they are intrinsically incompatible, which leads to poor interfacial contact and ion transport. In this work, we investigate the effect of an interfacial copolymer layer based on polydopamine (PDA) to enhance the LLZO-PEO interaction. Specifically, we hae synthesized PDA-co-PEO polymers of varied molecular weight and characterize the structure and property relationship of LLZO-PDA-PEO composites. To optimize the processibility of casting such hybrid composite films, we have examined their viscoelastic characteristics of composite slurries against varied PDA-PEO molecular weight. Also as increasing the concentration of added PDA-PEO copolymer, a transition from critical gel to viscoelastic solid is observed. We further correlate their viscoelastic properties with measured electrochemical properties of cast composite films to determine optimal additive conditions for LLZO-PEO solid electrolytes for lithium ion battery applications.   

Nanoscale Velcro-like Effect: Synthesis and Rheological Properties of Polymer Loop-Grafted Nanoparticles

Grafted chain architectures are used to control the interfacial chain entanglements and reinforcement in polymer nanocomposites. This study aims to create complex grafted chain topologies to alter free matrix chain relaxations and viscoelastic properties. Polymer loop-grafted particles were synthesized, and rheological behavior of their composites were explored. First, linear poly(methyl methacrylate) chains were grafted on 15 nm SiO₂ nanoparticles by RAFT polymerization. After chain end modification with thiol group, loops between PMMA grafts were achieved by thiol-ene click reaction. Molecular weights of connected chains were determined using gel permeation chromatography after etching the nanoparticles. The dispersion of loop grafted chain nanoparticles was then examined in transmission electron microscopy. The linear viscoelasticity of polymer loop-grafted nanoparticle composites and their comparison to that of bare and linear polymer-grafted composites at same particle loading will be discussed.

    

Crystallization and phase separation of poly(caprolactone) and poly(ethylene oxide) side chain bearing bottlebrushes

     Molecular bottlebrush copolymers have potential applications in the biomedical field due to their unique molecular architecture. Bottlebrush copolymers have been shown to self-assemble into spherical crystalsomes owing to the restriction of the backbone during single crystal growth. In this work, we seek to build on this work by characterizing the crystallization behavior of molecular bottlebrushes with crystalline mixed side chains. A series of mixed side chain molecular bottlebrush was formed using a copper catalyzed grafting-to azide-alkyne cycloaddition click reaction. N₃ functionalized poly(hydroxyethylmethacrylate) was used as backbone, and alkyne-terminated poly(ethylene oxide) and poly(caprolactone) were grafted as side chains (PHEMA-g-PEO_xPCL_y). Differential Scanning Calorimetry (DSC) experiments were performed to investigate the bulk crystallization. Molecular bottlebrush crystalsomes were grown through a solution crystallization process and characterized with Scanning Electron Microscopy (SEM). A systematic study of crystallization behavior through DSC shows a range of crystallization behaviors with a dependence on side chain loading. Peak crystallization temperatures and integrated heat of crystallization were generally decreased with mixed grafting, indicating hindered crystal growth. SEM morphology analysis shows that mixed loading introduces phase separation and influences the shape of the crystalsomes.

    

Self-Assembly of Molecular Weight-Controlled Bottlebrush Block Copolymer within Evaporative Emulsion

Bottlebrush block copolymers(BBCPs) are powerful candidates in confined assembly because of the distinct chain architecture with densely grafted side chains. Here, we report the self-assembly behavior of BBCPs within three dimensional confinements where each block consisted of polystyrene (PS) and polylactide (PLA). The molecular weight was found to be critical parameter for determining the final particle morphology and the chain conformation at the emulsion interface. Morphological transition of the particles from onion to ellipsoid was observed when the molecular weight of BBCP increases. This is rationalized by the competition between the particle surface/surroundings interactions and the chain stretching/bending penalty of the BBCPs, both for the experiments and simulations. While investigating the morphological evolution of BBCP particles, BBCP ellipsoids particularly exhibited interesting features that were not observed in the linear BCP particles. The lamella rings were formed at the particle surface with slow axial propagation to the entire particle surface, which was followed by radial propagation of the BBCP ordering to the particle center. In addition, the shape of BBCP ellipsoids were controlled as a function of particle size.   

Controlling Polymer Structure with Precise Sequence Design

Optimal polymer design is challenging due to the vastness of polymeric chemical and structural possibilities. This work provides atomic-level insight to establish simple design rules to control polymer structure through precise sequencing. We use sequence-specific polypeptoids, whose structural effects can be studied with experimental and simulation techniques to explore how monomer sequences can impact polymer folding and assembly. Specifically, two model systems are studied to examine changes in the local and global structure of the polypeptoid chains. To explore these effects, we simulate polypeptoid chains in solution to understand how the number and location of the hydrophobic and chiral monomers lead to changes in their structural ensemble. The number and position of chiral centers alters local peptoid helical formation. Furthermore, global polymer structure is controlled by leveraging the role of hydrophobicity. These computational methods will provide a molecular insight into the driving forces for polymer conformation and guide the development of new materials with tunable properties.   

Computer simulations of melts of ring polymers with non-conserved topology: A dynamic Monte Carlo lattice model

We develop a kinetic Monte Carlo scheme for polymer chains on the 3d FCC lattice which takes into account the possibility for pairs of polymer strands to perform strand crossing at a given tunable rate. We apply this method to melts of ring polymers and we characterize their structure and dynamics. We focus on the complex topology arising during the relaxation process by looking, in particular, at the formation of knots, links and higher order topological structures. As for the dynamics, we show that strand crossing makes polymers to diffuse faster with respect to melts of unknotted and non-concatenated rings provided that the time-scale of the process is smaller respect to the relaxation time of the unperturbed state, in agreement with recent experiments employing solutions of DNA rings in the presence of the type II topoisomerase enzyme. In contrast, at slow rates the melt is shown to become slower, and this prediction may be easily validated experimentally.   

Monitoring the Kinetic stability of vapor-deposited glasses using in-situ solvent vapor annealing.

Stable glasses (SGs), prepared by physical vapor deposition have been shown to have improved density and thermal stability analogous to highly aged liquid quenched glasses. Numerous studies have investigated their thermodynamic stability via measurements of density, enthalpy, and fictive temperature. However, the kinetic stability of SG films is difficult to evaluate, as the SG transformation mechanism upon heating above the glass temperature can depend on film thickness and the transformation temperature. Here, we employ an indirect method of measuring the kinetic stability of SG films using in situ solvent vapor annealing (SVA) combined with in situ spectroscopic ellipsometry. Under proper solvent vapor pressure, a moving solvent front is observed that starts from the free surface towards the center of the film, analogous to the thermal annealing front. Using this technique we study the kinetic stability of films of various molecules, deposited across a range of temperatures and thicknesses, through measurements of the solvent front velocity. In contrast to thermal annealing fronts, SVA can be applied to both liquid quenched and SGs with a broad range of stability, providing a direct comparison in these systems.   

Curing Kinetics of Methacrylate and Dual-Cure Interpenetrating Polymer Network (IPN) Resins for UV-Curable Additive Manufacturing via In-Situ Raman Spectroscopy

Curing kinetics of photopolymerizable resins are important for determining the printing parameters for resin-based additive manufacturing. Most traditional methods of analyzing the chemical and structural dynamics, such as photo-differential scanning calorimetry or infrared spectroscopy, can be difficult to perform in situ, but Raman spectroscopy is ideally suited for such studies. Here, we used non-contact Raman spectroscopy to better understand the curing kinetics of fully methacrylate resins, dual-cure interpenetrating epoxy-methacrylate polymer networks (IPNs), and chemically connected IPNs. We also investigated resins amendable for UV-assisted direct ink write printing to elucidate the effects of rheological modifiers. Peaks at 1640 cm^-1 and 915 cm^-1 were monitored to track methacrylate and epoxy conversion, respectively, and the disorder band around 15 cm^-1 and torsional band around 85 cm^-1 were monitored to determine the “structural kinetics” of the polymers, independent of chemical functionality. These results were fitted to a model to experimentally determine the kinetic rate constant, order, and ultimate conversion, all critical parameters for optimizing additive manufacturing processes.

    

Centrifugally-Spun Fibers

Continuous spun fibers provide an ideal material for various applications, ranging from fibrous membranes and fiber mats to structural scaffolding for tissue engineering. To target specific properties and morphology of centrifugally-spun polymer fibers, a long list of parameters, such as polymer entanglements, extensional relaxation time, surface tension, and evaporation time must be accounted for. This work compares previously studied methods that predict the formation of continuous fibers. We consolidate these parameters and propose additional considerations to provide a more robust processability map for fiber formation prediction via torsional rheometry, Dripping-onto-Substrate (DoS) protocols, and thermogravimetric analysis (TGA).   

Impact of polymer molecular weight on droplet coalescence and the properties of parts printed via powder bed fusion

Understanding and controlling the fundamental processes governing sintering is vital to achieving robust structures by laser powder bed fusion (LPBF) process. In this presentation, we will highlight our studies to understand the role of polymer molecular weight (M_w), and thus zero-shear viscosity, on particle coalescence and the powder bed fusion process. Our group has used thermally induced phase separation (TIPS) to form polypropylene (PP) powders from PP with M_W of 12k, 250k, and 340k, and their 50/50 blends (12k/250k,12k/340k, and 250k/340k). The coalescence behavior of the powders was studied, where the Hopper model provides insight into the molecular-level processes that control the consolidation of particles during sintering. Additionally, analysis of printed parts from these powders shows that the bimodal samples exhibit lower void space, higher crystallinity, and more robust mechanical property than the unimodal counterparts. These results provide molecular-level insight into how control of powder M_w can impact the LPBF process and offer pathways to optimize the macroscopic properties of the printed parts.

    

Mechanical Properties of Ultrathin Liquid Crystalline Polymer Films fabricated by Chemical Vapor Deposition

Liquid crystalline polymer (LCP) coatings are attractive materials for creating smart surfaces, which offer responsive topography, reflectivity, and polarization properties. However, conventional fabrication methods for LCPs are difficult to use to achieve coatings with sub-micron thickness. We utilize initiated chemical vapor deposition (iCVD) to fabricate ultrathin LCP films. The iCVD technique is solvent-free and can be used with a massive monomer library to fabricate a large range of LCP architectures. Here, we demonstrate how the surface energy of the substrate controls the surface alignment of LCP-iCVD films, and we quantify their mechanical properties to provide new insight into the properties of LCP as a function of film thickness.   

Molecular weight distribution effects on flow induced crystallization of model polymer.

Flow induced crystallization is a process with significant industrial interest in the field of polymer processing and applications such as packaging. Despite the significant practical relevance, the initial stages of the flow induced crystallization remain unclear, and it is difficult to elucidate the nature of nucleation. We perform Molecular Dynamics simulations to understand the role of chain length distribution, temperature, and flow in crystallization. Our study focuses on the role of shear flow in the orientation and stretching of model polymer melts with a distribution of chain lengths. We simulate the model polymer melt under different processing conditions by using a soft interaction potential and generate shear by using SLLOD boundary conditions. We quantify the extent of crystallization using appropriate order parameters, and gain insights in the rate of crystallization and the morphology of polydisperse semi-crystalline melts, including the structure of the precursor at the onset of crystallization.

    

Evaporation Induced Crystallization of Poly (L-lactide acid) on Water Surface

Polymer self-assembly and crystallization on water surfaces have been extensively investigated to understand polymer chain conformation on water surfaces and to fabricate free-standing polymer thin films. The Langmuir–Blodgett (LB) approach is often used in this research field as it provides a well-controlled water/air interface. In this study, we introduce an evaporation crystallization process to investigate polymer crystallization on water surfaces. Poly (L-lactic acid) (PLLA) was used as the model polymer and PLLA crystals were obtained by controlling solvent evaporation on the water surface. The crystal structure and morphology were investigated using transmission electron microscopy and atomic force microscopy. We show that water surface plays a critical role in determining PLLA chain conformation, which in turn, leads to different crystal morphologies including one-dimensional ribbons and two-dimensional plates. The evaporative crystallization technique, therefore, provides a unique opportunity to tune polymer crystallization pathways.   

Role of Chain Entanglements in the Stereocomplex Crystallization between Poly(lactic acid) Enantiomers

Stereocomplex (SC) crystallization between polymer enantiomers has opened a promising avenue for preparing high-performance materials. However, high-crystallinity SCs are difficult to achieve for high-molecular-weight (HMW) enantiomeric blends of chiral polymers [e.g., poly(lactic acid)]. Despite extensive studies, why HMW enantiomeric blends have difficulty in SC crystallization has not been clarified. Herein, we chose the HMW poly(l-lactic acid)/poly(d-lactic acid) (PLLA/PDLA) 1/1 blend as the model system and demonstrated the crucial role of chain entanglement in regulating SC crystallization. PLLA/PDLA blends with various entanglement degrees were prepared by freeze-drying. We observed that disentangling promoted not only the crystallization rate but also the crystallinity of SCs in both the nonisothermal and isothermal processes. The less-entangled samples crystallized exclusively as the high-crystallinity SCs at different temperatures, in contrast to the predominant homocrystallization that occurred in the common entangled samples. This study provides deep insight into the SC crystallization mechanism of polymers and paves the way for future research attempting to prepare SC materials.   

Fluorophore Self-Assembly in Liquid Crystals

Liquid crystals (LCs) are a state of matter, characterized by an order called the nematic phase. While past work has investigated how 5CB LC drop configuration transforms under an electric field, 5CB behavior in magnetic (B) fields is yet to be studied. This project uses the fluorophore BODIPY-C5 to visualize the transition of radial 5CB drops in response to B fields. With zero B field, radial drops with 5CB molecules arrange from the center to the edges. As the B field increases, the 5CB molecules rearrange to be aligned with the direction of the field. Similarly, drop defects (regions in which 5CB molecules do not have uniform direction) change configuration, starting as a point defect in the zero B field configuration and converts to a ring defect with an increasing B field. Fluorophores are added to topological defects formed by planar rubbing of PVA-coated substrates to stretch polymers and induce 5CB alignment. Fluorescence microscopy is used to take images of drops and quantify the intensity distribution. Preliminary results show that at zero B field, the intensity is lowest at the center of the radial drops containing the point defect. Future work will use confocal microscopy to analyze layers of drops and quantify intensity change over an increasing B field.   

Ultra Thin Liquid Crystal Elastomer Fiber Actuator With Liquid Metal Core

Liquid Crystal Elastomer (LCE) can be used as actuators in soft robotics. However, due to low thermal conductivity of this material, bulk LCE does not react to temperature change very

quickly, thus the actuaion period is long and it is not ideal for typical soft robotic applications. In this work I present a method to directly spin thin LCE fiber with Liquid Metal (LM) Core, which allows the LCE to heat up and cool down very fast. Thus achieving ideal actuation speed.   

Monodisperse rod formation and liquid crystal behavior of computationally designed parallel peptide coiled-coil ‘bundlemers’

Computationally designed peptides 30 amino acids in length can assemble into the homotetrameric, parallel coiled coils in the aqueous solution, which are also called ‘bundlemers’. The peptide sequences have multiple amino acid side-chain modification positions on the bundlmer exterior as well as the n- and c-termini. Different ‘click’ chemistry functional pairs are used to modify the N-termini to provide potential covalent linking points for the formation of multibundlemer chains. Parallel coiled-coil bundlemers offer the unique possibility for monodisperse, rigid, dimer bundlemer chains when linked together in an end-to-end fashion. Transmission electron microscopy reveals the well-dispersed short rod like structures while small-angle x-ray scattering indicates the monodisperse nature of the rod chain length and diameter. Optical birefringence should be observed in concentrated rod solution under the polarized optical microscopy (POM). With additional C-terminal modification, one can also create ultralong polymers of the parallel bundles. Different inter-bundlemer linking strategies will be discussed to produce different monodisperse lengths of rod-like chains as well as liquid crystals.

    

Effects of Small Molecule Additives on Liquid Crystal Elastomer Network Phase Behavior

Due to their actuation and soft elastic properties, liquid crystal elastomers (LCEs) hold promise for a wide variety of applications, ranging from electrocalorics to artificial muscles. To tune these properties, a comprehensive understanding of the relationship between LCEs' properties and their network structure is required. While theoretical models have been developed to explain LCE behavior, as-synthesized LCE networks are affected by the inevitable presence of small molecule additives; little work has been done to explicitly understand their impact. Notably, crosslinkers can lead to two opposing effects to the LCE network: an increase in the crosslinker concentration increases the crosslinking density, however the crosslinker can also act as a defect in the LCE system prior to crosslinking. Here, by probing the thermal and mechanical properties of LCEs utilizing complimentary techniques, we quantify the effects of crosslinking molecules as a function of concentration and functionality both prior to and following crosslinking. Through this study, we highlight factors and additives that perturb LCE phase behavior, allowing for a more controlled design of LCE networks.   

Molecular dynamics of poly(propylene oxide-co-glycidyl methyl ether) (GME): Unraveling the effect of composition and molecular weight on segmental and chain dynamics

In this study, the segmental and normal mode dynamics of polar aliphatic polyethers based on the copolymerization of propylene oxide (PO) and glycidyl methyl ether (GME) were investigated using dielectric spectroscopy for a wide range of molecular weights and monomers compositions. Polar interaction of glycidyl methyl ether results in increasing glass transition temperature (T_g) and slowing down the segmental dynamics. However, the fragility of the copolymers is identical to the neat poly (propylene oxide) which implies that the influence of the backbone structure is dominant rather than the molecular cohesive energy factor on the fragility. In addition, the temperature dependence of the normal mode is weaker than segmental dynamics which resulted in the decoupling of segmental and normal mode dynamics. The effect of molecular weight on the decoupling is prominent in comparison to the copolymer composition. From the relaxation strength of the normal mode and segmental mode, the parallel and perpendicular components of the dipole moment were calculated. The effect of glycidyl methyl ether (GME) composition on the dielectric strength is significant due to the higher dipole moment of GME. The results of the current work shed light on the effect of cohesive energy density and molecular weight on the segmental and chain dynamics of polymers.

    

Using a fluorescent molecular rotor probe enables accurate determination of glass transition temperatures in polymers: Experiment and atomistic simulation

In this presentation, we show that a fluorescent molecular rotor consisting of a julolidine headgroup and a farnesyl tail, farnesyl-(2-carboxy-2-cyanovinyl)-julolidine (FCVJ), can be used as a probe for experimental determination of T_g for bulk and nanoconfined polymers. Experiments show that FCVJ has a higher sensitivity to changes in free volume and is thus able to detect the glass transition more reliably than other types of molecular rotors previously studied. Atomistic MD simulations show that the difference in conformational flexibility between FCVJ’s head and tail groups produces anomalous kinetic energy distributions between these groups below T_g. The T_g values determined for a low-molecular weight polystyrene by experiment and simulation, both using FCVJ as a probe for detection of glass transition, agreed with each other and also with the value obtained by DSC. These results also establish that the T_g of a polymer can be accurately determined by atomistic MD simulation—by tracing the motions of the probe molecule’s head and tail groups (rather than tracing the motions of polymer segments themselves), which enables to circumvent the well-documented dilemma of T_g overestimation that occurs due to a fast cooling rate employed in atomistic MD simulation.   

Leveraging Modern Computational Tools to Identify the Glass Transition From Noisy Data on Thin Polymer Films

Measurements of the glass transition frequently yield data where the transition manifests as a continuous change in slope from a linear liquid region to glassy region, with Tg often taken as the intersection of two linear fits or from a nonlinear fit to an equivalent functional form. Temperature-dependent film thickness data from ellipsometry is an example. The challenge arises for very thin films where the data are inherently noisier, and interfacial gradients cause significant broadening of the transition. Leveraging state-of-the-art computational tools, we address various inherent drawbacks of the methods commonly used. We compare the use of a Bayesian inference method to rapidly search combined subsets of parameter space relative to a standard nonlinear least squares fit. The Bayesian inference method we developed uses the open-source library PyMC as its backend to rapidly search the parameter space for the values that minimize the error of the model, allowing for efficient fitting while reducing ambiguity in the determination of Tg. We also test a least trimmed squares regression that was designed to isolate linear trends from noisy data, as well as simply a brute-force iterative search of all possible Tg values.   

Polyolefin upcycling via shear-induced chain scission in particle composites

Upcycling processes that use chemo-catalytic methods to convert waste plastic into useful products are often limited by the mobility of macromolecules in catalytic nanopores. The inability of chains to access interior spaces of a porous catalyst limits high conversion, makes the scale-up of bench-top reactions difficult, and dictates the use of energy-intensive routes to process the polymer-catalyst mixture. We propose that shear-induced scission of particle-filled polymer melts can be used as an effective strategy to design energy-efficient catalytic conversion processes. In this poster, we will present results demonstrating the design of polymer-particle composite system that undergo shear-induced chain scission arising out of a combination of high shear rates and retarded polymer dynamics in composites. We study the impact of different shear histories and flow types on the amount and rate of scission of polyolefin chains in a composite melt with silica particles as fillers. The effect of varying particle attributes viz. particle surface chemistry, particle size, particle loading, and particle morphology on the scission reactions will be presented in this poster. Particle-polymer interactions influence adsorption kinetics and dictate the amount and conformations of adsorbed chains. Longer chains will form loops that entangle with surrounding chains as well as bridges between multiple particles - all conformations that will result in slower dynamics and higher possibilities of scission. Thus, our results on chain scission in polymer composites will guide the development of better upcycling processes to transform plastic wastes into value-added commodities.

    

Utilizing Recycled Polyurethane Products for Fabricating Composites with High Sound Attenuation and Thermal Insulation Performance

Polyols, obtained by chemolysis of polyurethane (glycolysis, acidolysis, hydrolysis), are typically recycled to only partially replace virgin polyols in polyurethane foam production. This is due to their high -OH values (higher reactivity) and a lack of control over their chemistry. In our work, we utilize polyols obtained by glycolysis of industrial scrap foam, to fabricate strong, robust and lightweight organic/inorganic composites suitable for soundproofing and thermal insulation. In this poster, we will discuss the correlation between the chemical composition (nature of polyol, organic and inorganic contents) and the material (density, microstructure, and mechanical properties) and functional (sound absorption and thermal conductivity) properties of these organic/inorganic composites. The recycled organic/inorganic composites, consisting of recycled polyols, naturally occurring aluminosilicate minerals, and organic linkers will be shown to exhibit enhanced sound attenuation and thermal insulation behavior as compared to conventionally employed materials (e.g., ordinary Portland cement, gypsum). Finally, the performance of these recycled composites will be compared with virgin composites comprising polyols with similar reactivities.

    

pyDSM: Fast Quantitative Rheology Predictions for Entangled Polymers in Python

It has been extensively shown that the discrete slip-link model (DSM) accurately predicts the linear and nonlinear rheology of various entangled polymer systems. The only publicly available implementation of the DSM algorithm is written in the CUDA C++ programming language for GPU computing. In this work we discuss the implementation of the fixed slip-link model and the clustered fixed slip-link model in Python. Our work shows that Python can also utilize GPUs to enable fast quantitative rheological predictions. Our simulation code, named pyDSM, allows an easy-to-read and beginner-friendly approach for users wanting to utilize the efficiency of GPU computing while also enabling an open-source Python package that can easily couple or interact with other simulation or data analysis software. We demonstrate pyDSM's versatility by implementing a recently published algorithm that allows estimation of the statistical uncertainty in the autocorrelations for any time series data, accounting properly for the correlation in the data. Here the method is used to calculate the uncertainty in the relaxation modulus and the chain center-of-mass mean squared displacement. Moreover, the uncertainty quantification in the relaxation modulus allows propagation of error through a multi-mode Maxwell fit to determine the uncertainty in the dynamic modulus. Lastly, we include benchmarks and discuss capabilities and limitations of the publicly-available pyDSM package.   

Quantifying non-linear effects in high-rate elastic recoil

A quantitative understanding of the mechanical properties of materials unloading at high rates and large deformations is important for the design of elastic mechanisms to drive ultra-fast movements. Recoil testing is a direct way to measure unloading performance, where high speed videography is used to track the displacement field of a freely retracting material. However, current approaches to recoil testing do not consider non-linear viscoelastic properties of materials during retraction from large deformations. In our work, we combine experimental recoil measurements with viscoelastic wave propagation simulations. As a first step, we find agreement between our experiment and simulation for key metrics of kinematic performance such as maximum power output during retraction as initial strain in the material is increased.   

United Atom and Coarse Grain Force Fields for Crosslinked Polydimethylsiloxane with Applications to the Rheology of Silicone Oils

Chemical crosslinking plays a determining role in the mechanical properties of silicone materials comprised of polydimethylsiloxane (PDMS). Classical molecular dynamics (MD) is an invaluable tool to explore, understand, and optimize materials performance, but requires accurate force fields (FFs). We develop a hierarchical pair of FFs for crosslinked PDMS. We first extend an existing united-atom FF to include crosslinking terms and then use it together with iterative Boltzmann inversion to train a coarse grain FF where each monomer is represented by a single particle. MD simulations with both FFs show that crosslinking alters the rheology of silicone oils, leading to systematic increases in density and shear viscosity. The viscosity of crosslinked oils follows an empirical linear trend with number-average molar mass. The FFs developed here serve as a bridge to upscale insights on siloxane chemistry to enable quantitative bottom-up predictions for curing- and age-induced effects.   

Temperature dependent diffusion in block copolymer organogels

Organogels made with styrenic block copolymers are recently being studied for their potential use in transdermal drug delivery which requires an extensive investigation of diffusion behavior through these gels. To completely characterize diffusion of solutes through these gels, examining temperature dependence of diffusion is crucial along with other factors including gel concentration, polymer molecular weight, and nanostructure. In this work, the temperature dependent transport of a solute, namely sodium bis(2-ethyl-1-hexyl) sulfosuccinate (AOT) reverse micelles, is determined for several unique gels. These gels consist of the same organic solvent (Hydrobrite 200) and one of three different styrenic triblock copolymers ( triblock1: 158 kg/mol and ƒS = 0.278; triblock2: 248 kg/mole, ƒS = 0.297; triblock3: 421 kg/mol, fS = 0.291) at concentrations in the range of 6 to 14%. Diffusivity values for AOT reverse micelles are determined over a temperature range of 20 to 50°C. To confirm the validity of this somewhat narrow experimental temperature range, temperature dependent transport of triblock1 copolymer organogels varying in solvent viscosity (29, 80, 153 cP at 25°C) is also analyzed. Results from these experiments will be compared with theoretical models of temperature dependent solute diffusion.   

Mechanical Properties of Poly-L-Lysine Hydrogels Across the Helix-Coil Transition

Poly-L-lysine (PLL) is a biological polyelectrolyte that undergoes structural changes in

response to environmental shifts such as pH. Here, we take advantage of PLL’s structural changes

across the helix-coil transition as a function of pH to develop new functional materials. PLL is

crosslinked with poly (ethylene glycol) diglycidyl ether (EDGE) at crosslink densities, ranging from 3-

6%, and the bulk mechanics of the gel are studied across the coil-helix transition. Dynamic and Dynamic

Small Angle Light Scattering are used to determine the diffusion coefficients of the gel and rheometry is

used to determine shear modulus and strain behavior of the gel as a function of crosslink density, salt,

and pH. Circular Dichroism is used to characterize the helical structure of the PLL in gel. Analyzing the

results of these methods, meshsize is calculated as a function of modulus and volume fraction and

compared to changes in crosslinker % and pH of solution. We find that shear modulus increases as a

function of % crosslinker and mesh size decreases as a function of pH and % crosslinker. By

understanding the hydrogels’ structure and response to environmental changes, we can expand their

potential as functional materials in biomedical applications or soft actuators.   

Network Forensics of Linear Chain Networks

We use a forensic-like approach to analyze results of coarse-grained molecular dynamics simulations of nonlinear deformations of networks made by crosslinking linear chains in a melt. In particular, we have obtained the Kuhn length and degrees of polymerization of the network strands between crosslinks as well as the cumulative contribution of the network defects into the network structural modulus. For networks with trapped entanglements, we identified a transition from crosslink- to entanglement-controlled network elasticity with increasing degree of polymerization of network strands between crosslinks and correlate this transition with changes of entanglement and structural shear moduli describing different modes of network deformation.

    

On the Structure of Reversible Networks made of Star Polymers

We develop a theoretical approximation for the structure of reversible networks made of star

polymers based upon a set of suitable balance equations. These allow to predict the partitioning of

the connectivity types of star polymers including the formation of the most abundant small cyclic

structures in the system. Our model is developed using three different kinds of computer simulations.

First, mean-field Monte-Carlo simulations are designed to check the basic equations on the treatment

of the most relevant intramolecular reactions. Simulations with the bond-fluctuation method (BFM)

to model diffusion and collision of reactive groups in space to form bonds. Here, we focus on linear

polymerization to explore the differences to mean field, since there, the impact of loops can be

computed exactly. In a third step, the BFM is used to produce realistic network structures that are

compared with the basic equations that were modified with respect to the corrections to mean field.

Finally, our findings are discussed in the light of preceding work in literature.   

Deformation Driven Deswelling of Brush Gels

We studied the effect of nonlinear strand deformation on the swelling of brush networks using Flory-Rehner and scaling models of gels. The model predictions are tested by coarse-grained molecular dynamics simulations of brush gels undergoing large uniaxial elongation. Our analysis showed that the swelling ratio of the brush gels Q_eq(λ) is a nonmonotonic function of the deformation ratio λ. It first increases with increasing gel deformation and then begins to decrease. This behavior is a manifestation of the optimization of the polymer/solvent interactions and conformational entropy of brush strands in the nonlinear deformation regime. The location of the maximum of Q_eq(λ) is directly related to the strand molecular architecture shifting to smaller λ values with increasing brush grafting density and degree of polymerization of the side chains. Analysis of the gel stress-deformation curves points out that the network firmness parameter β is identical in both dry networks and gels. However, the structural modulus of gels, G_s, appears to be reduced in comparison with that in the dry state by a factor equal to the ratio of the Kuhn lengths of brush strands in the dry and swollen states, G_s = G_dr b_K/b_K,s.

    

Molecular scale diffusion of water in cross-linked poly(ethylene glycol) diacrylate

The separation performance of polymer-based water purification membranes is thought to be governed by both molecular and macroscopic water properties near polymer surfaces. However, the role of molecular-level interactions between water and membrane interfaces on macroscopic transport remains unclear. Using aqueous poly(ethylene glycol) (PEG) solution, a common membrane component, we find that the diffusion of water at multiple length scales is mediated by molecular scale water structuring around the polymer chain. A fractional free volume diffusion model accounts implicitly for water-polymer interactions to describe water diffusion in aqueous PEG solution. Furthermore, the impact of polymer interfaces on water dynamics is unknown for cross-linked polymer networks. We measure nanometer scale water diffusivity using Overhauser Dynamic Nuclear Polarization on cross-linked PEG diacrylate to investigate whether the same water structuring drives water diffusion in the cross-linked environment. We determine the effect of water volume fraction in swollen hydrogels on local water diffusion. This study shows how molecular scale interfacial water dynamics impact macroscopic transport relevant to the design of structurally complex polymer membranes.   

Computational Study of Li+ Transport in Mixed Solid Polymer Electrolytes Containing Microscopic Interfaces

For practical application, solid polymer electrolytes (SPE) are often required to achieve high conductivity, high transference number, and high mechanical strength simultaneously. Many SPE designs therefore mix different chemical species to introduce the added functionalities beyond Li⁺ conduction. Varying degrees of mixing of the added components into conducting components tends to alter the dynamics of the polymer host and the solvation environment for Li⁺. This poster features computational studies that attempt to understand and quantify the effect of mixing. One study considers Li⁺ transport in mixtures of the poly (ethylene oxide) (PEO) and poly (methyl methacrylate) (PMMA) couple, where effects of miscibility on Li⁺ transport can be examined in isolation. A graph-based transport model is proposed to effectively quantify long-range transport of Li⁺ in the mixtures. The second study considers mixed graft copolymer electrolytes containing a polarity contrast, using poly(glycerol carbonate methacrylate) (PGCMA) and poly (oligoethylene methacrylate) (POEM) as building blocks. Simulations reveal how entropy governs the solvation site formation and Li⁺ transport in those mixed-polarity SPEs containing microscopic interfaces of varying sharpness. The study also concludes that the synergy of polarity and mobility contrast for conductivity observed in liquid electrolytes is  not transferable to polymeric systems, due to fundamentally different Li⁺ solvation and transport mechanisms.

    

Compatibilization of immiscible polymer blends through ionic interactions

Polymer blending provides an attractive and sustainable platform to obtain materials with desirable physicochemical properties, but often results in immiscible blends exhibiting poor mechanical and optical properties that limits applicability. To address this challenge, we demonstrate that ionic interactions are a powerful tool for polymer compatibilization, recycling, and upcycling. In this work, ionic bonds efficiently compatibilized a highly immiscible blend of poly(n-butyl acrylate) P(nBA) and poly(dimethylsiloxane) (PDMS). At 10 mol% or less incorporation, pendant acidic moieties were introduced in P(nBA) through reversible addition–fragmentation chain-transfer copolymerization, and pendant basic moieties were tethered along the PDMS backbone through a facile thiol-ene reaction. Stoichiometric acid-base polymer blends exhibited optical clarity and single glass transition temperatures. In addition, oscillatory shear rheology is utilized to probe the blend dynamics as a function of temperature. The combined synthetic and characterization strategy is opening significant opportunities for understanding and exploiting low levels of ionic functionalization in commercially important polymeric systems.

    

Equilibrium studies on oppositely charged polyelectrolytes

Polyelectrolytes are well known to be strongly correlated even in extremely dilute solutions. At high concentrations especially, proper accountability of ionic specificity in terms of ion size and dielectric environment is essential. We present how such ionic specificities affect the equilibrium thermodynamics of various electrolytes/polyelectrolytes systems. By accounting for the ionization equilibrium between the oppositely charged groups, an approximate analytical formula for the intra-chain pair potential can be derived in terms of the charge and size of the chain. In the case of oppositely charged polyelectrolytes, the inter-chain pair potential can also be derived self-consistently by incorporating all monomer and counterion degrees of freedom.   

Variations in thermal stability and hydrophilicity of multiple polyampholyte membranes with unique structural compositions

Polyampholytes are polymers that have randomly distributed sequences of both positively and negatively charged monomeric units. Polyampholytes show excellent anti-fouling properties because of the oppositely charged components along their chains. Therefore, they are ideal candidates for the fabrication of filtration membranes. In this study, we used a random polyampholyte amphiphilic copolymer (r-PAC) that is composed of monomer units that are hydrophobic in addition to the positively and negatively charged components in various compositions. The r-PAC membranes were prepared by doctor blading, and thin films were prepared by spin casting. The doctor-bladed membranes were characterized using thermogravimetric analysis (TGA) and Fourier-transform infrared spectroscopy (FTIR). Sessile drop contact angle measurements were performed on spin-cast thin films. TGA showed that r-PACs degrade via a multistep process and FTIR confirmed that the cationic group degrades first. Sessile drop contact angle measurements showed that as the negatively charged components increased, the surface of the material became more hydrophobic. With increased hydrophobicity, these materials possess excellent mechanical and chemical stability while the hydrophilicity of the charged components preserves their anti-fouling properties.   

Behavior of Sulfonated Polystyrene in Dilute Solutions

The current study explores the behavior of sulfonated polystyrene in dilute solutions. Ionizable polymers are often cast from solutions because of their high Tg induced by clustering of the ionic groups. Solution structure however often determines the structure of the polymer films and their properties. Here using molecular dynamics simulations, we probed the conformation of single polystyrene sulfonate at different sulfonation fractions. Sulfonation was varied from 0 to 95% across the transition from ionomer to poly electrolytes. Measurements were carried out in water (ε = 78), THF (ε = 7.5), toluene (ε = 2.8), and cyclohexane (ε = 2.0). The radius of gyration, the static structure factor of the polymer, and counterion condensation were calculated. In high dielectric solvents such as waster, we observe a decrease of counterion and a faster rate of chain collapse than in the lower dielectric solvents such as toluene. In all solvents, the chain's structure is also affected by the sulfonation fraction, where we observe that low sulfonation are slower to collapse fully, if at all.   

Poly(ethylene oxide) electrolytes with tailored nitrile end-groups

Lithium salt-doped poly(ethylene oxide) (PEO) and PEO-derivatives have been widely investigated to develop polymer electrolytes for lithium-ion batteries. Nevertheless, low ionic conductivity, poor mechanical strength, and limited electrochemical stability of PEO electrolytes limited their practical uses in viable applications. Herein, we studied advanced PEO electrolytes by introducing tailored nitrile terminal moieties. Spectroscopic analyses and molecular dynamics simulations showed that nitrile end-groups changed Li⁺ solvation structures by forming –C≡N···Li⁺···(EO)_n interactions. This lowered coordination numbers and developed partially opened shell structures, enabling fast and selective Li⁺ relaxation dynamics. By doubling the local number density of terminal nitrile moieties, the effects of CN-driven interchain interactions increased, resulting in more than 2-fold increased lithium transference number and radically improved electrochemical stability window. To enhance mechanical strength in addition to improved electrochemical properties, nitrile-ended PEO electrolytes were blended with polystyrene-b-poly(ethylene oxide) (SEO) block copolymers. Intriguingly, even if the number density of nitrile end-groups was the same, nitrile termini at α- and ω-positions of PEO improved the blend electrolyte properties more effectively, compared to α, α-dinitrile PEO-blended counterparts.   

Morphology Control of Charged Block Copolymers through Electrostatic Control of Interfaces

In the present study, we investigated the self-assembled morphologies of charged block copolymers comprising ionic liquids. To control electrostatic interactions of polymer matrix with embedded ionic liquids, two types of acid-tethered block copolymers were prepared. Increasing the amount of embedded ionic liquids in the acid-tethered block copolymers resulted in sequential morphological transitions from gyroid-to-lamellae-to-hexagonal cylinder owing to the effective swelling of ionic domains. Interestingly, when the cation-excessive nonstoichiometric ionic liquids were employed, a radical morphological change from lamellar (stoichiometric) to A15 (non-stoichiometric) structures was observed for the acid-tethered block copolymers. This was remarkable given that such phase transitions occurred despite the calculated volume fractions of ionic domains were almost identical. By varying the non-stoichiometry of ionic liquids, it has been revealed that the use of excessive cations stabilized the A15 structures by lowering the concentration fluctuation at block copolymer interfaces via electrostatic interactions. Such stabilization became pronounced when the polymer matrix binds more strongly with the cations. Computational simulations unveiled the formation of thin ionic shell layers at the block copolymer interfaces, which played a crucial role in stabilizing the low symmetry morphology. Owing to the three-dimensionally connected ionic domains in the A15 structures, enhanced ionic conductivity was achieved for corresponding block copolymer electrolytes.   

Coarse-grained molecular dynamics simulations of interfacial structure and mixing in ionomer melts

Ionomers are polymers with modest fractions of charged groups. We perform coarse-grained molecular dynamics (MD) simulations to determine how synthetically controllable parameters (e.g., average ion spacing) impact the interfacial adhesion of these materials. Specifically, we simulate freestanding ionomer films at different ion densities and subsequently bring them into contact. We use a Kremer-Grest-based model for the ionomers that includes uncharged backbone monomers, charged pendant groups, pendant stickers representing unneutralized acid groups, and unbound counterions. Composition profiles exhibit a layering of neutral and charged groups near the vacuum interfaces that becomes more pronounced with increasing ion density. We also track the mixing of ions and backbone monomers across adhering interfaces. We find that increasing ion content decreases the mixing of backbone monomers but increases the mixing of ions. We suggest that, at short time scales, an intermediate ion content yields the strongest interfacial adhesion.   

Characterization of Thin Film Nafion Structure via Neutron Reflectometry and Complementary Techniques

The thin film structures of Nafion, the most widely used proton-exchange ionomer, impact the performance of proton-exchange membrane fuel cells (PEMFCs). Engineered Nafion surfaces were developed by Dowd et al. to alter the surface composition and wettability of Nafion to be hydrophobic or hydrophilic^[a]. Using neutron reflectometry (NR), we probe the through-plane structure of Nafion thin films to characterize potential structures at the engineered Nafion surfaces. Buried layers of phase-separated water/Nafion lamellae were observed in Nafion thin films at Au, Pt, and SiO₂ interfaces by Dura et al.^[b] and DeCaluwe et al^[c]. For this work, a titanium dioxide (TiO₂) substrate was applied to minimize the neutron scattering contrast to potential interface structures and enhance the NR sensitivity to the surface structure of engineered Nafion.

NR data of the neat Nafion:TiO₂ sample taken in dry (Ar, 0% RH) and humidified (H₂O and D₂O, 92% RH) environments are compared to determine the Nafion water content as a function of depth through the film. A non-lamellar, mixed-SLD region at the Nafion:TiO₂ interface was observed.

NR results of the hydrophobic and hydrophilic-engineered Nafion thin films on TiO₂ are compared to the neat films to determine water uptake differences and changes to the Nafion surface structure following modification.

^[a]10.1149/2.1081702jes ^[b]10.1021/ma802823j ^[c]10.1039/C4SM00850B   

Influence of solvent quality on structures within grafted polymer coatings

Polymers can be grafted to or grafted from surfaces to manipulate the properties of the surface. This can be used to prevent fouling of the surface or as an additional selective layer for separations. In good solvents and for long polymers, scaling theories can be used to understand the structure and properties of the polymer brush layer. However, in systems where attractions are important like poor solvents, the structure and properties are different and not easily described by simple theories. Here we show the results of simulations that include explicit solvent and attractions of the polymers and solvent. The structure of the brush depends on the solvent interactions and the processing conditions for making the brush layer.   

Determining Sequence–Structure Relationships for Calcium-Responsive Repeat Proteins

Responsive proteins enable myriad possibilities for engineering dynamic polymeric materials. We seek to quantify the nanostructure and dynamics of calcium-responsive polypeptides comprising repetitive "Repeats-in-ToXin" (RTX) domains. These domains remain unfolded in the absence of calcium ions but fold into β-roll conformations in the presence of calcium ions. A consensus repeat sequence from natural RTX domains was identified to control calcium-actuated structural change. Specifically, a conserved aspartic acid residue is involved in calcium ion binding; however, the roles of the remaining residues are not fully understood. We report a panel of twelve RTX variants in which an unexplored residue in the calcium-binding region was exchanged with various charged, hydrophilic, and hydrophobic residues. Circular dichroism indicates differential binding of variants to calcium ions, and small-angle X-ray scattering suggests the contraction of RTX proteins in the presence of calcium. Further probing of RTX proteins using X-ray scattering and crystallography will reveal the ability to systematically tune structure through protein sequence. Predictive control over protein structure and dynamics will enable the rational design of novel stimuli-responsive biomaterials.   

Phase diagrams of complex block copolymers: the DPD approach

In the last decades there has been enormous progress on our ability to predict the phases of matter. One particular area where this has occurred is in block copolymers through the use of coarse grained techniques such as Self-Consistent Mean-Field theory (SCFT)  or meso scale techniques such as Dissipative Particle Dynamics (DPD). Here, we show how a new parametrized force field for DPD is able to capture many new and old phases of complex block copolymers such as bottle brush, semi-flexible or multi-arm copolymers with almost quantitative agreement with experiments. The new parametrization is based on the classical coarse-grained representation of intermediate length polymers, which is the important experimental range for polymers. In the case of complex bottle brushes, we find never before - yet experimentally  observed – bicontinuous layered network morphologies, Frank-Casper Phases, and other more common phases. Finally, we present inverse-design strategies for synthetizing complex macromolecules targeted to self-assembled into prescribed phases.

    

Development of a machine learning-based closure relation for polymer integral equation theory

Theoretical approaches such as polymer reference interaction site model (PRISM) theory can compute quantitative thermodynamic and structural properties much more efficiently than traditional molecular dynamics simulations (MD). Thus, PRISM theory could serve as a fast and reliable computational screening method to discover novel polymeric materials and formulations. Despite the great advantages of PRISM theory, it can face issues with poor accuracy and numerical stability for some classes of polymeric systems, typically attributed to limitations in the analytical closure relations used to generate a numerical solution to the PRISM equations. In this work, we describe our efforts to develop a data-driven machine learning (ML)-based closure relationship to improve the accuracy and applicability of PRISM theory. We used coarse-grained MD simulations across a range of chain lengths, intermolecular interaction strengths, and thermodynamic conditions, to generate an initial dataset for closure development on a simple homopolymer system. Then, we evaluated multiple ML approaches to develop an improved closure function. Our goal is to develop an ML closure that minimizes regression errors while simultaneously satisfying the PRISM governing equations. We then describe our ongoing work to evaluate the ML closure’s transferability to unknown conditions, and to expand the work to other important classes of polymeric systems (e.g., copolymers, blends, polymer nanocomposites).

    

Bottlebrush Polymers Fold in Melts

Abstract: Bottlebrush molecules are branched polymers with a long linear backbone densely grafted by many relatively short linear side chains. Such a unique molecular architecture enables bottlebrush polymers with properties and functions inaccessible by their linear counterparts. The existing understanding is that, in melts of bottlebrush polymers, the inter-backbone distance decreases as the grafting density of side chains becomes smaller. Here, we experimentally discover a behavior opposite to all existing works: the inter-backbone distance increases monotonically as the grafting density decreases. To explain the remarkable experimental findings, we develop a theory by accounting for the incompatibility between side chains and the backbone polymer. The backbone polymer folds into a cylindrical core with all grafting sites on its surface to reduce interfacial free energy. As the grafting density decreases, the backbone becomes more collapsed; this process not only increases the diameter of the cylindrical core but also reduces the distance between grafting sites in space, such that the extension of sides is not alleviated. Our discovery presents a paradigm-shifting understanding of the molecular structure of bottlebrush polymers.

 

Keywords: Bottlebrush polymers; X-ray scattering; scaling theory

    

phase behavor of architecture-controlled bottlebrush copolymer system using graph convolutional network

In this work, we present studied the phase behavior of architecture-controlled bottlebrush copolymer in solution system using Graph Convolutional Network (GCN) based on Dissipative Particle Dynamics (DPD) simulation dataset. study with Graph Convolutional Neural Network (GCN) for predicting phase behavior from single chain parameters. Bottlebrush copolymer architecture was encoded by graph including connectivity, side chain length, bead types, and repulsion parameter of DPD simulation. First, single bottlebrush copolymer chain properties such as radius of gyration, volume of chain, asphericity, etc., was predicted using GCN with over Initially, the result of GCN show over 95% accuracy about single bottlebrush chain properties, such as radius of gyration, volume of chain, asphericity, etc., with the graph. Second, we put thesusede predictedthese single chain properties to predict into multi-chain self-assembly behavior in solution using multinomial classification model to learn morphologies of bottle brush copolymer in selective solution states. With this model, we made generated the phase diagram of self-assembled morphologies of bottlebrush copolymers having various architectureswe did not simulate. This work could significantly reduce the searching space for designing target morphology of bottle brush copolymers and provide information which single chain properties influence the phase behavior in selective solventsolution state.

    

Morphology, mechanical properties, and intermolecular interactions of ion gels based on phosphonic acid polymers

Ion gels prepared by immobilizing ionic liquids in polymer matrices have advantages of fast ion diffusion and easy control of mechanical properties over conventional solid electrolytes. Particularly, facile processability and reversibility of ion gels based on physical crosslinking networks have attracted recent attention. In the present study, we investigated phosphonic acid-based ion gels, where the intermolecular interactions were chemically controlled. Two approaches were used for the preparation of ion gels: (1) controlled polymerization of phosphonate styrene monomers in which the bonding position of the phosphonic acid group was precisely controlled and (2) introduction of various ionic liquids having dissimilar anions. This allowed the effective modulation of ionic interactions between the phosphonic acid groups and the ionic liquids, yielding significantly different chain packing structures, mechanical properties, and ion transport properties of the resultant ion gels. Investigation on ion gels based on phosphonic acid block copolymers was also conducted by focusing on the effect of types of ionophobic blocks and local concentration of phosphonic acid groups on the characteristics of ion gels.   

Controlling Ensemble Chain Conformations with Precise Sequence Patterning of Polypeptoids

Polymer properties are intimately related to chain structure at the molecular length scale. In biological polymers, control over folded chain shape via primary sequence patterning creates highly selective catalytic sites and nanomachines. Replicating this control over structure and properties through precise tuning of chain sequence affords opportunities to expand applications of polymeric systems. As a first step toward precisely tuned chain shapes, this work uses hydrophobic sequence patterning to narrow and shift the ensemble of chain conformations away from the Gaussian chain statistics of a random coil. Double electron-electron resonance (DEER) spectroscopy reveals that placement of hydrophobes at the chain ends drives the ends together. Meanwhile, scattering results show that this contraction in R_ee is not paired with a concomitant collapse in the overall chain dimensions, demonstrating a decoupling from the classical proportionality of R_g and R_ee with the introduction of sequence.   

Molecular mechanism of the Debye relaxation in monohydroxy alcohols revealed from rheo-dielectric spectroscopy

Rheo-dielectric spectroscopy is employed, for the first time, to investigate the effect of external shear on Debye-like relaxation of a model monohydroxy alcohol, i.e. the 2-ethyl-1-hexanol (2E1H). Shear deformation leads to strong acceleration in the structural relaxation, the Debye relaxation, and the terminal relaxation of 2E1H. Moreover, the shear-induced reduction in structural relaxation time, scales quadratically with that of Debye time, and the terminal flow time tau_f, suggesting a relationship of tau_d^2/tau_alpha. Further analyses reveal that 2E1H follows Arrhenius temperature dependence that applies remarkably well to many other monohydroxy alcohols with different molecular sizes, architectures, and alcohol types. These results cannot be understood by the prevailing transient chain model and suggest a H-bonding breakage facilitated sub-supramolecular reorientation as the origin of Debye relaxation of monohydroxy alcohols, akin to the molecular mechanism for the terminal relaxation of unentangled “living” polymers.

    

Rapidly Ordered Block Copolymer Membranes with Tunable Pore Sizes for Wastewater Treatment

The present surface water resources will soon be insufficient to meet the needs of the next generations. Wastewater is now contaminated with oil and other organic compounds due to the rapid rise in oil and gas, petrochemical, pharmaceutical, and food processing industries. Membranes present an easy and energy-efficient solution for removing both particulates and oily matter from wastewater. Here we present a methodology to rapidly order block copolymer thin films with well-defined through-thickness channels having minimal tortuosity. The technique involves casting BCP films from solution mixtures doped with selective plasticizing additives that segregate into one of the BCP domains. Owing to the selectivity and plasticization capability of the additive and the preferential solvation of BCP components in the solvent mixture, the film is fully ordered in the casting process. With careful selection of the casting environment, completely perpendicular domain morphologies with variable domain sizes can be achieved for high fluxes and tunable pore sizes. These films are supported by commercial membranes like PES and treated to selectively crosslink one and etch the other block to open the pores. The film microstructure is characterized via atomic force microscopy and x-ray scattering. At the same time, the membrane performance is tested using a dead-end cell and UV-vis spectroscopy.   

Extending BigSMILES to Non-Covalent Bonds in Supramolecular Polymer Assemblies

As a machine-recognizable representation of polymer connectivity, BigSMILES line notation extends SMILES from deterministic to stochastic structures. The same framework that allows BigSMILES to accommodate stochastic covalent connectivity can be extended to non-covalent bonds, enhancing its value for polymers, supramolecular materials, and colloidal chemistry. Non-covalent bonds are captured through the inclusion of annotations to pseudo atoms serving as complementary binding pairs, minimal key/value pairs to elaborate other relevant attributes, and indexes to specify the pairing among potential donors and acceptors or bond delocalization. Incorporating these annotations into BigSMILES line notation enables the representation of four common classes of non-covalent bonds in polymer science: electrostatic interactions, hydrogen bonding, metal-ligand complexation, and π-π stacking. The principal advantage of non-covalent BigSMILES is the ability to accommodate a broad variety of non-covalent chemistry with a simple user-orientated, semi-flexible annotation formalism. This goal is achieved by encoding a universal but non-exhaustive representation of non-covalent or stochastic bonding patterns through syntax for (de)protonated and delocalized state of bonding as well as nested bonds for correlated bonding and multi-component mixture. By allowing user-defined descriptors in the annotation expression, further applications in data-driven research can be envisioned to represent chemical structures in many other fields, including polymer nanocomposite and surface chemistry.   

Effects of localization length and spatial disorder on a charge carrier mobility in organic disordered semiconductors using Ab initio methods.Seyfan Kelil Shukri, Department of Physics, Salale University, Fitch P.O. Box 245, Ethiopia; seyfan74@gmail.com or seyfan.kelil@aau.edu.et

I investigate the transport properties of charge carrier disordered organic semiconductors with a focus on the determination and analysis of charge carrier mobility. By understanding that charge transport is due to incoherent hopping of charge carriers across localized states, I use a model that relates mobility to charge carrier (not small polarons) hopping by thermal activation. I consider the Miller–Abrahams expression to describe the hopping rate of charge carriers and employ Ab initio methods to generate data from which we can analyze charge carrier mobility as a function of applied electric field, temperature, localization length, and spatial and energetic disorder parameters. Based on my results, I discuss the effects of these parameters on charge carrier mobility. My results show the importance of the spatial disorder parameter and localization length in the effects of electric field dependence on charge carrier mobility, and I also evaluate the value of localization length that has been mostly considered as 0.1b, where b is the lattice parameter.   

Small molecules for integrated electro-optic modulators in nanophotonics

We discuss electrically poled small molecule assemblies that can serve as the active electro-optic material in nano-scale guided-wave circuits such as those of the silicon photonics platform. These monolithic organic materials can be assembled using physical vapor deposition in vacuum, making it possible to homogeneously fill nanometer-size integrated-optics structures. In addition, after deposition they can be electrically poled at higher temperatures to impart an orientational non-centrosymmetric order that remains stable at room temperature. As an example, using the "DDMEBT" molecule and corona poling delivers a material with the required high optical quality, an effective glass transition temperature of the order of ∼80°C, and an electro-optic coefficient of 20 pm/V. While this value is smaller than what can be achieved with poled polymers, it is comparable to LiNbO3, and the ability of small molecules to consistently and easily create a very homogenous filling in sub-100nm gaps is a unique advantage.   

The Entangled Triplet Pair in Rubrene: Quantum Beats

In crystalline organic semiconductors that consist of tightly packed small molecules, photon absorption can result in the creation of a pair of triplet excitons in an entangled spin state with zero total spin. Some well-known materials where this happens are single-crystal tetracene and rubrene. The individual excitons in a pair can undergo independent diffusion, randomly hopping in the crystal lattice. The probability that a photon is emitted by  triplet-pair is then proportional to the probability that the two excitons in the pair meet again.

We show that the photons created in rubrene on the occasion of geminate annihilation of a triplet pair can serve as a probe for exciton transport in the crystal lattice. By using a sub-picosecond pulse for photoexcitation, we obtain the time-dependence of the probability of photon emission over 6 time-decades using time-correlated single photon counting. Transport in one, two, or three dimensions can be distinguished and identified on different time scales after photoexcitation, from picoseconds to microseconds. Hopping times and hopping anisotropies can be derived, and temperature and magnetic-field dependence can then provide additional information.   

The entangled triplet pair in rubrene: transport

In crystalline organic semiconductors that consist of tightly packed small molecules, photon absorption can result in the creation of a pair of triplet excitons in an entangled spin state with zero total spin. Some well-known materials where this happens are single-crystal tetracene and rubrene. The individual excitons in a pair can undergo independent diffusion, randomly hopping in the crystal lattice. The probability that a photon is emitted by triplet-pair is then proportional to the probability that the two excitons in the pair meet again. We show that the photons created in rubrene on the occasion of geminate annihilation of a triplet pair can serve as a probe for exciton transport in the crystal lattice. By using a sub-picosecond pulse for photoexcitation, we obtain the time-dependence of the probability of photon emission over 6 time-decades using time-correlated single photon counting. Transport in one, two, or three dimensions can be distinguished and identified on different time scales after photoexcitation, from picoseconds to microseconds. Hopping times and hopping anisotropies can be derived, and temperature and magnetic-field dependence can then provide additional information.   

Rapid, High-Resolution, Large-Area Patterning of Semiconducting Polymers using Projection Photothermal Lithography

Semiconducting Polymers (SPs) have received widespread attention due to their promising qualities like superior absorbance/emission, easy chemical tunablity, low-temperature solution processing, lightweight and flexible substrates, and low environmental toxicity. A significant obstacle for the industrial development of SPs is the lack of a patterning technology that is inexpensive, rapid and viable and capable of producing sub-micron features. Photomask lithography is impossible because the SPs cannot withstand the processing steps. The Moule group recently developed a new photopatterning concept that enables micropatterning of SPs. We present a novel solution based optical patterning method that is compatible with any non-cross linked SP, termed Projection Photothermal Lithography (PPL). We have built a lab scale PPL microscope and demonstrated rapid (∼ 4cm²hr⁻¹), large single exposure area (0.21 mm²), sub-μm patterns can be obtained optically. Selective polymer domains are removed as a photo-induced temperature gradient enables selective dissolution. We estimate the commercial patterning throughput of (∼ 5 m²hr⁻¹) can be obtained through optimization of optical components.    

Surface structure, mechanics and rheology of amphiphilic polymer conetworks on different length scales

In order to allow the simultaneous transport of hydrophilic and hydrophobic substances, networks with fine-structured hydrophilic and hydrophobic components are requested. Amphiphilic polymer co-networks (ACNs) can be tailored to create gels that selectively swell or collapse in different solvents with the corresponding polarity and greatly impact transport properties through these networks. 

This study focuses on the relation between structure, swelling abilities and mechanical/rheological properties of films of ACNs.^1,2 First, the correlation between different synthesis strategies for gel films and their resulting properties will be described. Secondly, the effect of solvents of different polarity on the swelling ability will be presented on different length scales. For this purpose, topology and near surface structure are studied with atomic force microscopy (AFM). We also put special emphasis on the determination of mechanical and rheological properties laterally and orthogonally to the gel surface by carrying out dynamic AFM indentation experiments. In order to evaluate heterogeneities the mechanical and rheological behavior at the interface of the ACNs will be presented on various length scales (nm - µm). The study shows that the synthesis strategy has a strong effect on the gel structure and on nano/microrheological properties. The structure and rheology of gel films will be compared with results obtained of the respective bulk gel phase.   

The role of imperfection geometry in the buckling of thin spherical shells

The elastic buckling of thin spherical shells under external pressure is sudden and catastrophic, often driven by geometric imperfections several orders of magnitude smaller than the shell radius. Recent work has demonstrated that under uniform external pressure, the reduction of the critical buckling load caused by a localized imperfection can be precisely predicted using a priori knowledge of the defect geometry, opening the door for further work towards understanding the complex and fascinating imperfection sensitivity which pervades their mechanics. Merging desktop stereo-lithography 3D printing with recently developed techniques for introducing symmetric, dimple-like defects into the shell’s mid-surface, we utilize a combination of precision experiments and results from classical shell theory to investigate the effects of defect amplitude, angular width, and localized thickness variation in the reduction of the buckling strength of spherical shells under uniform external pressure. Then, to explore the role of defect shape, we present a technique to create asymmetric defects which allows for systematic variation of the amplitude and degree of asymmetry of the imperfection. Utilizing a point-loading probing scheme, we characterize the stability landscape and evaluate the variation of the buckling strength over a range of pressurization levels and applied probe forces.   

Measuring spontaneous charging of single aerosol particles

Charge accumulation on airborne particles and droplets plays a critical role in a variety of natural and industrial processes. It gives rise to lightning in thunder- and sandstorms and can lead to dangerous dust explosions during industrial processing. Shavlov et al. [1] suggest that the hydroxide ions and protons formed by the dissociation of water molecules are sufficient to cause charging during evaporation and condensation of droplets or surface-adsorbed water on solid particles. This hypothesis is backed up by Moreira et al. [2] who find that liquid evaporation leads to charge buildup on dielectric surfaces.

            By levitating individual aerosol particles in an optical trap [3, 4] we study this proposed charging mechanism. Our setup allows for trapping of various types of solid and liquid particles in the micrometer size range. The particle’s charge is measured by applying a sinusoidal electric field and observing the resulting particle motion. The Mie scattering pattern of the particle furthermore gives information about the particle’s size and refractive index, both at equilibrium and during evaporation and condensation.

            Ultimately we aim to gain detailed insights into the proposed evaporation-condensation-charging mechanism and its implications for the triboelectric effect and atmospheric electricity.

Role of access resistance in governing conductance in nanopore translocation experiments

Nanopores are valuable for a variety of applications such as biomolecule detection, sequencing, and fingerprinting applications, among others. Electrical signatures from nanopores provide information about the morphological characteristics of translocating biomolecules. Therefore, careful interpretation of these signatures and accurately modeling the accompanying conductance blockades is critical for practical applications and remains an open question in the field.

The key resistances in the system include access (or convergence) resistance and channel resistance. In addition to their dependence on pore geometry and salt concentration, both quantities are perturbed due to the presence of an analyte inside the pore. 

We numerically solve fully coupled Poisson-Nernst-Planck and Navier Stokes system of equations and predict conductance blockades for a range of geometrical parameters. We find that the state-of-the-art approaches are inaccurate for experimentally relevant conditions – thin pores and size of the analyte comparable to pore diameter. Our results underscore that the usage of the existing models is limited.

We combine computational and analytical modeling and propose a new model for access resistance accounting for the presence of an analyte inside the capture region. The proposed model is validated using computer simulations and experimental data. These results constitute an important step towards accurate, physics-based modeling of conductance in nanopores and ion channels.

    

Motor-driven advection competes with crowding to drive spatiotemporally heterogeneous transport in cytoskeleton composites

Particle transport through the cytoskeleton can range from anomalous and heterogeneous subdiffusion to superdiffusion and advection. However, fully understanding the mechanisms by which cytoskeletons induce these different types of transport remains challenging. Here, we combine light sheet microscopy and single particle tracking to elucidate anomalous transport in actomyosin-microtubule composites. We show that particles in these composites exhibit multi-mode transport that transitions from pronounced subdiffusion to superdiffusion at tunable crossover timescales. In particular, we find that increasing actomyosin content enhances superdiffusion at longer time scales via myosin motors inducing ballistic-like contraction, restructuring, and flow of the composites and enhances subdiffusion at shorter time scales via steric entanglements, connectivity, and slow thermal relaxation of cytoskeletal filaments.   

Enzyme kinetics in salt resistant complex coacervate emulsions

Research in protocells has burgeoned in recent decades due to their fundamental importance in the origin of life and their latent technological potential. Complex coacervates formed by liquid-liquid phase separation of charged macromolecules can be simplistic protocellular models with a distinct interface, spontaneous biomolecular sequestration, and chemical conversions within macromolecularly crowded environments. While the bulk material properties of such coacervates are well understood, this knowledge is yet to be applied towards tailoring protocell design. A major limitation was the long-term stabilization of the liquid-liquid interface, which we previously demonstrated using comb-polyelectrolytes (cPEs). In this talk, we demonstrate that this approach is generic and works with distinct polymer characteristics and salt identities, over a wide range of concentrations. We show improved salt resistance of droplets, tunable by cPE concentration and an expansion of the two-phase window. Improvement of coaocervate droplet interfacial stability by cPEs is attributed to both kinetic and thermodynamic effects. In essence, at low cPE concentration, the excess charge by its pressence does not influence the phase behavior significantly and the droplets are kinetically stabilized. At higher cPE concentrations, both kinetic and thermodynamic effects stabilize the coacervate droplets against salt.   

Magnetic-field and spin polarization effects on electron transport in dsDNA molecules

The magnetic field and electron spin effects through the double-helix structure of DNA molecules connected to semi-infinite electrodes are studied. Our theoretical approach involves the application of the two-dimensional tight-binding Schrödinger equation and Landauer-Buttiker formalism to calculate transmission and electric current through the nearest-neighbors of twenty base-pairs’ DNA. We also incorporate a variation of magnetic field flux density into the hopping integrals as a phase factor and observe Aharonov-Bohm oscillations with their periodicity in the transmission. Under the electron spin and backbone effects, we show that the ds-DNA serves as a perfect spin filter despite the weak spin-obit coupling, and therefore its spin filtration efficiency could be enhanced by increasing the DNA length. More importantly, the dsDNA could also act as either a semiconductor or a metal depending on the spin-orbit coupling strength, which show high percentage of spin-polarized current at a specific bias voltage.

    

Engineering Adaptable Materials via crosslinking by Circadian Clock Proteins

Circadian oscillators exist in nearly all living organisms to regulate sleep cycles, metabolism and, in the case of cyanobacteria, the timing of photosynthesis. The cyanobacteria circadian clock involves the cyclic binding and unbinding of monomeric KaiB proteins to hexameric KaiC rings over a regular 24-hour cycle. Here, we exploit this system to enable time-dependent aggregation and gelation of colloids in suspension. Specifically, we coat colloids with KaiB proteins such that KaiC rings act as crosslinkers to connect and cluster colloids via time-varying binding to KaiB. We use fluorescence microscopy and sedimentation experiments to show that mutant KaiC proteins that are frozen in the 'KaiB-binding' state lead to large scale percolated structures of colloidal aggregates that continue to slowly grow over several days. Conversely, with non-binding KaC mutants, the materials remain as diffuse suspensions of single colloids. Wild-type KaiC proteins lead to time-varying crosslinking and aggregation that is controlled by the phosphorylation state of KaiC. We build on this work by demonstrating that this platform can enable time-varying material properties that span from the microscopic to macroscopic scale and can be easily incorporated into synthetic and biological materials for potential applications in pharmaceuticals and adaptive bio-inspired infrastructure.   

Differential Dynamic Microscopy Enhanced with Convolutional Neural Networks

Differential dynamic microscopy (DDM) has been widely used to analyze the dynamics of bacteria, colloidal particles, gels, and other soft matter systems. With this Fourier-space image analysis technique, one typically needs 100s to 1000s of images in a time series to accurately quantify dynamics. When fewer images are used for DDM analysis, the output can be too noisy to reliably quantify the dynamics. Here, we employ a convolutional neural network (CNN) to denoise DDM data. With this machine learning approach, we can obtain accurate values for the characteristic decay times of density fluctuations in colloidal suspensions using only 10s of frames. The ability to accurately perform DDM with short durations of imaging data enables the study of samples in which the dynamics are quickly changing. We demonstrate this approach of using DDM with machine learning to quickly perform microrheology measurements on colloidal particles throughout a sample slide with spatially varying properties, highlighting the high-throughput microrheology enabled here.   

Asymmetric Functionalization of Colloidal Microcapsules

Cell mimics are microstructures engineered to emulate the features and behavior of biological cells. Their development can help expand our fundamental understanding of cell biology and create countless opportunities in nanotechnology. While some cell mimics made of bio-materials can recreate certain cell functions and structures, fully abiotic cell mimics remain rudimentary in their design and lack functionality. In my talk, I will describe a synthetic process for fabricating colloidal microcapsules with well-defined geometries and tunable internal chemistry.   

Shaping the interaction behavior of mechanically linked colloids

When engineering materials on any length scale, building block shape (and organization) determines properties and function of bulk material. One common challenge in colloidal synthesis is optimizing particle geometry design for specific particle-to-particle interactions. Herein, we investigate the relation between shape and interaction behavior by engineering the morphology of hexapod-shaped colloidal particles. The arms of hexapods can be finely tuned to be straight or winding and display unique mechanical-linkage interactions attributed to particle geometry. Upon particle packing, the mechanical interaction is characterized as reversible or irreversible, on short timescale, and display interaction behaviors visible on the macroscopic scale.   

Lattice Boltzmann simulations of formation and deformation of bicontinuous emulsion gels in magnetic fields

Particle stabilized emulsions are of interest for their stability, environmentally friendliness, and possibility of microstructure tuning. One particular emulsion structure is known as the bicontinuous interfacially stabilized emulsion gel (bijel) and has shown promise in developing membranes, catalyst supports, templates and pharmaceuticals. We present lattice Boltzmann simulations of magnetic response of bijels synthesized with anisotropic particles. The results show that the domain size of the bijels increases with increasing magnetic field strength, while the interfacial area and the Gaussian curvature of the interface decrease. We hypothesize that this effect is due to the way particles pack within the interface, changing the jamming point. Under magnetic fields, the particles reorient and the orientational order increases with magnetic field strength, thereby allowing closer packing of the particles This link between microstructural changes and particle packing is not observed in bijels stabilized with spherical particles, lending support to the hypothesis that the orientation of the particles alters the jamming point of the bijel.   

Tuning the transition from wrinkle to secondary bifurcations

The mechanism for wrinkling in a bilayer composed of a thin, stiff film on top of a thicker, softer substrate under compression has been elucidated. However, the mechanism for subsequent bifurcations when further compression is applied remains elusive. Several studies have shown that wrinkles change to period doubles in elastic bilayers at a compressive strain of about 20%. Substrate nonlinearity has been attributed to explain this quite universal value. Yet, it is still not sufficient to unify multiple open questions including why the transition is not significantly affected when the bilayer systems are modified with certain levels of compressibility and what are the parameters that can be used to adjust it. This work explores the substrate properties that can be employed to tune the transition from wrinkles to secondary bifurcations through finite element modeling. We show that factors like the directionality (fiber-reinforced nature), and damage, viscoelasticity, or plasticity (dissipative nature) significantly affect this transition. Unlike elastic systems, this work provides the capability to make wrinkle transform to secondary bifurcations at a smaller strain, which might be critical for developing a universal analytical theory to better understand this transition.

 

    

ATRP-brush modification of variably shaped surfaces and biopolymer adsorption: Dissipative particle dynamics simulation study

We present a DPD simulation study on the surface modification of initiator-embedded microparticles (MPs) of different shapes via atom transfer radical polymerization (ATRP) brush growth. The ATRP-brush growth leads to forming of a more globular MP shape. We perform the comparative analysis of ATRP-brush growth on three different forms of particle surfaces: cup surface, spherical surface, and flat surface (rectangular/disk-shaped). First, we establish the chemical kinetics of the brush growth: the monomer conversion and the reaction rates. We next argue the structure changes (shape-modification) of brush-modified surfaces by computing the radial distribution function, spatial density distribution, radius of gyration, hydrodynamic radius, and shape factor. The polymer brush-modified particles are well known as the carrier materials for enzyme immobilization. Finally, we study the biopolymer adsorption on ATRP-brush-modified particles in a compatible solution. In particular, we explore the effect of ATRP-brush length, biopolymer chain length, and concentration on the adsorption process. Our results illustrate enhanced biopolymer adsorption with increased brush length, initiator concentration, and biopolymer concentration. Most importantly, when adsorption reaches saturation, the flat surface loads more biopolymers than the other two surfaces. The experimental results verified the same, considering the disk-shaped flat surface particle, cup, and spherical particles.

    

Switching Adhesion with Origami

One of the most interesting features of origami, is its ability to form both mechanically stable (or stiff) and unstable (or soft) configurations.  Here we show how the changes in stiffness of origami structures relate to their adhesion with surfaces.   Specifically, we designed three bi-state origami designs made of polycarbonate, cut with a Cricut cutter, and supplemented with 3D printed “holders” to decrease the compliance of the stiff state.  We use well-understood polydimethylsiloxane(PDMS) elastomers as adhesive pads in order to carefully explore adhesion as the designs shift their mechanical state.  Ultimately, we show how the ‘stiff’ state breaks adhesive contact similar to a bulk solid, soft states tend to fail by initiating ‘peel’ modes on various facets.  According to our observations, we are capable of moderate switching ratios (Fon/Foff ~50) and offer many options for scaling designs up or down in size as well as pointing out practical considerations for manufacturable devices.

    

Low Refractive Index Binary Colloidal Crystals from Charged Fluorinated Polymers

Under the right conditions, oppositely charged colloids in water can serve as model ions and form bulk ionic colloidal crystals^[1]. To study structure and crystallization dynamics of these binary systems we developed low refractive index colloidal spheres that can be index matched in water:DMSO mixtures, thus enabling in situ 3D confocal microscopy. Our particles can be made both positively and negatively charged, with uniform sizes ranging from 100 nm and 500 nm. Here, demonstrated that even when dispersed in pure water, our model system crystallizes into nearly transparent ionic colloidal crystals that can be imaged in bulk with single-particle precision.   

Diffusion of DNA in active and passive enzyme baths

Enzymes—catalyzing protein complexes—have been shown to exhibit enhanced diffusion in the presence of their substrate, potentially creating the makings of a molecular-scale active matter system. Directly quantifying the enhanced diffusion of an enzyme can be challenging due to the difficulty of reliably imaging/tracking its motion. Differential Dynamic Microscopy (DDM), which combines real-time video microscopy with Fourier analysis of light scattering has been shown to accurately quantify the diffusion of diffraction limited molecules, such as single-stranded DNA (ssDNA). We use ssDNA as a diffusion probe in enzymatic (urease) baths to characterize activity. We investigate if the presence of bulk enzymatic activity can affect the diffusion of passive molecules – in this case, ssDNA. We characterize our enzyme baths through UV-vis spectroscopy to determine the linear range and timescale of activity. These experiments on the activity of enzyme baths have the potential to unlock a large design space for molecular-scale active matter.   

Diffusion of colloids in an active enzyme bath

The diffusion of microscopic particles suspended in a fluid due to random thermal fluctuations in the surrounding environment is a manifestation of Brownian motion. It has been hypothesized that these particles can experience enhanced diffusion if catalysis of an enzyme-substrate reaction is included in the fluid bath. Using differential dynamic microscopy we look to extract the dynamics of colloidal suspensions in the presence of enzyme activity, specifically a urea-urease reaction, and verify enhanced diffusion when compared to colloids in a bath with no activity. In order to verify the activity and timescale of our enzyme bath we use a phenol red assay to measure the change in absorbance over time at the 560nm wavelength, which indicates enzymatic activity through a pH change. Preliminary results suggest that our urea-urease enzyme bath is active and Brownian-like diffusion of colloids can be characterized via differential dynamic microscopy. We investigate the dependence of passive colloid size on diffusion enhancement due to enzyme bath activity. These experiments set the stage for using active baths to drive transport of passive objects.   

Revisiting assertions of boosted mobility of catalytic enzymes

If it is a truism that science progresses by lively debate, then dueling claims of boosted diffusion (or not) of enzyme diffusion must be leading to rapidly-progressing understanding. In the face of the asserted lack of evidence of boosted diffusion, here we contribute with new experiments: (1) we expand the range of catalytic enzymes for which enhanced diffusion is reported, (2) we visualize the diffusion of fluorescently-labeled single enzymes, and (3) we make progress in explaining large disagreements in the literature about what quantitatively is the turnover rate for particular enzymes.   

Curvature-driven Interfacial Fracture in Growing Elastic Shells

Biological interfaces can undergo instabilities that are triggered by growth. Especially interesting is the response of doubly curved growing interfaces. Motivated by the surgical problem of endograft seal zone stability, where a cylindrical membrane covered stent initially in contact with the inside of an artery losses contact, we study the stability of interfaces with varying curvatures under various loads. This computational study implements isotropic growth in a finite element model. The adhesive interface is modeled using cohesive zone mechanics (CZM). The load on the interface comes from growth as well as flow inside the lumen of the curved cylindrical shells. We perform a coupled fluid-structure-fracture simulation (FSFS).  We capitalize on our expertise with explicit dynamic approaches for solid mechanics/fracture and couple them with a Lattice-Boltzmann (LB) code to model fluid flow (CFD). Our data shows that singly curved interfaces, such as cylinders, lose stability uniformly and follow an edge-delamination mechanism. However, doubly curved interfaces, like a toroidal section of a bent cylinder, fail non-uniformly. The negative Gaussian curvature section is more sensitive to fracture compared to the spherical section. Our data can be used to better design endograft stents for optimal seal in vascular surgery. 

    

Capillary detachment of a microsphere from a liquid-liquid interface

The attachment and detachment of microparticles at liquid-liquid interfaces are important for a number of material systems, from capillary suspensions and emulsions to coating applications. Hence, capillary forces become relevant to develop appropriate guidelines for designing these material systems. The required work to detach microparticles from a liquid-liquid interface is related to the shape of the meniscus; however, measuring capillary forces on a single microparticle at a liquid-liquid interface, while simultaneously imaging the meniscus, can be challenging. In this study, we correlate the detachment force with the shape of the meniscus by combining colloidal probe, atomic force microscopy (AFM) and laser scanning confocal microscopy. We measure the force and visualize the capillary bridge on a hydrophilic or hydrophobic microparticle, which is being pulled from a thin glycerol film surrounded by silicone oil. A fundamental model for detachment, based on capillary theory, is verified with different conditions. Moreover, we demonstrate that the interfacial tension and the continuous change of contact angle for a pinned contact line must be considered to accurately predict the detachment force.   

Molecular Dynamics Simulations of Water in Confined Surfaces

The freezing and thaw cycles of water in confined media, such as the pores of soil, need to be understood as it impacts infrastructure development in cold regions experiencing the effect of large variations in temperature. In this project we use the TIP4P/2005 model of water in the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) to try and uncover some poorly understood qualities of water. The four site TIP4P/2005 model was chosen over other water models, and even over other four site models, since it gave the most accurate results for density over other models for hexagonal ice. This model includes sites for two hydrogen atoms, one oxygen atom, and a virtual "m" atom between the two hydrogen atoms. Previous literature shows that when liquid-ice boundaries are coexisting with solid surfaces there is a solidification effect on the water molecules even with minimal or no change in temperature or pressure. The Vashishta potential was used to simulate the interactions between the SiO2 wall atoms, and an NPT ensemble was decided upon for our calculations in order to maintain consistency with the literature. For initial simulations we used walls made of an alpha-quartz silica lattice and compared it to walls of amorphous silica glass. Our results will enable us to understand the fundamental principles governing ice formation in confined systems.   

Colloidal Dispersibility of Graphene from the Perspective of Inter- and Intra-particle Interactions

Graphene oxide (GO), one of the graphene derivatives, is well known for having good colloidal stability and dispersibility in some solvents, including water, ethylene glycol, 1-Methylpyrrolidin-2-one, N, N-Dimethyl-formamide. The excellent dispersibility of GO is attributed to the hydrophilic functional group with a negative charge on the surface, and as the hydrophobic graphitic domain extends from the surface, the dispersibility is either maintained or not depending on the solvent.

First, the basic structure and physical properties of GO dispersions in each solvent were investigated. Then, each GO dispersion was mildly heated, which increase a graphitic domain of GO. The change in the dispersibility of GO with mild heating suggests proper processing conditions for GO-based applications such as GO-polymer composites. This study answers the question of the mechanism by which graphene particles are sensitive to certain solvent properties and their interactions with solvents change. This study further answers the question of how the interaction with the solvent in the dispersion of graphene particles varies with the solvent and what is the dispersion mechanism in solutions.

    

Viscoelasticity of multi-armed PEG hydrogels by tweezers-based opto-microrheometry

Hydrogels, like extracellular materials, possess both solid and liquid-like properties; if their mechanical properties can be tailored precisely, they can be used not only to understand how cells respond to an extracellular environment but also for designing engineered tissues. However, multiple parameters that can dictate the viscoelastic properties of hydrogels are complex, it is difficult to predict mechanical properties of hydrogels simply from their molecular structures. To this end, an oscillating optical tweezer-based opto-rheometer is used to measure the micro viscoelasticity of an eight-armed PEG-DBCO covalently cross-linked with PAN MMP. Dependence of the viscoelasticity on the polymer concentration is measured. Viscoelasticity data is analyzed using the Maxwell model to examine how relaxation times and high-frequency shear modulus depend on the polymer concentration.   

A density-independent glass transition in designer active granular matter

Dense assemblies of active particles are thought to undergo dynamical arrest akin to supercooled equilibrium liquids. However, how activity modifies the approach to a glassy state continues to be debated. Addressing this question is essential even as a growing body of evidence suggests that dense assemblies of biological cells share hallmark traits of equilibrium glass physics. By designing synthetic active matter systems that capture certain key features of living ones, we systematically investigate active glassy dynamics in this model system. This allowed us to explore the interplay of nature and the degree of activity, shape and topological defects on glassy slowing down. We observed non-trivial relaxation mechanisms unique to active glasses. We anticipate that our experimental strategy will help prune theoretical predictions of active glasses.

    

Preparation and assembly of mesoscale polydimethylsiloxane ribbons

Long, thin filaments are widely used in nature and our everyday lives, from collagen fibrils to yarns. These building blocks assemble into hierarchical structures in order to achieve impressive, multifunctional performance properties, which are difficult to replicate with any other structures. Creating such structures using bottom-up fabrication methods with synthetic materials is challenging due to the complex topological pathways and numerous force interactions that need to be navigated and managed. Building upon recent studies focused on understanding and controlling multiscale kinematics of mesoscale polymer ribbons, we introduce new methods to fabricate crosslinked polydimethylsiloxane (PDMS) mesoscale ribbons. PDMS ribbons allow us to manage reversible adhesion interactions between neighboring ribbons, large scale elastic movements, and well-established solvent-PDMS interactions to control swelling-induced transformations. We use subtractive transfer printing to prepare the crosslinked PDMS ribbons, and we quantify the influence of processing parameters, including elastic modulus, thickness, and rates of transfer-based deformations. Furthermore, we demonstrate the ability to release mesoscale PDMS ribbons into fluid environments and observe transient swelling-induced deformations.   

Mesoscale Block Copolymer Ribbons

Mesoscale polymer ribbons combine nanoscale thickness with macroscale length, providing  unique opportunities to mimic mesoscale biological organization and dynamics. In these systems, elasticity, interfacial forces, and geometry all play important roles in controlling shape transformations and the properties of the final assembled structures. Here, we discuss recent work  focused on preparing highly adaptable mesoscale ribbons from block copolymers in order to provide multiscale, multifunctional control of properties and shape transformation kinematics. Polystyrene-block-polybutadiene (PS-b-PBd) ribbons were fabricated, and the relative block volume fractions were varied to investigate the influence of elasticity and interfacial forces on ribbon formation and properties. The preserved double bonds allowed for facile photopatterning, enabling the introduction of site-specific mechanical properties to aid active control of specific transformation kinematics. The hierarchical organization of block copolymer-based mesoscale ribbons provides key control parameters for mimicking and understanding active polymer systems observed in nature.   

Beyond Poisson-Boltzmann: A self-consistent theory for electrical double layers

One outstanding challenge in the physical chemistry of electrolyte solutions is to capture the inhomogeneity in electrostatic correlation where either the ionic strength or the dielectric permittivity is spatially varying. A solution to this problem is critical to understanding many complex interfacial phenomena such as like-charge attraction and charge inversion, among many others. The standard mean-field Poisson-Boltzmann (PB) theory fails to explain even qualitatively these as it does not take electrostatic correlations and excluded volumes of molecules into account. Using the Gaussian Renormalized Fluctuation theory, we have developed a new method to self-consistently solve for inhomogeneous ionic fluctuations and dielectric variations via a self-energy term and the effect of excluded volume of ions and solvent through an incompressibility constraint. The first system we investigated using this method is the vapor-liquid interface of ionic fluids. For symmetric salts, the surface tension predicted by our theory is in quantitative agreement with the simulation data. Ours is also the first self-consistent theory to successfully explain the phenomena of charge inversion and like charge attraction in multivalent electrolytes. In quantitative agreement with experiments, the value of zeta potential is found to depend non-monotonically on the bulk salt concentration. For a system of two like-charged surfaces immersed in a multivalent salt solution our theory again correctly predicts an attractive electrostatic force. In agreement with simulations, we show that the strength of attraction varies non-monotonically with respect to bulk salt concentration. Our work provides the first explanation of the re-solubilization of charged colloidal aggregates consistent with the non-monotonic nature of the effective surface charge after inversion. In the future, we and our collaborators aim to understand polyelectrolyte brushes, ionic liquids, and surface tension at the air-water interface with this new method.   

Understanding molecular adsorption through the lens of persistent homology

Topological descriptors associated with amphiphile adsorption at liquid/liquid interfaces have been developed. These are based upon sublevel set persistent homology analysis of images of the adsorbate density projected onto a plane. For example, tributyl phosphate (TBP) is considered adsorbed to the electrolyte/hexane interface as a function of the ionic strength of the aqueous phase, which tunes the adsorbate interfacial concentration. TBP is known to form organized dimeric assemblies, and the topology is compared to analogous adsorption surfaces representing stochastic distribution. We demonstrate that persistent homology descriptors like Persistent entropy (PE), Persistent Lifetime, Non-ideality index, Betti curves, etc., are good descriptors for characterizing topological heterogeneity within the adsorption surfaces. This work lays the foundation for further quantification of the PH-based descriptors to understand the fundamental chemistry at chemical and biological interfaces.   

Understanding Interfaces in Rare Earth Separations via Multiple Surface Specific Probes

Chemical separations are central to our energy, environment, and security needs. From efficient refinery and recycling of rare earths to cleanup of contaminated underground waters, chemical separations cover a wide range of processes such as liquid-liquid extraction (LLE), membranes, and sorbents. A common theme in most processes is that the target ions need to adsorb on or go through an interface. Understanding aqueous interfaces at molecular scale, require special experimental techniques that can distinguish the interfacial structures from the overwhelmingly larger bulk.

Surface sensitive synchrotron X-ray scattering and fluorescence, and vibrational sum frequency generation (SFG) spectroscopy techniques are among the most advanced tools available to study aqueous interfaces. This poster summarizes our group’s efforts in understanding aqueous interfaces in chemical separations, by combining these two experimental techniques. It demonstrates specific examples where a single method is not enough to decipher the complex interactions at the interface. The examples cover ion-amphiphile interactions in LLE and ion adsorption on graphene-oxide thin films.   

Hexagonal packing in gravitationally confined quasi-two-dimensional colloidal silica systems

Colloids are made from small solid particles in a liquid. When the particles are heavier than the liquid, they will eventually sink to the bottom of the liquid.  We use this to form a monolayer of particles at the bottom of a microscope sample chamber.  At high enough particle concentration, this monolayer organizes into a hexagonally packed crystal.  However, the structure is influenced by the interplay between gravity (causing the sedimentation) and diffusion (helping particles organize into a crystal).  We use high-density silica colloid particles of different sizes to study how the competition between thermal fluctuations and gravitational sedimentation affects the final structure of the layer.

 

    

Janssen Effect in a 2D Grain Silo with Photoelastic Particles

This work examines the Janssen effect 2D silo, using photoelastic disks as the grains. As the total height of particles in a system increases, the effective mass at the bottom of the silo is less than the total mass of the particles. This is because some of the weight is supported by the walls, as frictional force chains can act to redirect the weight force to the walls. By using photoelastic particles, we can characterize the statistics of the force chain network of a packing. For repeated experiments at a particular filling height, there will be differences in the force chain structure and statistics, due to the stochastic nature of filling the system. We seek to characterize the full spectrum of the system’s microstates for a given packing height. We repeat this analysis for differing heights in the system. This work will be used as a future diagnostic as we study the flow of particles and jamming around obstacles in this silo.

    

Soft Robotic Actuation Using Magnetorheological Fluids: Effects of Fluid Properties

We study the behavior of a soft robotic actuator. The device flows magnetorheological (MR) fluid through the actuator using a peristaltic pump, and the actuation is initiated by applying a magnetic field to locally solidify the fluid. This creates a pressure buildup in the actuator, which then bends due to a differential stiffness between its two sides. We investigate how different properties of the MR fluid (particle size, non-Newtonian rheology, etc.) and device geometry affect actuation efficacy. The actuation efficacy is quantified by both the speed of actuation and the force produced by the actuator. The results are compared to determine the best combination of MR fluid parameters and device architecture for robust actuation.   

Shearing of jammed granular systems with fixed pinning sites

The rheology of granular media is characterized in part by shear jamming, in which shearing of collections of individual grains under confinement leads to a transition from fluid-like to solid-like behavior. Such systems are driven by the boundaries and exhibit anisotropic force networks and history-dependent behavior. Here we experimentally investigate planar shear of an athermal, granular system with small pins inserted within the shearing zone which act as fixed obstacles within the bulk. We use photoelastic grains to visualize the stress networks and particle tracking to characterize particle locations and kinematics. We characterize the mean flow and stress response when small numbers of pinning sites are present in the system. We find that these pins can act as additional supports to stabilize the stress network and enhance anisotropy based on their arrangement. Such experiments represent a step to exploring the effects of pinning lattices which may offer a route to tunable granular rheology.   

Author not Attending

Although we have a fundamental understanding of foam collapse mechanisms, we are still lacking a clear insight into which foam and solution properties correlate to foam stability. For example, we know that the addition of surfactants is needed for foam generation but are not able to relate the foam stability of different surfactants to any one surfactant property. Furthermore, we know that the bulk solution rheology can be engineered to increase foam stability, but we cannot say with any certainty which rheological property maximizes foam stability. In this work, we propose a correlation between foam stability and bulk rheological properties. Here, we present an extensive rheological study of more than 15 formulations using different combinations of surfactants and viscosifiers that are typically used in commercial shaving cream formulations. All foams studied here are wet foams (φ > 10%) and were generated by using nitrous oxide as a propellant.  Our findings suggest that foam stability correlates to the magnitude of elastic modulus () and the linear viscoelastic phase angle  (tan δ = G”/G’) measured at low frequency ( s^-1). More specifically, the correlation between foam half-life and δ shows a better correlation than other physical parameters such as surface tension and viscosity. We also find that the half-life jumps by an order of magnitude when the modulus is larger than 10 Pa. These results present the first correlations between bulk material parameters and foam stability over a wide range of foam formulations.       

    

The Life of a Thermal Marangoni Bubble

Air injected in a pool of pure liquid forms bubbles at the interface that do not live long, unlike bubbles that dwell on a bath containing surfactants. Here we consider a situation where the pool is pure (made of oil), yet hot. We find that the bubbles at the surface can then live for minutes or even longer. We interpret this longevity as a consequence of the gradients of temperature generated in this experiment - oil is observed to be continually drawn to the apex of the bubble opposing its gravitational drainage, which reveals the dynamical nature of the lives of the thermal bubbles. A little bit of heat not only breaks the ephemerality of bubbles of pure liquids, but also endows the oil film with a remarkable stability and persistence.   

Eggless Vegan Food Emulsions

Food emulsions like mayonnaise, remoudale, French aioli, rouille, and others that are used as dressing, dips, or sauce bases are often egg-based. In this poster, we present the challenges and opportunities in emulating such emulsion recipes using plant-based proteins. We focus primarily on emulsification, shelf-life, processability and consumer experience or preferences set by the flow behavior. We characterize the shear and extensional rheology response of animal and plant-based emulsions and study the interfacial and bulk rheology of protein-polysaccharide mixtures utilized in making such emulsions.   

Effect of Ionic Strength on Foaming Behaviors of Per- and Polyfluoroalkyl Substances (PFAS) Solutions

Per- and polyfluoroalkyl substances (PFAS), a group of partially or fully fluorinated organic chemicals, have been widely used in many fields, such as non-stick cookware, aqueous film-forming foams (AFFFs), and food packaging. However, the main concern associated with using PFAS is their toxicity and accumulation in the human body. The PFAS are mainly transported through the air-water interfaces in water resources owing to surfactancy of PFAS molecules. Foam fractionation is one of the promising remediations to remove surfactants and colloids from water resources. Nevertheless, the foam fractionation at present is not viable for PFAS removal. Therefore, with the aim of making the foam fractionation viable and practical for PFAS remediation with improved removal efficiency, we conduct fundamental studies on the interfacial properties of long-chain and short-chain PFAS aqueous solutions. We use electrolytes with different ionic strengths to improve the PFAS foaming capacity and foam stability. Additionally, the correlations of PFAS air-water interfacial properties and their foaming properties are discussed.  

    

Bending Sensors Using Ionic Liquid Crystal Based on Oragnic Electrochemical Transistor

           In recent years researchers have been focusing on optimizing the semiconducting materials for organic electrochemical transistor. Organic electronics devices are promising devices in bioelectronics. The working mechanism of the OECTs depends on the injections of ions from the electrolyte into the organic semiconductor. Liquid electrolytes in OECTs are widespread, but there is a growing need for solid electrolytes since they can be easily integrated into wearable devices. Recently our group confirmed that ionic liquid crystal elastomers (iLCEs) can be used as solid electrolytes of flexible, substrate-free organic electrochemical transistors.[1]  Here we extend our studies to various ionic liquids and demonstrate that iLCE-based OECTs can also be used as sensitive bending sensors that is capable to distinguish the direction of the bending as well.  

    

Simulating the vibrant colors of polarizing microscopy images of liquid crystals

When viewed with crossed polarized optical microscope (POM), liquid crystals display vibrant colors and complex patterns that make them suitable for optical applications. The color patterns provide rich information for the intricate alignments and intrinsic optical properties of the liquid crystal molecules. While calculations of black and white images from single wavelengths using calculated director fields have been demonstrated, color images produced to date do not always make quantitative agreement with experiments. In this work, we extend the Jones matrix method to calculate the colored images from arbitrary director fields, and exemplify our method by simulating radial and bipolar droplets of 5CB. We compare simulation results to experiments of 5CB droplets of various sizes and alignments generated by microfluidic devices and vortex. The effect of elastic constants, refractive indices and particle geometry are discussed. Our results provide a powerful way of quantitatively comparing POM images from experiments and the director fields from simulations, thereby paving the way for the inverse design of materials with internal microstructure.

    

Multistable Elastic Pixels based on Nematic Colloids for Reconfigurable Metasurfaces

Metamaterials are engineered to modulate incident electromagnetic (EM) waves in novel ways. We are developing a versatile approach for reconfigurable metasurface design where reversible changes between device states correlate to significant changes in EM response. Our approach relies on multistable elastic pixels (MEPs) which are discrete nematic liquid crystal (NLC)-filled structures containing colloids whose positions are controlled by the NLC elastic energy landscape. MEPs have two or more well-defined elastic energy minima, which correspond to stable colloid positions, separated by significant energy barriers. Once stably placed, a colloid can be repositioned to another stable location by the application of an external electric or magnetic switching field. Upon removal of the switching field, the system will persist in the new stable state. Colloids will serve as scatterers; hence, metasurfaces with judiciously placed MEPs will have strong changes in EM response upon colloid repositioning. Colloids can be returned to their original locations by reversing the switching field; thus, changes in the EM responses are reversible. We design MEPs to generate complex director fields and defect interactions that define colloid multistable sites and energy barriers between them.   

Optical modulation of cholesteric structures using microfluidics

Materials that produce color changes in response to stimuli are interesting for applications such as sensing and camouflage. Cholesteric liquid crystals are a unique class of soft materials as they exhibit self-assembled helical structures sensitive to various external stimuli and are known for their selective light reflection. Their response to pressure-driven flow in microfluidic channels has however remained experimentally unexplored. Here we study a cholesteric system that has a helical pitch comparable to the wavelength of visible light and can therefore exhibit structural coloration. Before the application of flow, the color of the cholesteric phase is independent of temperature but after flow alignment a blue-shift is observed upon increasing temperature. New cholesteric textures are created in flow. We observe that flow creates stable-colored bands, which remain stable for months. Our work identifies a strategy to generate stimuli-responsive materials in low volume. The flow-structure relationships revealed by our study could be relevant to applications such as additive manufacturing of LCs which involve manipulating these fluids in microchannels.   

Spectrally Dependent Electro-Optics of Polymer-Dispersed Liquid Crystals

Recent advances in the development of new materials for smart windows applications revitalized the field of polymer-dispersed liquid crystals (PDLC). An opaque state of polymer-dispersed liquid crystals can be switched to a transparent one by applying an external electric field. As a rule, electro-optical characterization of polymer-dispersed liquid crystals is caried out using a monochromatic light source. From perspectives of smart windows applications, it is critical to study the dependence of electro-optical response of PDLC samples on the wavelength of light. In this report, we present the results of systematic studies of spectrally dependent electro-optics of polymer-dispersed liquid crystals.   

Linear and quadratic electromechanical effects of a room temperature ferroelectric nematic liquid crystal

The lack of centrosymmetry of the ferroelectric nematic (N_F) liquid crystal phase enables both linear (piezoelectric) and quadratic (electrostriction) electromechanical couplings. Here we report measurements of AC electric field induced mechanical vibration of a room temperature ferroelectric nematic liquid crystal mixture using a lock in amplifier and accelerometer. Mechanical vibrations were detected both at the base frequency (linear piezoelectric signals) and at double frequencies (electrostriction).  The signals are correlated with the alignment properties of the director and a theoretical model is proposed to explain the observations.   

Marangoni convection driven by temperature gradient in cyanobiphenyl liquid crystals

Drastic changes in surface tension σ near phase transition temperatures have been reported in cyanobiphenyl liquid crystals (CBLC) [1,2]. According to the reports, however, σ largely depended on the measurements, and hence the precise value of σ in such systems might not be determined. In this study, the Marangoni convection driven by surface tension gradient was paid attention to. The strong flow is expected to be induced in CBLC systems owing to the drastic change in σ near phase transition temperatures. CBLCs from 5 to 8CB were prepared with fluorescence dyes dispersed. Under temperature gradient, the flow field in these LCs was measured by fluorescence photo-bleaching method [3]. On the basis of our measurements, we have successfully observed the strong flow induced in the coexistence state between the nematic (N) and isotropic (I) phases. Furthermore, near air interface, the flow from I- to N- phase was observed in 5CB, while the opposite flow direction was observed in 7CB. These flows are considered to be driven by the surface tension difference between the N and I phases in each sample. [1] M. Tintal, et al, Liq. Cryst., 28, 793, 2001. [2] L. S. Gomes and N. R. Demarquette, Mol. Cryst. Liq. Cryst., 437, 181, 2005. [3] J. Yoshioka, et al, Phys. Rev. E, 105, L012701, 2022.   

Phase transitions and structural changes of ionic liquid crystals in nanopores

Ionic liquid crystals (ILCs) are ionic liquids including liquid crystal molecules, and hence ILCs show interesting phase transition behavior. In our previous study, 1-methyl-3-alkylimidazolium and tetrauoroborate ([C_nmim]BF₄), by using various experimental techniques. In this study, DSC, X-ray and dielectric measurements were performed to clarify phase transitions of ILCs confined in nanopores. For the heating process from the highly-ordered smectic phase, DSC together with X-ray scattering measurements on [C₁₂mim]BF₄ clearly show that the phase transition behavior in this system changes depending on the pore size as follows: For pore sizes larger than 160 nm, during the heating process from highly ordered smectic phase, ILC melts at ca. 3 deg C and immediately starts to crystallize. Then, they transform to the Sm phase at ca. 28 deg C after a transition to another crystalline phase. For pore sizes less than 40 nm, the phase transition near 3 deg C is shifted to ca. -3 deg C, and no thermal anomaly is observed near 28 deg C. The X-ray pattern also shows a change from the highly ordered smectic phase, where there is a broad peak at q = 2.2 nm^-1, into another phase at -3 deg C, then a wide-angle ordered pattern changes to only a broad amorphous halo at about 15 deg C. In the presentation, we will discuss in detail the structural changes associated with the phase transition in ILCs in nanopore, together with the results of dielectric measurements.   

Optical spectra of hybrid cholesteric elastomers doped with metallic nano-ellipsoids.

We consider a hybrid system composed of a cholesteric elastomer doped with metallic nano-ellipsoids of different materials. One of the semi-axes of the ellipsoidal nanoparticles is aligned parallel to the helical axis of the host cholesteric medium. We calculate the effective dielectric tensor by using a generalization of the Maxwell–Garnet formalism for uniaxial media with low birefringence. We use this approach to obtain the co-polarised and cross-polarized transmission and reflection spectra of circularly polarized light of both handednesses impinging the sample normally. We obtain these optical spectra versus the constituent parameters of the ellipsoids (size of its semiaxes) forming the guest medium and the strain parameter of the host elastomer medium   

Anchoring effects on the propagation of modes in a blue phase cylindrical fiber

Normal linear propagating modes within a cylindrical wave guide filled with a blue phase liquid crystal are studied. This system is surrounded by a dielectric cladding and it is submitted to soft anchoring boundary conditions. iThe axis of the two dimensional helical structure of the blue phase is taken parallel to the cylindrical

wave guide axis.

The presence of the blue phase is characterized by the equilibrium equations for this texture resulting from the minimization of the free energy density. Alongside with these, Maxwell's equations under the presence of a blue phase are considered and the coupled governing equations are written and solved. 

With this, it is possible to obtain blue phase configurations parameterized for different anchoring energies from which the band structure and electromagnetic fields associated to these textures are calculated.   

Emerging Topological Structures in Nematic Moiré Patterns

Topological defects are of fundamental interest to soft matter physics, particle physics, and mathematics. In liquid crystals, they are also of practical importance in sensing, photonics, and directed self-assembly of colloids and molecules. Rational design of topological defects with arbitrary morphology and periodicity could enable more practical applications of topological defects, which remains a challenge to date. Inspired by the moiré pattern, here we combine simulations and experiments to study nematic liquid crystal cells confined by two identical surface patterns. By a mechanical twist, we observe a rich variety of highly tunable, novel topological structures, which are sensitive to system geometries; the corresponding cross-polarized images are distinct from isotropic moiré patterns. Simulations also show that the Frederiks transition voltage is approximately 10% lower in nematic moiré patterned cells than in conventional planar twisted cells. As such, the proposed simple mechanical twist method shows the promise of designing and tuning arbitrary, external-field-responsive, mesoscopic structures and optical patterns in liquid crystals and beyond, which can facilitate applications in defect-templated self-assembly, display, imaging, and photonic devices.

    

A highly sensitive fluorescent sensor for ammonia detection based on aggregation-induced emission luminogen-doped liquid crystals

As a toxic substance, ammonia can cause serious irritation to the human respiratory system and lungs. Although many detection techniques have been reported, most of them have drawbacks, such as expensive devices and complex and time-consuming fabrication processes. Thus, it is important to develop a simple method for ammonia detection. In this paper, we demonstrate a highly sensitive fluorescent sensor for ammonia detection based on aggregation-induced emission luminogen (AIEgen)-doped liquid crystals without the use of polarizers. The homeotropic orientation of the liquid crystals (LCs) on a modified substrate can be disturbed by ammonia, resulting in the fluorescence intensity change of AIEgen. This AIEgen-doped LC-based fluorescent sensor for ammonia detection exhibited a low detection limit of 5.4 ppm, which is 3 times lower than previously reported LC-based optical sensors. The detection range is also broad from 0 ppm to 1600 ppm. Meanwhile, this sensor can be applied to detect aqueous ammonia with a low limit of detection of 1.8 ppm. The proposed fluorescent sensor for ammonia detection based on the AIEgen-doped LC is highly sensitive, highly selective, simple, and low cost with wide potential applications in chemical and biological fields. This strategy of designing a liquid crystal fluorescent sensor provides an inspiring stage for other toxic chemical substrates by changing specific decorated molecules.   

Rheology of soapy formulations

Commercial liquid hand soaps and body washes are rheologically complex fluids with additives that influence smell, color, viscosity, phase behavior, and overall consumer’s sensory experience when dispensing or pumping onto the hand, body, or sponge.  Surfactants are a main ingredient in all commercial hand soaps with concentrations high enough for the formation of wormlike micelles.  They often exhibit shear banding properties and elastic instabilities that affect the flow behavior with different shear flows and extensional flows.  In this contribution, we characterize the shear rheology response of commercial hand soaps and body washes using torsional rheometry and characterize the pinching dynamics and extensional rheology using dripping-onto-substrate rheometry protocols.  In order  to better understand the connection between rheological studies and consumer sensory experience and satisfaction, we are developing non-standard characterization approaches to rank and analyze such products.

     

Effects of thermal cycling rate on the glass transition behavior of Choline chloride and ethylene glycol deep eutectic solvent mixtures

Deep eutectic solvents (DESs) are a class of mixtures with the potential to serve as designer materials, and substitute for conventional organic solvents used in a wide variety of applications.  The eutectic behavior of these mixtures has been explored in some depth, but the characteristic tendency of these materials is to behave contradictory to ideal, anticipated behavior. Therefore, experimental analyses are paramount to understanding the molecular dynamics of these materials. In this work, we have assessed a series of DESs using incremental compositions of Choline chloride (ChCl) and Ethylene glycol (EG). We have explored the rate dependence of glass phase transitions in these ChCl:EG mixtures using differential scanning calorimetry by quantifying the impacts of thermodynamic kinetics. The supporting evidence demonstrates that thermal cycling rate significantly affects glass transition temperatures, suggesting the importance of defining rate-independent transition temperatures for these mixtures.

    

Role of Solid-Solid Transitions of Choline-Halides on Deep Eutectic Solvents

Deep eutectic solvents (DESs) are a cheap, renewable, and versatile cousin of ionic liquids. DESs form via the eutectic point depression between binary mixtures of suitable constituent compounds. Choline halides are the most common HBA constituent in most DESs. Complete phase diagrams reveal insights to the formation of DESs. Choline-halide based DESs show melting transitions around the solid-solid (s→s) transition temperature of ChX + HBD compounds. This effect suggests deeper ties to the phase behavior, as this ultimately dictates the eutectic composition and temperature of resulting DES combinations utilizing choline halides as a constituent.

    

Using polymers to direct the self-assembly of complex liquid crystalline phases

While the anchoring of simple liquid crystalline phases, such as nematics, is well-understood, alignment of complex liquid crystals such as blue-phases and discotics is more challenging. We present here two methods to align complex liquid crystalline phases, namely chemo and grapho-epitaxy. These techniques involve making chemical (chemoepitaxy) and topographical (grapho-epitaxy) patterns using nanolithography. Chemo and grapho-epitaxy are well established techniques in the field of block copolymers. We present here extensions of these techniques for assembly of liquid crystalline phases. We demonstrate how directed self-assembly of blue-phase and discotic liquid crystals can be used to prepare polymeric photonic single crystals and biaxially textured crystals of organic semiconductors, respectively.

    

Orientational behavior of particles in self-assembled crystalline states of hard polyhedra

Hard particles are good models of self-assembly, can produce rich phase behavior in self-assembled states in terms of translational and orientational configuration of particles. These can form liquid crystals, plastic crystals (which exhibit long range translational order but complete orientational disorder), different types of complex crystal structures and even disordered structures in entropy driven self-assembly. In spite of having translational symmetry breaking present in the self-assembled states, different types of orientational configurations can occur in the system i.e. complete orientational disordered states i.e. plastic crystals, complete orientational ordered states and orientational glass phase where few particles are ordered and others are disordered, independent of the system length scales. We report these three kinds of orientational configurations in crystal phases in NPT Monte Carlo simulations for both sharp and sphero polyhedra (polyhedra with rounded vertices). In spite of having more rotational entropy in sphero shapes, rather than their underlying sharp shapes, we found the robustness of self-assembled structures and the existence of different kind of orientational states present in the systems. We predict a direct correlation between the shape attributes of the building blocks and the occurrence of the different kinds orientational states in self-assembled crystalline structures which can be used for material designing.

    

Fabrication and assembly of thin microgel particles with controlled curvature

Microgels are soft colloids that consist of polymer networks swollen in an aqueous solution. Such particles display a dual colloid-polymer nature that can be made responsive to stimuli such as pH and temperature. To date, studies on assembly of responsive microgels have been focused almost entirely on spherical geometries. In this work, we explore the assembly of multilayer, anisotropic microgels of rectangular shapes. These building blocks are fabricated with photolithography, and the inclusion of multiple layers within the particle in addition to various processing conditions allow us to control particle curvature due to swelling differences across layers. Using depletion interactions, we investigate curvature- and shape-dependent interactions in the assembly of these microgels. Finally, we study the effects of shape-morphing on final assembly structures, taking advantage of the microgel responsiveness to temperature and pH.<!-- This part is a little more aspirational than I usually aim for, unless there are recent results I haven't seen yet. I am OK with it, especially for a poster, in that presumably you will have at least something to show along these lines, but could consider softening a little bit --> Our findings are expected to guide the design of complex particle shapes to control assembly of responsive microstructures.

    

Dynamic Energy Transfer Between Polymer Nanocomposites in Supramolecular Microbeads

Bioinspired materials have proven to be effective platforms for the investigation and understanding of complex biological processes such as cell signaling, communication, and catalysis. Short-chain amphiphilic block copolymers (ABCs) have been shown to self-assemble photonic cofactors into nanocomposites mimicking photosynthetic light-harvesting and energy transfer with remarkable efficiency. We will present research that advances upon intra-nanocomposite energy transfer, toward dynamic, inter-nanocomposite energy transfer in supramolecular assemblies. Photonic ABC nanocomposites are organized in alginate microbeads using microfluidics approaches. Herein, we will report on developments toward dynamic, supramolecular energy transfer in alginate-polymer multi-scaled composites; particularly on abilities to: 1) create monodisperse alginate microbeads; 2) control organization of ABC nanocomposites inside alginate microbeads, and; 3), demonstrate inter-nanocomposite energy transfer. Composites and assemblies are characterized via fluorescence microscopy and spectroscopy, atomic force microscopy, and electron microscopies. These studies are designed to be proof-of-principle in developing robust, multi-scaled, supramolecular materials capable of dynamic cell-like communication.   

Self-assembly of nanocubes directed by surface and magnetic interactions

We study the stabilization of clusters and lattices of cuboidal particles with long-ranged magnetic dipolar and short-ranged surface interactions. Two realistic systems were considered: one with magnetization along the crystallographic direction [001] and another with magnetization along the crystallographic direction [111]. To explain the structural genesis of low energy configurations, we first studied magnetic nanocube clusters at 0 K and then analyzed their behavior at a finite temperature. Our results demonstrate that dipolar coupling can stabilize nanoparticle assemblies with cubic, planar, and linear arrangements seen previously in experiments. While attractive surface energy supports super cube formation, repulsion results in elongated structures in the form of rods and chains. We observe the stabilization of the ferromagnetic planar arrangements of the cubes standing on their corners and in contact with the edges. We illustrate that minimal energy structures depend only on the size of the assembly and the balance of surface repulsion and magnetic dipolar coupling. The presented results are scalable to different particle sizes and material parameters.   

Defect self-propulsion in active nematic films with spatially-varying activity

We study the self-propulsion of topological defects in an active nematic system with spatially varying activity, and consider the two limits of a constant activity gradient, and a sharp jump in the activity. For an activity with a constant gradient the self-propulsion velocity of the +1/2 defect becomes proportional to the local activity in the same way it is for a constant activity. A finite vorticity is induced at the defects core, which drives the defect to align its polarization with the direction of decreasing absolute activity, so that it will start moving in the direction that lowers its self-propulsion velocity. The constant activity gradient does not make the -1/2 defect motile and it does not pick up a preferred orientation. A sharp jump in the activity affects the translational and rotational motion of both defects. The positive defect slow down when it approaches the interface and an induced vorticity tends to reorient it so that the defects polarization becomes perpendicular to the interface. The -1/2 defect becomes self-propelled close to the wall and a finite vorticity is induced that tends to align the defects in a preferred orientation. The negative defects that has the prefered orientation is attracted by the interface.        

    

Probing microtubule-kinesin active matter in a low activity regime

Countless living systems exhibit complex behaviors driven by the spontaneous self-organization of their constituents. The dynamics of these systems occur far from equilibrium and often rely on the localized consumption of biological energy sources. In this work, we leverage kinesin-driven microtubule networks as a simple experimental system to quantify non-equilibrium material behaviors. By limiting kinesin-motors' access to energy-rich ATP, we tune the activity of our reconstituted ensembles, allowing us to probe the transition between fluidized and elastically gelled protein suspensions. We observe that our system's dynamics depend non-trivially on ATP concentration and can be further tuned by varying an incorporated ATP regeneration backbone. Together, these observations lend a new perspective on the energy-consuming protein interactions that drive emergent non-equilibrium flow in active materials.   

Active Ornstein-Uhlenbeck particles: a versatile model for self-propelled motion

Active Brownian Particles (ABPs), characterized by a constant self-propulsion velocity along the current orientaion, are commonly perceived as the standard model for dry active motion. As an alternative, Active Ornstein-Uhlenbeck Particles (AOUPs) model the persistent motion through a Gaussian process, which is particularly appealing in view of calculating exact solutions and developing approximate theories, and are thus sometimes perceived as an approximation to ABPs.

Here, we introduce a parental active model (PAM) based on a general stochastic process with fluctuating self-propulsion velocity, within which both ABPs and AOUPs emerge as limiting cases, i.e., they are rather sisters than cousins. We then demonstrate that a position-dependent swim-velocity field can be consistently introduced for any self-propulsion mechanism. As an application, we discuss the effects of varying self propulsion in external confinement and predict the stationary properties using effective interactions.

Both ABPs and AOUPs have been originally developed to model the overdamped dynamics of microscopic active particles. However, the recent interest in macroscopic active systems generates the need to develop manageable theoretical descriptions of inertial effects. For AOUPs with translational inertia we provide exact analytical solutions for dynamical correlation functions considering an active dimer, a time-dependent mass and various external forces. Finally, we discuss effects of rotational inertia.   

Diffusion Estimation via Particle Tracking with Vernier-like Time Sampling

Over the last two decades, particle tracking has become an essential technique for the analysis of diffusion processes and soft material properties. Much of this work has relied on time series data captured at fixed frequencies with speeds that are limited by the camera used. Here we present a flexible imaging scheme that generates time series with a Vernier-like structure. This scheme is analogous to the method used in Vernier calipers to achieve high precision length measurements. Two cameras acquire data at frequencies f₁ and f₂ with a frequency difference a = f₁ - f₂. These acquisitions are partially synchronized so that simultaneous exposures occur every 1/a seconds. The inter-camera exposures then exhibit a controlled desynchronization and produce a uniquely structured set of statistically independent lag times. In applications that investigate time independent processes, such as diffusion estimation and microrheology, these time series offer efficient access to data with a large field of view, wide dynamic range, with peak frequencies well in excess of f₁ and f₂.  Our poster will describe the properties of the Vernier time series, its impact of data acquisition and analysis, and experimental results for particle diffusion in glycerol-water solutions.

    

A Unified Procedural Graph for Metamaterial Design

We introduce a compact, intuitive procedural graph representation for the full spectrum of mechanical metamaterials. The "architecture" of each metamaterial may contain elements such as trusses, curved beams, thin shells, or solid bulks. However, it is challenging to explore these diverse architectures using existing representations. Generic approaches like voxel grids are versatile, but representing and editing any individual structure is cumbersome. Architecture-specific representations address these issues, but are generally incompatible with one another. We propose a unified procedural graph that succinctly represents the construction process for any structure using a simple skeleton annotated with spatially-varying thickness. By extending this design philosophy to all architectures, we greatly expand engineers' capacity for exploration. To demonstrate the expressiveness, accuracy and efficiency of our representation, we recreate a wide range of established structures. We also show that random searches over our representation can efficiently produce large collections of novel structures with promising material properties.   

Staticaponics: Water and Nutrient Delivery for Plant Growth by Electrostatic Deposition

Electrostatic deposition (ESD) is a targeted liquid deposition method that requires a high electric potential to atomize a solution flowing through a conducive nozzle, resulting in a fine spray of charged micro-droplets. In ESD, the emitted droplets result from the electrostatic breakdown from an electrostatically drawn Taylor cone. The droplets undergo Coulombic fission that decreases the ratio of the electric charge to the surface area, resulting in a monodisperse spray. The electric field directs the droplets to the rooting media and due to the large surface tension of water relatively high voltages can stabilize the spray. However, using high voltages can lead to unwanted corona discharge. Fortunately, liquids with higher electrical conductivities can be sprayed easily using electrostatic deposition. We demonstrated that a plant nutrient solution increases the conductivity sufficiently to produce an acceptable spray. But we needed to remove the electrical charge from the delivered nutrient solution droplets to prevent damage to the plants. By separating the current from the nutrient water flux, staticaponics proved to have a higher water use efficiency than traditional hydroponic or aeroponic growing techniques.   

Influence of Multivalent Ion Clusters on Composition and Viscoelasticity of Polyelectrolyte Complexes

Polyelectrolytes (PEs) are water-soluble charged polymers. Complexation between two oppositely charged PEs, driven by electrostatic interactions, leads to phase separation into complex (polymer-dense) and supernatant (polymer-lean) phases. The extent of complexation and phase separation is dictated by solution conditions and the nature of the PEs. PEs are utilized in various applications – water treatment, adhesives, cosmetics – in which they are exposed to monovalent (Na⁺, K⁺, Cl^-) and multivalent ions (Ca²⁺, Al³⁺, SO₄^2-). We have demonstrated that replacing divalent ions reverses the phase composition of PE complexes leading to greater retention of divalent ions in the complex phase. This behavior, in contrast to monovalent ions, led to changes in the viscoelastic properties of these divalent ion-PE complexes. In this poster, these contrasting observations for monovalent and divalent ion-PE complexes will be harnessed to tune the physical (composition, salt resistance) and viscoelastic properties of PE complexes, in the presence of a combination of monovalent and multivalent ion clusters. A combination of thermal degradation and rheology investigations will be adopted to study the evolution of the behavior of PE complexes with increasing ionic strength.

    

Phase Composition and Viscoelasticity of Non-Ideal Polyelectrolyte Complexes

Polyelectrolyte (PE) complexation is driven by electrostatic interactions between oppositely charged macromolecules in solution. The extent of complexation and properties of the complexes are influenced by a combination of the solution conditions under which complexation occurs (pH, ionic strength) and properties of the charged PEs (degree of ionization, molecular weight, chemistry). Experimental studies investigating phase behavior and rheology of polyelectrolyte complexes (PECs) have been performed with ideal systems, with well-controlled properties. However, in fields where PEs are utilized (biological systems, water treatment), the solution conditions and PE properties are non-ideal.  Previously, we noted that the phase composition of divalent salt-PEC systems stood in stark contrast to oft-studied monovalent salt-PECs. This manifested as a non-monotonic evolution in shear moduli with increasing divalent ion concentration. In this poster, we discuss the effects of non-idealities in PEs on the phase compositions of the PECs. Additionally, changes in PE properties will be shown to influence the shear response of PECs. Finally, the effect of ionic strength, in combination with non-idealities in PEs will be shown to influence the physical and shear properties of the PECs.

    

Sequence-(in)dependence protein-mimetic polymer

A new class of MMA-based random heteropolymers (RHPs) have displayed protein-like properties in an ensemble manner. Using atomistic molecular dynamics simulation, we have shown that the chain collapsed into globules with a weak sequence control. In this work, we find the sequence for MMA-based random heteropolymers do not contribute to the statistical properties of the monomers with different chemistries. However, this changes dramatically when we substitute the MMA backbone by a methacrylate (MA) backbone or by simply replacing the oxygen atom on the side chain with a nitrogen atom (methyl methacrylamide, MMAn or methacrylamide, MAn). In such a scenario, we find that the sequence is significant for the overall structure of the random copolymer. We apply the dimensionality reduction on the hydration of each monomer and find that in the case of MA and MAn/MMAn backbones, different sequences do not share any common space, meaning their properties are controlled by their sequence and not the composition which is maintained fixed. The sequence-independence of MMA-based RHPs provide a paradigm for protein-mimetic materials. 

    

Controlled assembly of covalent-supramolecular peptide ‘bundlemer’ nanostructures

Computationally designed peptides that are 29 amino acids in length could self-assemble into stable antiparallel, homotetrameric coiled coils in the water. These coiled-coil peptides, or ‘bundlemers’, have great potential to serve as fundamental building blocks to construct well-defined nanostructures. By tuning bundle surface-exposed functional groups and peptide termini, various natural and non-natural physical and covalent inter-bundle interactions can be introduced for nanostructure formation. The building blocks can be ‘click’ conjugated together to form a 1D physical-covalent hybrid supramolecular polymer. Herein, we focus on novel ladder-like covalent-supramolecular hybrid polymers by clicking together end-functionalized bundlemers with complimentary side-functionalized bundlemers. Constituent peptides with different designed net charges under different self-assembly and conjugation conditions have been studied. Additional designs discussed include bundlemers used to construct branched fibers and 2D peptide networks. Peptide design will be discussed as well as transmission electron microscopy, atomic force microscopy, and small-angle x-ray scattering results characterizing the ladder and 2-D nanostructures.

    

Force fluctuations in an active enzyme bath

Optical tweezers have allowed the quantitative study of piconewton-scale forces in many biological systems. An interesting recent example is active colloids constructed from urease attached to passive particles in a urea bath – which exhibit enhanced diffusion and measurably increased force fluctuations. In this study, we measure the force fluctuations of a physically different situation – a passive colloid (r=0.5um) immersed in an active enzyme bath composed of freely diffusing urease and urea. The concentration of urease is varied from 0-100U/mL. We find that despite the high concentration of urease, no enhanced force fluctuations are observed – perhaps due to the separation of length scales between the passive colloid and individual active enzymes. To test this, we decorate streptavidin-coated particles with a urease-biotin complex and measure their force fluctuations in a urea bath. These experiments set the stage for understanding the energetics of enzyme-propelled active matter.   

Volatile Solvent Free Styrenic Block Copolymer Based Pressure Sensitive Adhesive using Organic Eutectic Liquid

Styrenic block copolymer based pressure sensitive adhesives (PSAs) are commonly used from daily life to industry. Coupled with increasing environmental issues, there are tremendous demands for environment-friendly PSA development. In this poster presentation, a non-volatile and non-toxic organic eutectic liquid (EL) was developed as a substitute of both volatile organic diluent and toxic tackifier, which are conventional components of PSA. Substituting the EL for diluent and tackifier not only eliminates many disadvantages of conventional PSA such as use of toxic and volatile components but also simplifies the manufacturing process by excluding solution casting and solvent recovery steps. Moreover, upon incorporating EL into the poly(styrene-butadiene-styrene) block copolymer, increase in storage modulus at low temperature (high frequency) and decrease in glass transition of styrene end block at relatively high temperature (low frequency) were resulted. These facts indicate the EL helped the PSA to be especially suitable for conditions bearing high shear rates.   

Wet Adhesion Characterization of Hydrogel Sealants

Hydrogels – crosslinked polymer networks – are attractive candidates for medical applications such as wound dressing. Gelatin methacryloyl (GelMA) is a model biopolymer employed as a bioadhesive due to its similarity to native extracellular matrices, and it can be covalently crosslinked upon exposure to ultraviolet light, which results in robust mechanical stiffness. However, GelMA has weak mechanical strength before crosslinking, leading to undesired flows and dilution. We propose to overcome the low mechanical strength of GelMA by incorporating oppositely charged block polyelectrolytes (bPE) that self-assemble ionically when mixed, resulting in higher mechanical robustness prior to photocuring. To quantify the adhesive properties of the system, a burst pressure apparatus used to measure the maximum pressure that the hydrogel can sustain. We employ versatile testing in dry and underwater environments to study the adhesion in physiological conditions. The incorporation of bPE prevents dilution and enables wet adhesives that can withstand burst pressures up to 8 kPa. This work combines the fabrication of model interpenetrating polymer networks and bioadhesion testing protocol, which provides a model study for other polymers relevant in wet adhesion.   

Electrochemical potential enables dormant spores to integrate environmental signal

The dormant state of bacterial spores is generally thought to be devoid of biological activity. We show that despite continued dormancy, spores can integrate environmental signals over time through a pre-existing electrochemical potential. Specifically, we studied thousands of individual Bacillus subtilis spores that remain dormant when exposed to transient nutrient pulses. Guided by a mathematical model of bacterial electrophysiology, we modulated the decision to exit dormancy by genetically and chemically targeting potassium ion flux. We confirmed that short nutrient pulses result in step-like changes in the electrochemical potential of persistent spores. During dormancy, spores thus gradually release their stored electrochemical potential to integrate extracellular information over time. These findings reveal a decision-making mechanism that operates in physiologically inactive cells.   

Domain Morphology and Rheological Properties of Protein-Polyelectrolyte Complex Hydrogels

Polyelectrolyte complex (PEC) hydrogels are physically-crosslinked three-dimensional (3D) polymeric networks that electrostatically self-assemble from two oppositely-charged ABA polyelectrolytes. The associative microphase separation of the A-blocks (limited by the B-blocks) results in polymer dense domains within a 3D network that are responsible for the unique physical and mechanical properties of PEC hydrogels, such as their ability to encapsulate charged macromolecules. Previous research has demonstrated a relationship between PEC domain morphology and the mechanical properties of PEC hydrogels, but data on how protein additives affect that relationship is still unknown. In this poster, we use small-angle X-ray scattering to determine the domain morphology of protein-PEC hydrogels and use rheology to uncover how protein additives affect the shear properties of PEC hydrogels. This work establishes basic design criteria for moduli-tunable, biomedically relevant protein-PEC hydrogels.   

Active Particles in Polymer Networks Model Bacteria Behavior in Biofilms

Bacteria exert a hydrodynamic swim stress that present methods for infiltration and break up of biofilms, which are a large issue for medical device cleanliness. Active synthetic matter has also been shown to generate enough stress to drastically modulate the shape of a lipid membrane via tuning of the particle speed and membrane tension. We use active synthetic particles in a hydrogel to mimic the effect bacterial motion has on biofilms to better understand mechanisms for eradicating bacteria. Active platinum Janus particles are swollen with water and hydrogen peroxide fuel into a 4arm-PEG hydrogel that has either permanent (thiol-maleimide) or dynamic (boronic ester) crosslinks. By tuning the lifetime and permanence of the crosslinker, the swim ability can be dictated. In addition to biofilm elimination, this model active network exhibits a novel approach for polymer architecture design. Controlling the motion of the active particles during gelation could create pores for drug delivery or channels for ion conduction. Time-resolved rheometry is used to understand the viscoelastic changes made to the material and particle motion. Additionally, a novel microrheological magnetic tweezer setup is used to investigate the local scale properties of motion and crosslinker lifetimes.   

Relaxational dynamics of the size interconversion of virus capsids

Recent experiments show that a modified coat protein of a simple icosahedral plant virus forms capsids of different sizes, or T-numbers, under different solution conditions, and that by changing the solution conditions one T-number can be converted into the other albeit that the kinetics of the process is rather slow. We apply a simple relaxational model that ignores the impact of any nucleation barriers, and finds a reasonable agreement between theory and experiment with a minimal number of adjustable parameters. We conclude that following a sudden change in pH or salinity, and starting off from a solution dominated by one of the T-numbers, the initial response must be driven by an increase in mixing entropy giving rise to a mixture of sizes. In the late stages, the impact of minimizing the binding free energy kicks in and the solution relaxes to thermodynamic equilibrium. We find that the concentration of free protein subunits, or dimers, relaxes very swiftly and that their concentration remains virtually constant for most of the T-number conversion.   

A Manifold Minimization Principle for Physical Networks

A physical network is not only a combinatorial object, a graph of nodes and links, but also a geometric object that is best described as a smooth manifold, a "morphologically shaped" intrinsic d-dimensional space that is locally smooth everywhere. Inspired by string theory, we find that a graph can indeed be promoted to a smooth manifold when d≥2, by adding extra degrees of freedom that minimally describe the geometry of individual physical links (e.g., geodesic length and twist) and nodes (e.g., how links are sewed to each other). This manifold-based description further gives rise to a general manifold minimization principle for the formation of physical networks, minimizing not only the wiring length of all links (cf. the Steiner problem) but also other physical d-measures such as surface area or volume of the manifold. However, we show that in order to maintain the transportational functionality of each physical link, such d-measures cannot be minimized without constraint. Focusing on d=2, we introduce a systolic surface minimization scheme that keeps the shortest circumference (i.e., the systole) of each physical link fixed, finding that the solution predicts two novel structural transitions: a transition from bifurcation to trifurcation and a transition from sprouting-like bifurcation to branching-like bifurcation. Both transitions occur at finite length-systole ratios of the physical links and are forbidden by the Steiner solution, yet often observed in real biological systems, the transition thresholds agreeing with theoretical predictions. Our results reveal the inherent limitation of describing network geometry by shapeless 1D wires only, indicating a much richer geometry that pertains to the formation of manifold-described physical networks.   

Fluctuations in layered complex networks

Layered networks represent a natural extension of the successful complex network theory. They aim to model additional structure in the coupling and to account for

interdependent systems such as functional brain networks or coupled voltage levels in electric power grids. The latter are typically subjected to external perturbations or a

noisy environment, which, on the long run might damage some of the system components or, in extreme cases, drive the system through transitions between different fixed

point. Therefore, it is of primal importance to understand how perturbations spread over such layered networks. With this task in mind, I investigate how noise injected in one

layer is transmitted to its dependent layers. Interestingly, I show that, for networks with low algebraic connectivity, fluctuations might be strongly amplified while going from one layer to another, eventually leading to major system failures.   

Developing a Neural Network (NN) model for Analysing Fractal images to Recognize Pareidolia Phenomenon

Pareidolia is the tendency to perceive a pattern, often a meaningful image in a random or accidental arrangement of shapes and lines such as seeing shapes in clouds, rocks, trees, etc [1]. These structures are fractal and display complex patterns that are statistically self-similar at different levels of magnification and show patterns at increasingly fine size scales [2]. Fractal patterns are common all over nature such as lightning, clouds, trees, rivers, and mountains.

In previous research in 2016 [3], it was asked of subjects to form perception from images of the computer-generated fractal. Participants were presented with fractal noise at different fractal dimensions and asked to imagine objects within the shapes. As the result, fractals with medium to low fractal dimensions tended to produce more noticeable pareidolia. This prior research inspired us to build a deep-learning-based model of pareidolia detection.

In the current research, our goal was to use Convolutional Neural Networks (CNNs) to mimic the results observed in human subjects' experiments [3] for pareidolia perception. The application of a CNN was motivated by the fact that they are able to learn relevant features from an image at different levels, similar to the different levels of receptive fields in the human visual system. In this regard, we attempted to build a model of a “pareidolia classifier” and in order to achieve an effective model, we had to combine classification techniques with some kind of generative component.

At the initial stage, we chose to synthesize data rather than work from an existing dataset. Because we were concerned with identifying the forms of objects, if we had worked with photographs, we would have needed to isolate every object from its background. Our approach to building object classes was to limit classes to a small number (15) and build synthetic datasets from many rotated views of 15 different 3D models. Since the fractal stimuli were black and white, we chose to create greyscale top-lit views of each 3D model, and then convert them to black and white. We used 3Ds Max to load, animate and render 15 different 3D models. The final dataset for this project contained fifteen 3D models, with 100 images for each.

Our method was to implement code that identified regions in the fractal stimuli with boundaries larger than a given size. These regions were then assigned bounding boxes and extracted to their own image files, where artifacts were cleaned up, and the images were prepared for use as testing data. Each region was then tested against the 15 object classes. Upon classification of a region as an object class, it was passed to a final stage, where it was tested against each of the 100 frames within the object class indicated in the prior step. After each region was assigned a specific frame within an object class, a new image was constructed from the fractal stimuli regions and their paired object images, and a composite of regions and object images was built. All of the testing models were pre-trained, which enabled the system to produce the composited pareidolia images in a matter of seconds.

The object class images served as the training dataset, and the fractal stimuli served as the testing dataset, with the intended goal of finding the “pareidolia” of our training data within the fractal images. In this iteration, the neural network was a simple classifier, looking for similar shapes within the fractal stimuli and the object class. We tested on stimuli from a range of fractal dimensions, starting at 1.1D (almost smooth) and moving toward 1.9D (noisy). While we will look at different architectures in the future, deep neural networks provide a useful analog for modeling biological neural processes, and CNNs are specifically relevant to the human visual system, as they mimic the function of receptive fields in the mammalian visual system.

In this project, we investigated a small range of deep computer vision possibilities but were able to achieve a primitive functioning model of human pareidolia, which is beneficial for future endeavors. Our generated results were somewhat homogeneous throughout different fractal images because we had only 15 object classes. But even with a small dataset, often the results were surprising. Sometimes for their randomness and sometimes for their accuracy. Because the more complex fractals have the more regions and so have the potential to assign more in the variety of shapes, higher fractal dimension objects produce both nonsensical and visually interesting results. As with human subjects' pareidolia, most of the ”cleanest” results were within the 1.1-1.4 fractal dimension range. For example, For the fractal dimension about 1.1 and 1.3 Usually we got around 5 or 6 object classes.  And as we re moving to a higher dimension (e.g. 1.7 or 1.9) then we got more results (about 20). In summary, for this project, we built a Convolutional neural network (CNN)-based “pareidolia classifier,” and added a generative component to the model using a python program function. Then ran our model successfully on a range of fractal stimuli images, from 1.1 D to 1.9 D. Our future goals include training the current model to address the positive and negative color fields. Moreover,  we will apply different neural network architectures, and further augmentation techniques (namely rotation, scaling, and skewing) to the training data, and additional partitioning techniques (e.g. instance segmentation) to cover a wider range of shape classification possibilities. As another speculative step, we would like to train generative models, where the fractals would be used as initialization seeds in a generative morph toward the training data they are paired with.

    

Author not Attending

In the process of transcription, translation, or self-replication of DNA or RNA, information is transmitted to the incipient species from its predecessor. These processes can be considered as (generalized) biological copying mechanisms as the newly formed biological bodies like DNA, RNA, or proteins represent the information of their parent entities uniquely. The correctness of these copying mechanisms is essential, since errors in the copied code can affect the functionality of the next generation. Such errors might appear from perturbations on these processes. Most crucial in this context is the temperature of the medium, i.e., thermal noise. Although a considerable amount of experimental studies have been done on this important issue, theoretical understanding is almost missing. In the current work, we describe a model study which can focus on the effect of the temperature on the process of biological copying mechanisms, as well as on mutation. We show that for our paradigmatic models, in a quite general scenario, the copying processes are most efficient at an intermediate temperature range; i.e., there occurs an optimum temperature where mutation is most unlikely. This allows us to explain the observations for some biological species with the help of our model study.

    

Author not Attending

The Hopfield neural network is a paradigmatic model for associative memory. In the standard model, only one memory can be recalled for a given initial state of the network. However, when asymmetric coupling between neurons is included, sequences and cycles of multiple memories can be recalled. For a symmetric Hopfield network experiencing thermal fluctuations, it has been shown that the recall of a single memory is improved by replacing the associated white noise with colored noise, which keeps the system out of equilibrium. Here, we show that this nonequilibrium condition also enhances the recall of a memory cycle in an asymmetric Hopfield network.   

The efficiency of a linear heat engine in contact with the active bath

Our experiment shows that an introduction of time-correlated Ornstein-Uhlenbeck (OU) noise to a stochastic heat engine can elevate engine efficiency beyond the Carnot limit set by classical thermodynamics. We adopt a Brownian gyrator as a model system in which a water-immersed Brownian particle is constrained in a two-dimensional harmonic potential and subject to distinct effective temperatures and nonconservative coupling forces in orthogonal axes. Proper choice of the coupling force strength allows the gyrator to harvest work from its environments, operating as a heat engine. Compared with a counter-passive heat engine, thermodynamics currents (work and heat rates) are enhanced. Moreover, under some specific coupling force strengths, engine efficiency goes beyond the Carnot limit with non-zero power. We will discuss the influences of OU noise on the trade-off relation between the fluctuations of thermodynamic currents and the entropic cost.   

Non-Equilibrium Statistical Physics Beyond the Ideal Heat Bath Approximation

Important models of nonequilibrium statistical physics (NESP) are limited by a commonly used, but often unrecognized, near-equilibrium approximation. Fokker-Planck and Langevin equations, the Einstein and random-flight diffusion models, and the Schnakenberg model of biochemical networks suppose that fluctuations are due to an ideal equilibrium bath. But far from equilibrium, this perfect bath concept does not hold. A more principled approach should derive the rate fluctuations from an underlying dynamical model, rather than assuming a particular form. Here, using Maximum Caliber as the underlying principle, we derive corrections for NESP processes in an imperfect - but more realistic - environment, corrections which become particularly important for a system driven strongly away from equilibrium. Beyond characterizing a heat bath by the single equilibrium property of its temperature, the bath's speed and size must also be used to characterize the bath's ability to handle fast or large fluctuations.   

Active cyclic Brownian information engines

Brownian information engines can extract work from thermal fluctuations by utilizing information. So far, the studies on Brownian information engines consider the system in a thermal bath; however, many processes in nature occur in a nonequilibrium setting, such as the suspensions of self-propelled microorganisms or cellular environments called an active bath. Here, we introduce a simple model for Maxwell-demon-type cyclic Brownian information engine operating in a Gaussian-correlated active bath. The active engine can extract more work than its thermal counterpart, exceeding the bound set by the second law of information thermodynamics. We obtain a general integral fluctuation theorem for the active engine that includes additional mutual information gained from the active bath with a unique effective temperature. This effective description modifies the second law and provides a new upper bound for the extracted work. Unlike the passive information engine operating in a thermal bath, the active information engine extracts colossal power that peaks at the finite cycle period. Our study provides fundamental insights into the design and functioning of synthetic and biological submicron motors in active baths under measurement and feedback control.

    

Community Composition in a Changing World: Using a Circuit Equation to Predict Invasion Dynamics

Ecological communities are often composed of multiple species competing for the same resources.  Traditional Lotka-Volterra models would predict survival of only the species with the highest fitness. However, migration from outside the system permits species with lower fitness to stably persist, allowing them to quickly proliferate when conditions become more favorable. Thus, understanding the basis for invasive species persistence in suboptimal environments is important for predicting ecological dynamics under climate change.

Using a simple Lotka-Volterra equation modified to include migration, we show that the fitness of a less-fit species can be solved for based on its steady state survival when migration occurs. The equation is analogous to that describing an electrical circuit, I=V/R with the current, I, equivalent to the migration rate, the inverse of resistance, 1/R, equivalent to the steady state population of the invader, and the volatege, V, equivalent to the difference in fitness between the resident and the less fit invader. 

Here, we test this prediction by invading a population of E. Coli with 20 different mutants with known fitness defects. 

The approach provides a predictor of steady-state community composition, a potential tool for measuring in vivo fitness in invasive populations,  as well as predicting populations with the potential to become invasive due to stochastic variation and climate change.

    

Nucleation rates of OPC3-water and SPCE/hw-heavy-water systems using Monte-Carlo simulations with the aid of the Bennett Acceptance ratio

Nucleation rates of the OPC-water model and SPCE/hw-heavy water model have been calculated using Monte Carlo simulations. The free energy has been calculated using the Bennett acceptance ratio. Our results of the calculated free energy in the range of 200-260K when plotted against the number of molecules raised to the power minus one-third is a straight line for clusters containing more than six molecules. The straight line plays a major role in calculating the surface tension and the vapor density. The surface tension of small clusters has been calculated from the slope of the straight line, while the vapor density has been calculated from the intercept. The nucleation rates have been calculated based on the estimated values of surface tension and vapor density. Our results show good agreement when compared with the experimental data of Wolk and Strey.   

Observable partitioning under uncertainty in information engines with physically implemented observer memories

Generalized partially observable information engines were introduced recently to study the physical foundations of information processing and decision making under uncertainty [PRL 124(5)050601, 2020]. In [NJP (24)073031, 2022], we analyzed the physical characteristics of observer memories that maximize average engine work output of a canonical example. Optimal memories cannot be achieved by coarse graining, but rather are nontrivial probabilistic (``soft") partitions of the observable. While our model was simple, the resulting physical rules for constructing the memories were complex.

Coarse graining is ubiquitous in physics, but soft partitions are not. Intuition quickly fails. Here, we present an even simpler model to build physical intuition, namely a parameterized version of the example given in [PRL 124(5)050601, 2020]. We find that the physical process governing optimal observer memories is indeed easy to understand. We also compare optimal memories to coarse graining and soft partition approximations, obtained via parametric optimization, which is computationally less costly. Soft partition approximations give better performance.

It is worthwhile thinking about whether this broadening of the scope of possible ways to partition the observable might have useful consequences for other physical models that rely on coarse graining.   

Modeling creep and strain relaxation as an anomalous diffusion-limited mixed 2nd order reaction

Relaxation dynamics of disordered systems can be modeled as a reaction process limited by diffusion. In the case of a mechanical relaxation of a polymer or glass, "reactant A" corresponds to a concentration of strained bonds, and "reactant B" corresponds to a concentration of energetic catalyst such as a diffusing void or phonon above a certain energy cutoff, which permits the strained bond to relax upon contact. When the limiting diffusion is anomalous, stretched exponential relaxations (Kohlrausch-Williams-Watts law) or power-law decays (Curie-von Schweidler law) can result. These slow relaxations have been observed in a wide range of cases including stress relaxation in polymers, conductivity in amorphous solids, photocurrent in organic and inorganic materials, and dielectric relaxation in glasses among others. A microscopic model that can describe the dynamics of both standard and anomalous diffusion is the continuous-time random walk theory (CTRW), whereby each step of the diffusive random walk is governed by a wait-time distribution function ψ(τ ) predicting the probability ψ(τ )dτ for the subsequent step to be taken within dτ of the wait time τ. Working from the CTRW framework, this work will fit both analytical expresions and stochastic simulations to experimental data of relaxation phenomena to elucidate the role that different CTRW parameters play in the resulting random walk and, in turn, the relaxation dynamics.

    

Accurately modeling supercooled liquids and granular materials across a wide range of spatial dimensions with hdMD

Much insight into the physics of materials has been gained by modeling them across multiple length and time scales.  Another approach that has proven particularly useful for glass-forming and granular materials is modeling them across multiple spatial dimensions d.  However, the very small (and d-dependent) system sizes employed in most previous studies of these systems in d > 3 raise doubts about the validity of these studies’ conclusions.  To help the glass/jamming community overcome this issue, we have developed a publicly available, open-source, parallel MD code called hdMD [Phys. Rev. E 105, 055305 (2022)] that works in arbitrary d and allows simulation of much larger systems.  This poster will highlight how hdMD can be used to obtain novel results, focusing on how the character of the Gardner transition deep within the glassy state and the character of stringlike cooperative rearrangements in moderately supercooled liquids vary over the range 2 ≤ d ≤ 6.   

Average outpouring velocity and flow rate of grains discharged from a tilted quasi-2D silo

The flow of granular materials through constricted openings is important in many natural and industrial processes. These complex flows – featuring dense, dissipative flow in the bulk but low-dissipation, low density outpouring in the vicinity of the orifice – have long been characterized empirically by the Beverloo rule and, recently, modeled successfully using energy balance [J. R. Darias, et. al., Phys. Rev. E 101, 052905 (2020)]. The dependence of flow rate on the silo's angle with respect to gravity, however, is not captured by current models. We experimentally investigate the role of tilt angle in this work using a quasi-2D monolayer of grains in a silo. Using a camera and scale composed of load cells, we measure mass flow rate, the average exit velocities of grains, and the packing fraction along the orifice with varying tilt angles during steady-state flow of grains. We compare our results with a simple model that takes into account the angle of stagnant zones adjacent to the orifice in steady-state flow. We conclude by posing questions about possible extensions of our model in order to describe spatial variations of exit velocity and density along the orifice.   

Inertial effects on entropic transport of active Brownian particles in an asymmetric channel

Micro- and nano-swimmers diffusing in a liquid solvent confined by structures where entropic barriers arise naturally are often described by overdamped active Brownian particle dynamics, where viscous effects are large and inertia plays no role. However, inertial effects should be considered for confined swimmers (termed micro- and nano-flyers) moving in media where viscous effects are no longer dominant. Here, we study how inertia affects the rectification and diffusion of self-propelled particles in a two-dimensional asymmetric channel. We show that most of the particles accumulate at the channel walls as the mass of particles increases. Furthermore, the average particle velocity has a maximum as a function of the mass, indicating that particles with an optimal mass $m_{op}$ can be sorted from a mixture with particles of other masses. In particular, we show that the effective diffusion coefficient exhibits an enhanced diffusion peak as a function of the mass, which is a signature of the accumulation of most of the particles at the channel walls. The dependence of $m_{op}$ on the rotational diffusion rate, self-propulsion force, aspect ratio of the channel, and effective torque is also determined. The results of this study could stimulate the development of strategies for controlling the diffusion of self-propelled particles in entropic ratchet systems.

    

Entropy production in active turbulence

Active particles like bacteria and sperm cells sustain continuous intake and dissipation of energy. Consequently, they are intrinsically out of equilibrium and lead to a non-vanishing entropy production rate (EPR) even in steady states. Quantifying how EPR varies in different collective phases is crucial in developing a thermodynamic framework for the active matter. In this work, we look at EPR in active turbulence. We use Active Model H, a continuum model used representing active particles in a momentum-conserving fluid, to study turbulence in scalar active systems. We measure the local EPR in numerical simulations, which unveils the role of noise amplitude and activity on EPR in active turbulent system.

    

Mori-Zwanzig formalism for general relativity: a new approach to the averaging problem

Cosmology provides a coarse-grained description of the universe that is valid on very large length scales. However, the Einstein field equations are not valid for coarse-grained quantities since, due to their nonlinearity, they do not commute with an averaging procedure. Thus, it is unclear in which way small-scale inhomogeneities affect large-scale cosmology (backreaction). In this work, we address this problem by extending the Mori-Zwanzig projection operator formalism, a highly successful coarse-graining method from statistical mechanics, towards general relativity. This allows to derive a dynamic equation for the Hubble parameter in which backreaction is taken into account through memory and noise terms. Our results are linked to cosmological observations.   

An Investigation of Coupled Wave Chaotic Enclosures

Random Matrix Theory (RMT) and the Random Coupling model (RCM) have been constructed and verified to explain the statistical properties of electromagnetic radiation inside a single wave chaotic enclosure. Recently, there has been work done [1] to extend RMT and RCM so that they can also explain the statistical properties of electromagnetic radiation inside networks of coupled wave chaotic enclosures. This work was done by only taking data in the frequency domain. We now are building on this work by instead taking the data in the time domain. We plan to first verify the time domain version of this experiment works by comparing the results to the previous work that was done in the frequency domain. We then will conduct the following measurements. First, we plan to perform statistical analysis on time domain data taken for various enclosure networks. We then plan to investigate the effects of coherent illumination, time-dependent illumination, and Doppler shifted pulses on the enclosure networks. Lastly, we hope to combine these results to see if time domain measurements can be used to extract information about the enclosure network.

[1] Shukai Ma, Bo Xiao, Zachary Drikas, Bisrat Addissie, Ronald Hong, Thomas M. Antonsen, Edward Ott, Steven M. Anlage, “Wave scattering properties of multiple weakly-coupled complex systems,” Phys. Rev. E 101, 022201 (2020).   

Spectral and steady-state properties of fermionic random quadratic Liouvillians

We study spectral and steady-state properties of generic Markovian dissipative systems described by quadratic fermionic Liouvillian superoperators of the Lindblad form. The Hamiltonian dynamics is modeled by a generic random quadratic operator, i.e., as a featureless superconductor of class D, whereas the Markovian dissipation is described by $M$ random linear jump operators. By varying the dissipation strength and the ratio of dissipative channels per fermion, $m=M/(2N_F)$, we find two distinct phases where the support of the single-particle spectrum has one or two connected components. In the strongly dissipative regime, this transition occurs at $m=1/2$ and is concomitant with a qualitative change in both the steady-state and the spectral gap that describes the large-time dynamics. Our results show that some of the universal features previously observed for fully random Liouvillians are generic for a sufficiently large number of jump operators (above $m=1/2$). On the other hand, if the number of dissipation channels is decreased below $m=1/2$, the gap closes and the steady state decouples into an ergodic and a nonergodic sector, rendering it possible to suppress dissipation in protected subspaces even in the presence of strong system-environment coupling.   

Inertialess gyrating engines

A typical model for a gyrating engine consists of an inertial wheel powered by an energy source that generates an angle-dependent torque. Examples of such engines include a pendulum with an externally applied torque, Stirling engines, and the Brownian gyrating engine. Variations in the torque are averaged out by the inertia of the system to produce limit cycle oscillations. While torque generating mechanisms are also ubiquitous in the biological world, where they typically feed on chemical gradients, inertia is not a property that one naturally associates with such processes. In the present work, seeking ways to dispense of the need for inertial effects, we study an inertia-less concept where the combined effect of coupled torque producing components averages out variations in the ambient potential and helps overcome dissipative forces to allow sustained operation for vanishingly small inertia. We exemplify this inertia-less concept through analysis of two of the aforementioned engines, the Stirling engine and the Brownian gyrating engine. An analogous principle may be sought in biomolecular processes as well as in modern day technological engines, where for the latter, the coupled torque producing components reduce vibrations that stem from the variability of the generated torque.   

Segregation and inequality in kinetic models of wealth exchange

Empirical distributions of wealth and income can be reproduced using simplified agent-based models of economic interactions, analogous to microscopic collisions of gas particles. Building upon these models of freely interacting agents, we explore the effect of a segregated economic network in which interactions are restricted to those between agents of similar wealth. Agents on a 2D lattice undergo kinetic exchanges with their nearest neighbours, while continuously switching places to minimize local wealth differences. A spatial concentration of wealth leads to a steady state with increased global inequality and a magnified distinction between local and global measures of combatting poverty. Individual saving propensity proves ineffective in the segregated economy, while redistributive taxation transcends the spatial inhomogeneity and greatly reduces inequality. Adding fluctuations to the segregation dynamics, we observe a sharp phase transition to lower inequality at a critical temperature, accompanied by a sudden change in the distribution of the wealthy elite.   

Universal active agent: multicomponent vector presentation.

Recently, some agent-based models have been used to describe collective social behavior. Often, the rules chosen to represent agents are somewhat arbitrary. In this work, we attempt to describe evolving agents represented by multicomponent vectors with components defining attitudes to different social norms and behaviors. Each agent can represent an individual or a social group. The system of the vectors is initially established at the very basic state reflecting the averaged or simplified norms of the society. Then the agents are allowed to interact with a reservoir representing much richer types of social norms and behaviors. Thus, the system of agents is allowed to evolve until it reaches a steady state. The Monte-Carlo method is used to represent the interaction and evolution of the agents. Then the system of the agents is disconnected from reservoir and studied by itself. The system of agents prepared in such a way displays rich behavior that explains a number of social phenomena related to the influence of propaganda.   

EFFECTS OF AIR FLOW ON THE FABRICATION OF CONFINED SMECTIC LIQUID CRYSTAL FOAM

Foams are a substance that have an amazing range of characteristics and potential. These materials are both essential and found throughout our daily lives. They can be found everywhere: in various creams, meringue cookies, soda, shaving foam, and Styrofoam. The structure of foams is a continuously heated topic amongst physicists and mathematicians. This is not only because these systems present an essential role in fundamental research, but also because they expanded greatly in the development of many industrial applications, such as thermal insulation, packing, flotation, and oil recovery. Although most of the studies conducted on foams focus on bubbles that are made of simple fluids, little is known about how foams are arranged and packed when they are made of ordered materials such as liquid crystals. In this work, we use 3D printed devices to fabricate and confine smectic liquid crystal foams and investigate the effects of geometric confinement and airflow rate on their fabrication process and stability. We focus on the interplay between elasticity, surface tension, and the geometry of confinement and investigate how their balance may affect foam structure, assembly, and stability.   

Reconstruction of polymer structures from contact maps with Deep Learning

For any polymer, the euclidean distance map (D) is defined as a matrix where D_ij=d_ij² where d_ij is the distance between i and j. This contains all the necessary information to re-create the structure. However certain biological experiments, especially Hi-C or NOESY NMR, are only able to provide us with a contact map(C) containing a list of monomers that are within a certain cut-off distance (r_c). We propose a deep auto-encoder that is able to reconstruct D when only provided with C. We test this network on ensembles of structures generated by MD simulations. We show that a deep auto-encoder is capable of reconstructing polymer structures simply from the contact map information. We propose that this network can be applied to single-cell Hi-C maps to reconstruct chromosome structures in individual cells.   

Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data

Recently, several theories including the replica method made predictions for the generalization error of Kernel Ridge Regression. In some regimes, they predict that the method has a `spectral bias': decomposing the true function $f^*$ on the eigenbasis of the kernel, it fits well the coefficients associated with the O(P) largest eigenvalues, where $P$ is the size of the training set. This prediction works very well on benchmark data sets such as images, yet the assumptions these approaches make on the data are never satisfied in practice. To clarify when the spectral bias prediction holds, we first focus on a one-dimensional model where rigorous results are obtained and then use scaling arguments to generalize and test our findings in higher dimensions. Our predictions include the classification case $f(x)=$sign$(x_1)$ with a data distribution that vanishes at the decision boundary $p(x)sim x_1^{chi}$. For $chi>0$ and a Laplace kernel, we find that (i) there exists a cross-over ridge $lambda^*_{d,chi}(P)sim P^{-frac{1}{d+chi}}$ such that for $lambdagg lambda^*_{d,chi}(P)$, the replica method applies, but not for $lambdalllambda^*_{d,chi}(P)$, (ii) in the ridge-less case, spectral bias predicts the correct training curve exponent only in the limit $d ightarrowinfty$.   

Work extraction from quantum batteries subject to noisy channels

Quantum Thermodynamics studies the theoretical framework behind the energetic properties of promising quantum devices, such as quantum batteries. It has been shown that quantum batteries may potentially improve charging processes, but it is also crucial to assess the stability of the storage phase if they are in contact with environmental noise.

In this work we formalize the problem of the storage of useful energy in quantum devices in presence of noisy channels. We define new figure of merits to benchmark quantum batteries performance depending on the available resources. We show explicit evaluations for various classes of quantum channels.   

Thermalisation in non-Markovian environments

Thermodynamics tells us that a system weakly coupled to an infinite environment will reach thermal equilibrium. In the language of open quantum systems this means we expect a thermal steady state to arise. Under the Born-Markov approximations a the bath is assumed to relax instantaneously, and equations of motion can be derived to ensure thermal equilibrium is reached. However, in many realistic systems of interest these approximations no longer hold. Here we use a variety of exact numerical methods such as time evolving matrix product operators (TEMPO) and the hierarchy of pure states (HOPS) to investigate how non-Markovian environments can perturb the thermal equilibrium state of strongly interacting many-body quantum systems.   

Understanding the statistical origins of the quantum bound on chaos.

The process by which initially localized quantum information in a system is rendered irretrievable due to (usually chaotic) quantum dynamics, referred to as  'scrambling', has been a subject of intense interest in the last decade. The Out-of-time-ordered correlators (OTOCs) form an important class of quantitative tools that yield Lyapunov exponents which quantify the rate of scrambling in quantum systems. In thermal ensembles, these exponents are conjectured to obey a universal quantum bound (λ< 4π²kT/h, where k and h are the Boltzmann and Planck constants respectively). Our numerical investigation strongly suggests that, at least in quantum Boltzmann ensembles, the bound on λ is purely a quantum-statistical effect, which can be explained using imaginary-time Feynman path-integrals. Specifically, we find that delocalized structures in a fictitious extended phase space, that represents bounce instantons are responsible for this bound. This study has important ramifications about the nature of scrambling in quantum systems and demonstrates an important simulation paradigm for obtaining scrambling rates.

    

Author not Attending

It has been more than two decades since Bruce Kane proposed that spin-half phosphorus nuclei embedded in a spin-zero silicon substrate might act as a possible implementation of spin quantum computing. The coherence times of isolated nuclear spins are very long, which makes them ideal qubits. In addition to this their sensitivity to magnetic fields allows a measurable means of qubit manipulation. Despite this, spin quantum computing remains an elusive goal. More recently, physicist Matthew Fisher has suggested a role for nuclear spin dynamics in cognition and possibly consciousness. Intriguingly this model involves phosphorus nuclear spin in the spin-zero substrate of calcium phosphate molecules. While the hypothesis has generated a great deal of interest there are integral questions that remain to be answered. We have modelled the spin dynamics of entangled phosphorus nuclei in pure and doped calcium phosphate molecules. Our results suggest a way in which entanglement might be preserved by the presence of the weak geomagnetic field. This result may potentially inform approaches to spin quantum computing. On the other hand, one of the open questions in Fisher’s model is how entanglement effects might translate into biological signalling. We investigate how quantum computing models of spin transfer from nuclei to electrons might offer insights into the similar case of spin quantum cognition.

    

Noise Limits in the Computation for Motion Detection

Extracting motion information from visual signals is a crucial function for the survival of most animals. A widely accepted model of how the visual system detects wide-field motion is built on computing correlations in the input spatiotemporal light pattern sampled at separate locations in space and time. I used psychophysical experiments to measure the limits of the spatial span and time delay over which the human visual system correlates these input signals. These results set the parameters in a correlation-based ideal observer model. Ideal observer performance is compared to human performance on a psychophysical task based on the estimation of motion direction. The comparison between these results give insight into how robust this computation is to input noise either in the form of contrast fluctuations or photon shot noise.   

Design and Synthesis of Bioinspired Membrane Curvature Sensors

Septin proteins are the only known micron-scale curvature sensors in eukaryotes. These proteins assemble cooperatively and use motifs, such as amphipathic helices, to bind the membrane and detect curvature through mechanisms that are largley unknown. Despite their central role in both health and diverse disease states, the nature of the lipid defects sensed by septins at shallow curvatures and their physical basis for sensing remain unknown. We show how the structural and physical features of septins is exploited in the design of syntethic micron-scale curvature sensors. By reverse-engineering septins, we elucidate the mechanism of septin-mediated curvature sensing and engineer septin-mimetic curvature sensors that can be triggered to recognize multiple curvatures and transduce reactions as a response to the sensing event.    

Structural and functional characterization of unmodified and pyroglutamylated amyloid beta peptides in lipid bilayers

The amyloid β (Aβ) peptide forms soluble oligomers, which play a key role in the etiology of Alzheimer’s disease (AD). N-terminal truncation and pyroglutamylation of Aβ significantly affects its biophysical/biochemical properties and enhances cytotoxicity. One of the mechanisms of  neurotoxicity of Aβ is membrane destabilization or pore formation and dysregulation of cellular ionic homeostasis. Here, the structural features and ion-conducting channel formation in lipid bilayers by four Aβ variants (Aβ_1-42, Aβ_1-40, Aβ_pE3-42, Aβ_pE3-40) are reported. Voltage clamp bilayer electrophysiology studies indicate that all variants exhibit ion channel activity in phosphatidylcholine/phosphatidylglycerol/cholesterol (6:3:1 mol%) bilayers with distinct conductance behaviors. Aβ_1-42 and Aβ_pE3-42 show step-like conductance changes with well-defined open-close states whereas Aβ_1-40 and Aβ_pE3-40 show high-frequency burst-like activity with multi-state conductance. Structural data from circular dichroism and infrared spectroscopy identify significant β-sheet content for the peptides in lipid membranes. In all cases, the channel activity could be blocked by Zn²⁺ ions to varying degrees. Overall, these results suggest that pyroglutamylated variants of Aβ, like unmodified Aβ, are capable of forming ion channels in cell membranes. Characterization of the molecular structure and ion channel formation activities of the most abundant and toxic Aβ species may help in rational drug design for AD.

    

Self-assembling peptide nanopores are stabilized by a cooperative hydrogen-bond network

We have been using synthetic molecular evolution (generations of iterative library design and screening) to evolve large macromolecule-sized (5-10 nm diameter) “nanopores” that self-assemble into such controllable nanopores at low concentration. We identified the pHD peptides that self-assemble into nanopores in lipid bilayers at very low concentration, triggered by mildly acidic pH. We also evolved the closely related macrolittins, which have the same activity, but are not pH sensitive. Such peptide nanopore formation is unprecedented. These peptides fold into α-helices that, despite multiple charged and polar residues, insert into membrane-spanning configurations and stabilize the perimeter of large water-filled pores. Classical textbook concepts of protein folding in membranes do not predict this structure because the peptides appear to be too polar, overall. Since hydrophobicity alone does not account for their stability in membranes, these nanopores must also be stabilized by other interactions, such as H-bonds. Individual sidechain H-bonds in membrane proteins, or in contact with bulk water, are relatively weak. Yet, our atomistic molecular dynamics (MD) simulations show that  charged and polar groups located along the polar surfaces of the nanopore forming peptides form dynamical, yet persistent, cooperative H-bond networks between peptides, lipids, and water that stabilize peptide nanopores. Such networks have been described for some membrane protein, but none are as extensive as the one we have identified in the pHD peptide and macrolittin nanopore structure. These nanopore forming peptides represent a new type of membrane protein structure.

    

Daily prefrontal closed-loop repetitive transcranial magnetic stimulation (rTMS) produces a progressive entrainment-dependent clinical response in depressed adults

In recent decades, increasing evidence suggests the alpha phase is an index of excitation and inhibition across or within networks. Therefore, whether the phase of the endogenous EEG alpha rhythms mediates top-down influences in the human brain, particularly in response to stimulation (e.g., TMS), is an active area of investigation. Under the hypothesis that phase-locked TMS pulse delivering may affect brain dynamics and neurostimulation efficacy, our group developed a novel closed-loop EEG-rTMS system where we could trigger the TMS pulse train at a specific phase of each patient's prefrontal EEG quasi-alpha rhythm (6-13 Hz). 

In this double-blind study, 24 patients with major depressive disorder received daily treatments of rTMS over six weeks. They were randomly assigned to either a synchronized or unsynchronized treatment group. When rTMS is applied over the dorsal lateral prefrontal cortex and synchronized to the patient's EEG rhythm, patients develop increasing alpha phase entrainment over the stimulation site. In addition, at the end of the treatment course, patients who showed more robust phase entrainment across entire treatments would have a better clinic improvement. We did not observe similar effects in the group given rTMS without initial EEG synchronization. The entrainment effects build over days/weeks, suggesting that these effects engage neuroplastic changes. Moreover, this observed entrainment across treatments in the synchronized group has clinical consequences for depression.   

Shear stress and pressure of a granular system with pins

Granular media are large collections of disordered macroscopic particles interacting via dissipative and frictional forces. We encounter them everyday in the shapes of sand, gravel, grains, foams, and even biological beings like bacteria colonies and human crowds. Our research focuses on the effects of pins, small particles that act like restraints, on "jamming", a phase transition when granular media shift from a fluid-like state to a disordered-solid state. Our system contains three types of athermal, bidisperse, repulsive disks in two dimensions with ratio 0.004 (pins) : 1.0 : 1.4 . A shear is applied by moving the top and bottom walls, made of rough particles. We study macroscopic properties such as shear stress, and pressure as function of time and packing fraction and for various shear rates.   

Author not Attending

We probe the microstructural yielding dynamics of a concentrated colloidal system by performing creep/recovery tests with simultaneous collection of scattering data via X-ray Photon Correlation Spectroscopy (XPCS). This combination allows for time-resolved observations of the microstructural dynamics as yielding occurs, allowing for the formation of time-resolved structure-property relations. To more accurately track the non-equilibrium processes which occur under yielding, we utilize two-time correlation functions, which provide additional time-resolved information that is inaccessible via more typical one-time correlations. Under sufficiently small applied creep stresses, the correlation in the flow direction reveals that the scattering response recorrelates with its pre-deformed state, indicating nearly-complete microstructural recovery, and the dynamics of the system slow considerably. Conversely, larger creep stresses increase the speed of the dynamics under both applied creep and recovery. The correlation data show a strong connection between the microstructural dynamics and the acquisition of unrecoverable strain, and suggest that the yielding transition in concentrated colloidal systems is highly heterogeneous on the microstructural level.   

Modelling and simulation of shear jamming in dense suspensions

Shear jammed suspensions respond elastically to deformations and are able to support a stress in the absence of a background flow velocity gradient [1], features absent from standard Wyart-Cates Theory [2]. Experiments on shear jamming in a Couette cell show that this proceeds via a jamming front that advances from the inner boundary of the cell, which has an initially-higher shear rate, to the outer boundary of the cell, with an initially-lower shear rate. In this talk, we present a minimal extension of Wyart-Cates Theory to a dynamical one-dimensional theory (similar to [3]), capable of capturing these features of a shear jamming suspension in a Couette cell. We compare the predictions of our model with results from particle simulations of shear jamming in this geometry. [1] I. R. Peters, S. Majumdar, and H. M. Jaeger, Nature 532, 214 (2016). [2] M. Wyart and M. E. Cates, Phys. Rev. Lett. 112, 098302 (2014). [3] R. N. Chacko, R. Mari, M. E. Cates, and S. M. Fielding, Phys. Rev. Lett. 121, 108003 (2018).   

Resource competition explains simplicity in microbial community assembly

Predicting the composition and diversity of communities is a central goal in ecology. While community assembly is considered hard to predict, laboratory microcosms often follow a simple assembly rule based on the outcome of pairwise competitions. Despite the empirical success of this bottom-up prediction, its mechanistic origin has remained elusive. In this study, we elucidate how resource competition can lead to simple patterns in community assembly. Our geometric analysis of a consumer-resource model shows that trio assembly is always predictable when some species grow faster than another species on every resource. We also identify all trio assembly outcomes under three resources and find that only two outcomes violate the assembly rule. Simulations demonstrate that pairwise competitions often accurately predict trio assembly with up to 50 resources. We further show that this predictability holds for communities larger than trio and with cross-feeding between species. Our findings highlight that simple community assembly can emerge even in ecosystems with complex underlying dynamics.   

Quantifying intracellular information flow

Signalling pathways convey information about the environment which cells collect and process to make decisions. The cell’s ability to govern its functions correctly and precisely while relying on these intricate biochemical networks is surprising given the noisy cell interior, which indicates the mechanisms cells use to process information are highly sophisticated. While our understanding of the constituents of the cellular machinery and the processes taking place in the cell is steadily increasing, little is known about the information flow within the cell. Are pathways conveying only on/off signals, or is there graded information being transduced? Here, we measure and quantify the information relayed through the MAPK signalling pathway, one of the key signalling pathways in eukaryotic systems. Using a synergy of the optogenetic experimental setup and data analysis based on information theory, we quantify the input-output relationships within the MAPK signalling pathway and highlight the role of intracellular and extracellular noise, stochastic activations of the pathway and the temporal aspect of the information processing in the cell. We show that the capacity of the pathway exceeds the 1-bit value (on/off), and that collective systems of cell seem to exploit this capacity.

    

The effect of pins on micro- and macroscopic properties of sheared particles near jamming

Jamming, the onset of macroscopic rigidity, occurs in a wide variety of disordered soft/granular systems. Fixing degrees of freedom by adding pinned particles facilitates jamming and tunes microscopic and macroscopic properties near the jamming threshold. For example, it has been shown for a system in mechanical equilibrium that pins dramatically alter the distribution of forces and decrease the elastic moduli [1]. Here, we use LAMMPS molecular dynamics to shear an athermal 2D system of harmonically repulsive particles. Particles and pins are sheared at a constant rate between rough particulate walls. We study the effect of pins on pressure and shear stress vs. shear rate and packing fraction, and analyze transient responses like yield. Microscopically, we study relationships between D²_min, which quantifies a particle’s non-affine deformation, contact number, Z, and locations of pins.

[1] A.L. Zhang, S.A. Ridout, C. Parts, A. Sachdeva, C.S. Bester, K. Vollmayr-Lee, B. C. Utter, T. Brzinski, and A.L. Graves, Phys. Rev. E 106, 034902 (2022)

 

    

Capillary imbibition in lubricant-coated surfaces

We describe spontaneous imbibition processes in lubricant-coated surfaces. This geometry represents a simplified version of experimental realisations like slippery liquid-infused porous surfaces (SLIPS) and lubricant-impregnated surfaces (LIS), where the lubricant eliminates direct contact of both invading and displaced fluids with the solid. We combine a theoretical and computational analysis to clarify the dissipation mechanisms that governs the dynamics of imbibition. The asymmetric distribution of dissipation among the fluid phases results in two limit regimes:  When the dissipation is more relevant in the displacing fluid, we find a diffusive advancing of the front, which corresponds the well-known limit in which invading and displaced fluids are in direct contact with the solid. If dissipation takes place preferentially in the lubricant, we find a linear advancing of the front through the entire channel.

A simplified mathematical modelling is presented, which captures these regimes. The analysis allows to characterise the corresponding crossovers between the limiting cases, and generalise the dynamics to imbibition when there is an external forcing.

Our work paves the way into experimental scenarios of similar systems, like SLIPS or LIS, and also towards characterisation of lubricant-coated surfaces in more general channel geometries like wegdes or sinudoidal shapes.   

Modeling Colloidal Surfaces using Method of Regularized Stokeslets

Bacterial motility can be hindered or enhanced by interactions with different types of surfaces in a fluid environment. To study bacterial motion near a rough surface, we want to simulate a layer of randomly-distributed microspheres to represent a surface constructed of lipids. Our goal is to incorporate physically realistic forces into our simulations to make quantitative predictions of fluid-surface interactions. Using the method of regularized Stokeslets, we validated the Brownian motion of a particle due to thermal energy in the fluid environment. We further included an interparticle force that depends on the distance between two particles to examine how the forces affect the fluid flows. We compared the fluid flows predicted by two models: (1) a regularized Stokeslet point at the center of a particle, and (2) a sphere whose surface is discretized by regularized Stokeslet points. In future work we will compare the viscosity as predicted by the sphere model and the point model.   

Fingering contact propagation between a droplet and a thin liquid film

When impacting droplets approach a hard plane substrate slowly, so that the Weber number is below approximately 5, a contact-less rebound will occur due to the entrainment of ambient gas. On slightly deformable and smooth spin-coated liquid films upon a rigid solid, this effect is more robust and may occur until slightly higher Weber numbers. Deformation of the thin film is usually ignored – while it is proven to be present. The deformation amplitude depends on the impact dynamics as well as the thickness and viscosity of the surficial oil layer. At slightly higher impact velocities, i.e. slightly higher Weber numbers, delayed contact formation between the film liquid and the droplet occurs. Depending on the layer’s properties, interestingly, the contact line may be unstable displaying a fingering texture. Instability occurs independently of whether the drop and film liquid differ or not. We present and analyze this phenomenon.

    

Assembly of Electrically Charged Particles on Asymmetric Droplet Interfaces

Microparticles on the interface of a sessile droplet interact via electrostatic and capillary forces that are governed by particle size, surface charge, and contact line roughness. We created various asymmetric liquid droplets using surface energy patterning and delivered microspheres to the interface with electrospray atomization. Using water as the target droplet, we observed the particle assembly over time. We found that the underlying surface energy pattern could significantly influence the colloidal assembly, depending on the particle type. Electrically insulative particles arranged as a large, single cluster with local hexagonal ordering, but left a clear region free of particles near the contact line. This depletion region is attributed to electrostatic repulsion between interfacial particles and the photoresist used to create the surface energy pattern, both of which retained electric charge from the electrospray. Our experimental results are supplemented by a numerical solution to the electric field near the droplet interface, to corroborate the substrate repulsion and depletion region formation. Finally, to understand the magnitude of particle-substrate interactions, we explored particles with different electrical properties. Understanding the kinetics of electrosprayed particles at the droplet surface is essential for building predictable and structured monolayers via interfacial self-assembly.   

Liquid-Solid Co-Printing of Multi-Material 3D Fluidic Devices via Material Jetting

Multi-material material jetting additive manufacturing processes deposit micro-scale droplets of different model and support materials to build three-dimensional (3D) parts layer by layer. Recent efforts have demonstrated that liquids can act as support materials, which can be easily purged from micro/milli-channels, and as working fluids, which permanently remain in a structure, yet the lack of a detailed understanding of the print process and mechanism has limited widespread applications of liquid printing. In this study, an "all in one go" multi-material print process in which non photo-curable and photo-curable liquid droplets are simultaneous deposited, is extensively characterized. We envision the liquid–solid co-printing process as a key new capability in additive manufacturing to enable simple and rapid fabrication of 3D, integrated print-in-place multi-material fluidic circuits and hydraulic structures with applications including micro/mesofluidic circuits, electrochemical transistors, lab-on-a-chip devices with in-situ reagent deposition, and robotics. We note the ease in which this technique allows fabrication of micro/mesofluidic devices. 3D printing enables those with no prior soft lithography and micro-fabrication experience to produce micro/mesofluidic devices thus making the field more accessible.   

Metachronal waves with programmable densely packed magnetic artificial cilia

Biological cilia exhibit a consorted collective movement in a metachronal wave. It is yet unclear how these collective movement contribute to the biological functions of cilia or how these waves are generated in the first place. Hence, it is useful to create artificial cilia that can reconstitute metachronal waves to generate insights and to help develop applications that make use of these mechanisms. However, almost all of the artificial cilia to date that are capable of having metachronal motion have a large pitch-to-width ratio, hence are too sparsely distributed to study the interciliary flow or their influence on the collective functions of natural cilia. For example, magnetic artificial cilia, the most common ones due to the remote actuation mechanism and high obtainable frequency, are all placed relatively far apart because of attractive forces from magnetic interaction between cilia. Hence, creating a system with densely packed magnetic artificial cilia that allows tuning of the cilia spacing, phase difference and wavelengths is needed for modeling natural cilia. In this study, the magnetic artificial cilia were fabricated by molding magnetic thermoplastic elastomer in micromolds fabricated with femtosecond laser-assisted etching (FLAE) technique. The design was assisted by a COMSOL model. Experiment and simulation results show the same vortex structures generated by the cilia, which are critical in understanding the mechanism of metachronal-induced flow.   

Progress in Quasihydrodynamics

Hydrodynamics is the study of interacting systems at late times and large distances. Applying this framework to a generic system requires that the only degrees of freedom that remain relevant at these scales are those associated with conservation of the “hydrodynamic charges” such as energy, momentum or particle number.

Spurred by discoveries in high energy physics (in particular gauge-gravity dualities), there has been much recent work in understanding and obtaining the formal structure of hydrodynamic constitutive relations. For example, it is now understood how to obtain dissipative constitutive relations from a variational principle via the “Schwinger-Keldysh” formalism. Moreover, this programme has led to the development of hydrodynamic descriptions for some rather exotic states of matter (such as strange metals, Weyl semi-metals etc.).

A sister theory to hydrodynamics is quasihydrodynamics. This represents a modification of hydrodynamics where energy, momentum and particle number are no longer conserved, but decay very slowly. Quasihydrodynamics is much less well understood, but is necessary if hydrodynamics is to be a good description of certain exotic states of matter.

In this poster I will review the progress that has been made into understanding the structure of quasihydrodynamics. I will summarise recent work and indicate where open questions remain.   

Developing a Slow Moist Variable for a Compressible Atmosphere with Clouds

Clouds are one of the greatest challenges in atmospheric physics. They are the leading source of uncertainty in climate change predictions, and rainfall is arguably the most challenging quantity to predict in weather forecasts. Our theoretical understanding of clouds also lags behind our understanding of a ``dry'' atmosphere. In recent years a new conserved quantity, called the “M” variable, was shown to describe the slow component of moisture in the atmosphere. for a simplified set of equations, called the Boussinesq equations. Here we seek to develop an M quantity for the more general compressible set of equations. In particular, we show that the energy for an atmosphere with clouds, can be decomposed into three components that correspond with pressure perturbations (acoustic/sound waves), buoyancy, and a slow moist latent energy which is points towards a compressible definition of the “M” variable.

    

Development of Micromixing Strategies Using Extensional Flow Elements

Computational fluid dynamics modeling was used to characterize the effect on mixing of the integration of constrictions into a serpentine channel. The constrictions are defined by hyperbolic functions, that seek to maximize the extensional flows experienced by the fluid, while limiting the increase in the pressure drops along the channel. In this new topology, the combination of these flows with the Dean flows formed in the curved sections due to the centrifugal forces experienced by the fluid, results in complex flows that are found to enhance the mixing performance of these systems. Optimization of the mixers with respect to the improvement in the mixing performance relative to simple serpentine designs identifies designs for which the mixing performance exceeds 0.93 (1.00 being the maximum) for a broad range of Reynolds numbers.   

Dynamics and Transportation Mechanism in Two-Coupled Large-Scale Circulations ---A Novel Theoretical Approach

The large-scale circulation (LSC) in Rayleigh-Bénard Convection has been extensively studied including two stochastic models which treat diffusion of the LSC strength in a potential well [1,2] and other deterministic models with chaotic solutions [3,4]. Therein, the rich dynamics and inherent physics of LSC can be well-described by stochastic models proposed by Brown and Ahlers [5]. However, the majority of LSC found in nature entails ceaseless interaction with adjacent LSC, such as ocean circulation and general atmospheric circulation which always exist as multiple flows coupled with each other. Thus, existing models are inadequate to describe the coupling mechanism when it comes to multiple flows.

Based on single-roll LSC model BA07 [4], taking volume average of physically important terms rooted in Navier-Stocks (NS) equations, we formulate a modified one to account for double-layer LSC dynamics and coupling mechanism, i.e., thermal coupling and viscous coupling, in two-layer fluid system. The updated model [6] contains four stochastic ordinary differential equations to describe two degrees of freedom of each roll. We numerically calculate these equations and obtain the probability distribution function (P.D.F) of relatively azimuthal orientation. The results of numerical calculation on the stochastic model are in good accordance with previous experiment results in two-layer RBC [7], which shows a peak around zero degrees and a small one close to Pi. It can be concluded that, in a two-layered system consisting of heavy fluid in the lower layer and a light fluid as the upper layer, the rolls prefer to stay in the thermal coupled mode, which may have broad implications in a wide-spread of physics problems.   

Thermodynamically-consistent formulation of stochastic chemistry for modeling reactive gas dynamics at small scales

While the mean behavior of a fluid is well captured by deterministic fluid equations such as compressible Navier-Stokes equations down to micro and nanoscales, random molecular motions of fluid particles elicit thermal fluctuations at these small scales in the continuum description. In reactive fluid systems, these spontaneous fluctuations can grow beyond the microscale due to the interaction with the nonlinearity of chemical reactions, potentially impacting the macroscale behavior of the fluid. In this work, we develop a simulation method for reactive gas mixtures at small scales. To this end, we incorporate the chemical Langevin equation description of stochastic chemistry into the fluctuating hydrodynamics equations for the mesoscopic fluid description. We derive a thermodynamically-consistent stochastic chemistry formulation, where the temperature-dependence of the rate constants are correctly included. We validate our formulation and implementation by using an equilibrium gas mixture system undergoing a reversible dimerization reaction. We demonstrate that the correct temperature dependence of the rate constants is essential for achieving thermodynamic consistency even in a system with small temperature fluctuations.

    

Thermocapillary migration of spherical droplet with a particle laden interface – Limit of Conducting Stagnant Cap.

The thermocapillary migration of a drop under an applied temperature gradient is a well-established phenomenon (Young et al. 1959). Often in practical applications, this migration is hindered by the presence of a stagnation region due to the downstream accumulation of surface impurities/surfactants along the drop surface. Models incorporating the effect of this stagnant region (stagnant cap) on the hydrodynamics of the drop have been effective in determining the forces on the drop and its terminal velocity (Kim and Subramaniam 1989). Applications in microfluidics/microgravity problems involving larger adsorbed quantities on the fluid interface (Ex. colloidal particles adsorbed onto larger drops/bubbles/foams etc. (Lan 2012)) raise the interesting prospect that the stagnant cap can not only affect the flow field, but also the local temperature field. We show that the surface area and thermal conductivity of the stagnant cap play a significant role in determining the Marangoni stresses on the drop. We also investigate the role of the transport properties of the drop and suspending medium in this system. Finally, we use asymptotic models to analytically determine the bounds of the effect of the stagnant cap conductivity on the terminal velocity of the drop.   

High-throughput soft particle mechanical measurements by Capillary Micromechanics in a microfluidic chip

Capillary Micromechanics is a simple and direct method for probing the mechanics of microscopic soft objects. It is based on measuring the pressureinduced deformation of soft particles or cells, as they are forced into a tapered glass microcapillary. However, there are several limitations, such as low throughput, lack of device reusability, and device fragility. To overcome these drawbacks, we developed a fused-silica microfluidic chip with parallel, tapered channels of circular cross section. We fabricate the chip using femtosecond (fs) laser micromachining in combination with chemical wet etching (CWE)[2] and test it by measuring the mechanical properties of soft hydrogel particles.

    

Dynamically similar models of bacterial moving near a boundary

Numerical simulations of microorganisms are often not compared to precise measurements because making microscopic measurements of forces and torques in biological experiments is difficult. Instead, we use dynamically similar tabletop experiments to provide precise calibration values as part of our collaborative project (NSF POLS - 2210610). The tabletop experiments use various bacterial models that are about 10 cm in size and match the Reynolds number of swimming microorganisms by using highly viscous silicone oil that is 100,000X more viscous than water so that they are dynamically similar. We can measure the forces and torques with high precision and scale the results to biologically relevant values. We have calibrated the method of timages for regularized Stokeslets and found excellent agreement between our data for both cylinders and helices (Shindell et al. 2021). Our results have also confirmed the theory of Jeffrey and Onishi (1981) for the torque on a cylinder rotating near a plane wall and the theory of O'Neil (1964) for the torque on a sphere near a wall.   

Purcell's Three Link Swimmer in a Macroscopic Lab

Purcell theorized that one of the simplest robots that can move at low Reynolds number is a three-link swimmer, which consists of three hinged links in a chain. The work of Hatton and Choset (IEEE Trans. Robot, 2013) provides a theoretical framework to predict the displacement and rotation of such a swimmer, but assumes the robot links are slender. They use a phase space of the two joint angles and a 3-D map known as a height function derived from the Navier-Stokes equations to determine the motion of the swimmer. However, no one has tested this theory experimentally using a macroscopic three link robot. We use a 3-D printed body and vary its shape to see how the how the performance of the swimmer changes in a sand test bed before placing the robot into a tank of highly viscous silicone oil so the Reynolds number is small. Once the robot design is complete we wil lthen track the motion in videos to compare the displacement and rotation to that predicted by theory. We plat to determine the height function for our robot empirically (Hatton et al., PRL 2013) to understand the error introduced by our robot not being a slender body.   

MEASURING ENERGY DISSIPATION OF REFLECTING INTERNAL WAVES USING EXPERIMENTS AND SIMULATIONS

Determining the energy flux of an internal wave from the experimentally measured velocity field was made possible by the work of Lee et al. (Lee et al., Phys. Fluids, 26, 2014). This method is used in our work to measure the amount of energy dissipated when internal waves reflect from sloping boundaries by computing the reflection coefficient: the ratio of the outgoing energy flux to the incoming energy flux through a surface near to the reflection region. We account for viscous decay so that we can quantify the losses in the reflected wave due only to boundary processes and harmonic generation. We compare our experimental results to numerical simulations of the Navier-Stokes equations in the Boussinesq limit where the energy flux is known from the pressure and velocity fields. There is good agreement between our experimental and numerical simulation data, and we find that there are high rates of energy dissipation during reflection process. We also find that there is a wave reflected back from the boundary towards the generation site when either the boundary is rough or the angle of the boundary is close to the angle of the internal wave beam.   

The effect of obstacles near a silo outlet on the discharge of soft, low-frictional grains

Soft, low-friction particles show peculiar characteristics in silo discharge, including, for example, non-permanent clogging and intermittent flow. This paper describes a study of hydrogel spheres in a quasi-2D silo. We enforce a more competitive behavior of these spheres during their discharge by placing an obstacle in front of the outlet. High-speed optical imaging is used to capture the discharge. All particles in the field of view are tracked by means of machine learning software using a mask region-based convolutional neural network algorithm. With particle tracking velocimetry, the fields of velocity, egress time, packing fraction, and kinetic stress are analyzed. While in pedestrian dynamics, placement of an obstacle in front of a narrow gate may reduce the stress near the exit and enable a more efficient egress, the effect is opposite for our soft grains. Placing an obstacle above the orifice always led to a reduction of the flow rates, in some cases even to increased clogging probabilities.   

The Capillary-driven Two-phase Embedded Microchannel Heatsink for the Efficient Cooling of Power Electronic Modules

The power electronic module is an integrated package of chips, including power MOSFET and diodes, for the application of power modulation. The evolution of power electronics leads to a more compact form factor and higher power density. The miniature size and the increased power density pose challenges to thermal management. The embedded microchannel coolers in the Direct Bonded Copper (DBC) substrate significantly improve the cooling performance (1, 2), but the high pressure drop is a critical drawback for coolers of this kind. The 3D manifold structure optimized the flow distribution and demonstrated a decrease in the pressure drop by 5-fold (from >200 kPa to <40 kPa) (3). However, there is room for further pushing the Pareto front.

In this study, a microchannel cooler with a wicking structure is proposed to leverage the potential of capillary flow and two-phase cooling to improve the cooling performance. The wicking structure at the surface of the channels transports the coolant via capillary force (4). Also, phase-change cooling removes heat by latent heat without a temperature increase (5). The design enables a much lower thermal resistance of the heat exchanger (< 0.2 cm2-W/K) that can operate at a much lower pressure drop (<5 kPa) for the application to the next-generation power electronic module.   

The dynamics of jet produced due to droplet

We numerically studied a moving droplet inside a quiescent liquid medium and studied the jet formation using Volume of fluid (VOF) method. When the droplet moves inside the liquid, it creates a lower-pressure zone at its rear side, which causes the surrounding liquid to rush toward the low-pressure zone creating a jet-like structure. Droplet moving with higher velocity creates mushroom-shaped jet. We found that the velocity profile of the jet matches well with the similarity solution for the axisymmetric free jet u/um = (1+η²)^-2, where η = σ` r/x is the similarity variable. Here, σ` is a constant, and um is the axial velocity along the centreline, i.e., u(x,y=0). Through capillary time scale and energy balance, we found that the jet velocity (V_j) = V (1-Oh)^-1/2, where Oh =μ / (ρ R σ)^1/2 , R and V the droplet radius and velocity, ρ, µ and σ indicating the liquid density, viscosity, and interfacial tension coefficient respectively. Within Oh ? 0.01, jet velocity is approximately equal to the droplet velocity. With an increase in Weber number (We = ρ V² R /σ) of the droplet, jet velocity gets increased, and the jet moves in the forward direction penetrating the droplet in a toroidal shape. We analytically predicted the critical Weber number needed for the jet to completely traverse the droplet from an energy analysis of Edgerton’s experiment of a bullet traversing an apple, and the critical Weber number required for the jet formation is ≈ 23, which matches well with our numerical findings. Here the jet velocity is almost equal to the initial droplet velocity, and the maximum jet height (H_j{max} ≈ 0.056 We) and maximum jet radius (R_j{max}≈ -0.036 We) scale linearly with the Weber number. From this linearity phenomenon, we can say that the jet becomes narrower and longer as the droplet velocity increases.   

Flagellar motility in shear flows

Motile bacteria use different strategies to provide activity. Rotating helical flagella is one of the best studied motility mechanisms. Flagella are elastic filaments, and thus are deformable under shear. The deformed flagella change the direction of the thrust force that modifies the bacterial motion. Here we present a preliminary study on the swimming behavior of bacteria in a semi Poiseuille flow.

    

Macromolecular Engineering of Rheology and Pinching Dynamics of Formulations

Formulations for personal care products, paints and coatings, and food products are common examples of multicomponent fluids containing a mixture of polymer, amphiphiles, and particles as additives. Hydrophobic stickers, charged micelles, and charged particles provide hydrophilic, flexible polymers with temporary, dynamic junctions that change with polymer concentration and deformation. Macromolecular engineering of formulations typically relies on the characterization of response to shear flow, with velocity gradients perpendicular to flow direction, emulating processing flows through channels and drag flows near moving solid surfaces. However, extensional rheology characterization has remained a longstanding challenge, even though streamwise velocity gradients associated with extensional flows, often arise during processing, especially during dispensing and liquid transfer (e.g., dripping, jetting, or spraying). In this contribution, we examine the influence of dynamic associations on macromolecular dynamics and formulation rheology in response to both shear flows and extensional flows using torsional rheometry and dripping-onto-substrate (DoS) rheometry, respectively. We find that dynamic associations help to tweak the rate-dependent rheological response, to facilitate easier dispensing and coating, and better sagging, leveling, and storage while reducing misting and stringiness.   

Rheological Evaluation of Artificial Saliva Formulations

Artificial saliva formulations are commonly used in medicine, food, and pharmaceutical research to emulate the biochemical, tribological, and rheological properties of human saliva. Like other viscoelastic fluids, saliva is known to possess properties such as stringiness or spinnbarkeit, governed by extensional flow parameters which cannot be extracted using conventional torsional rheometry. Even though extensional flows involving saliva are commonly encountered in situations such as swallowing, licking, drooling, and sneezing, rheological evaluations of saliva substitutes in the current literature are usually based on shear viscosity alone. In this contribution, we provide a comprehensive examination of the shear and extensional rheology of twelve commercially available artificial saliva formulations and dry mouth treatments using rate-dependent torsional rheometry and dripping-onto-substrate (DoS) protocols, and evaluate their properties based on pioneering studies of saliva's viscoelasticity. Despite the majority of these formulations being marketed as having enhanced rheology, only a select few displayed measurable viscoelasticity and strain-hardening, and did so at viscosities significantly higher than that of saliva.   

Isotropic to Nematic Transition in Sediments of Colloidal Rods

This study focuses on developing a colloidal system to investigate the structural properties of sediments from suspensions of colloidal rods. SU-8 colloidal rods have been prepared using a high shear-based method and have been filtered by centrifugation to separate by rod length and mitigate the polydispersity of the rods. Rod suspensions are then loaded into capillary tubes and sediments are formed by high g centrifugation. Preliminary results indicate that some conditions lead to dense, nematically ordered sediments while others produce isotropic, low density sediments. The goal of this work is to investigate the impact on sediment properties of modifications of the rod size and aspect ratio, by varying synthesis conditions, as well environment alteration, including centrifugation rate, and solvent. Determination of density and ordering is performed using confocal microscopy.   

Chemotactic behavior of a self-phoretic Janus Particle near a chemically emitting patch.

Self-phoretic Janus Particles (JPs) are artificial microparticles that aim at reproducing the motion of biological microswimmers (S. Michelin and E. Lauga, J. Fluid Mech. 747, 572 (2014)), such as sperm cells, microalgae, and bacteria, among others. They possess the ability to self-propel in fluids by modifying the chemical composition of the surrounding solution. This results in an effective slip on the particle surface, which can drive the net motion of the JPs. Motivated by the behavior of the biological counterparts which sense and respond to an external chemical gradient (i.e., exhibit chemotaxis), this study aims at modeling the motion of a self-phoretic JP in a non-uniform fuel gradient under geometric confinement. The fuel molecules are released into the solution by a chemically emitting patch located on a planar solid boundary. The particle, moving at very low Reynolds numbers in a Newtonian fluid, steers towards or away from the patch through the interplay of self-diffusiophoresis and chemotaxis. The influence of multiple parameters, such as the activity function, fuel function, catalyst coverage, and patch geometry, is reported. Finally, we address how these states are affected by thermal fluctuations.

    

Band structure of a rotating helical phononic crystal

Carlos I. Mendoza , 1,* J. Adrián Reyes,2 and Gerardo J. Vázquez 2

1Instituto de Investigaciones en Materiales, Universidad Nacional Autónoma de México, Mexico City, Mexico 2Departamento de Física Química, Instituto de Física, Universidad Nacional Autónoma de México, Mexico City, Mexico

We consider an elastic helical medium whose tensor stiffness twirls uniformly along the helix axis. We are

interested in analyzing the band structure when the whole material is externally forced to rotate around the helix

axis to a fixed constant frequency. Departing from a general dynamic description of the elastic phenomena,

we establish a set of equations for the displacement vector and the stress tensor. These equations allow us to

calculate the band structure parametrized by the externally imposed rotating frequency. We find that the band

structure strongly depends on the rotation frequency, and we show that backward and forward modes propagate

differently, particularly for the longitudinal and right-polarized modes.   

Development of 3D Printing Feed Stock of Thermosets using Photothermal Refractory Plasmonic Nanomaterials.

Epoxy resin additive manufacturing is the newest trend, replacing traditional materials and techniques in various fields due to its capacity to produce complicated geometries fast and affordably. Traditionally, photoinitiators are incorporated in epoxy to enhance the curing rate using UV light. However, photo initiators can compromise the mechanical strengths of the printed parts. Additionally, microscopic voids and roughness of the surface adversely affects the printed epoxy part's mechanical integrity. Here we are developing 3-D printing feedstock by mixing thermoset polymer mixed with strongly optically absorbing photothermal refractory plasmonic titanium nitride nanomaterials. Additionally, we integrated dynamic covalent diene-dienophile links (Diels-Alder process) in epoxy to incorporate thermo-reversibility. Titanium nitride nanomaterials can efficiently, rapidly convert light into localized heating to accelerate the curing of epoxy. FTIR data suggested the curing rate with light is around 26 times faster than curing using heat when the average bulk temperature of the samples are similar. The complex viscosity of the resin significantly increases after a brief exposure to light in comparison to heat. Additionally, optical microscopy and atomic force microscopy images confirm that we could use light to controllably depolymerize targeted surface area of 3-D printed parts to smooth out the rough surface or heal any cracks.

    

Transfer Kinetics of Cargo Items among Nanocarriers

Nanocarriers such as micelles, liposomes, nanoshells and nanocages, dendrimers, carbon nanotubes, and nanoparticles are used in applications to transport cargo items--often drug molecules--to a target site. When nanocarriers collide with each other, cargo items are able to migrate from one to another nanocarrier. We employ chemical reaction kinetics to characterize how the distribution of cargo items among all nanocarriers in a mixture of different nanocarrier types depends on time. In the continuum limit, valid when each nanocarrier contains a sufficiently large number of cargo items, we express the kinetic equations as a system of partial differential equations--diffusion equations with additional demixing terms--that evolve into Gaussian distributions over time. We solve the partial differential equations and thus determine the kinetic behavior for any initial distribution of cargo in this multi-type nanocarrier system. The model can be generalized to address related problems, including the account of sink conditions, spatial variations analogous to diffusion-reaction phenomena, the release of cargo directly into the solution, and aggregation of cargo items inside carriers.

 

    

Camphor disk velocity depends on reservoir depth

We investigate the self-propulsion of a camphor disk in a one-dimensional periodic system to study the relationship between the velocity and the water-depth of the aqueous phase. The camphor disk was hypothesized to increase its self-propulsion speed as the water-depth of the system increases due to Marangoni flows. Using an annular ring, we quantified the dynamics exhibited by the camphor disk while varying water-depth: 1mm - 10mm. Our results suggest that the velocity of the camphor disk exhibits a nonmonotonic relationship with water depth – in contrast with some previous studies. We investigate confounding parameters that indicate camphor disk motion is much more complex than we realized. These experiments set the stage to understand the multiparticle dynamics of strongly interacting camphor disks.   

Diffusion of inhomogeneous populations - a computational study

A system made up of a homogeneous population of identical objects undergoing Brownian motion can be precisely characterized by an average diffusion coefficient. A multicomponent (two or more) system can also be characterized by an average diffusion coefficient, but in this case the measurement and interpretation of that diffusion coefficient represents a mixture of different dynamics. At the microscopic scale, similar objects are expected to diffuse at similar rates (determined by thermal noise), but at the macroscopic scale Brownian-like "diffusion" of particles (e.g. hexbugs) is driven by active noise and may differ even for similar-sized objects. We study a variety of systems made up of inhomogeneous populations undergoing diffusion using a simple computational approach. We analyze their motion using Dynamic Differential Microscopy as well as single particle tracking. We characterize the dynamics of these systems using two statistics, namely Mean Squared Displacement (MSD) and Mean Back Relaxation (MBR). We relate these statistics to the diffusion coefficient.   

Dynamic Modeling of Myosin VI Allosteric Communication Pathway

Myosin VI, fueled by ATP hydrolysis, can act as a transport motor that moves along actin filaments to deliver cargo. It has been well established that the ATPase kinetics of the motor is affected by myosin VI binding to actin filaments. In order to investigate the origin of this dynamic change at a molecular level, we modeled both a myosin VI monomer and myosin VI actin complex by mapping their structures onto elastic networks.  We analyzed the vibrational dynamics of the models and calculated the residue-dependent responses to local perturbations to map the corresponding allostery wiring diagrams.  Specifically, we study the ADP to APO transition in both models.  We report actin binding-induced changes in dynamics of the models and in the allosteric signaling network.

    

Analyses of the cores of AlphaFold2 protein structure predictions

Developing computational methods to accurately predict the three-dimensional structure of a protein from its primary sequence of amino acids is an important and unsolved problem. AlphaFold2, a deep learning methodology developed by DeepMind to generate computational models of proteins, has been successful in recent Critical Assessment of protein Structure Prediction competitions. In the present work, we assess AlphaFold2 computational models using the number of residues in the core, a feature that is strongly correlated with protein stability. We find that while AlphaFold2's predictions for the E. coli proteome resemble X-ray crystal structures, the eukaryotic protein predictions contain too few core residues. Our analysis considers the influence of intrinsically disordered sequences on the fraction of core residues, using both AlphaFold2's per-residue confidence levels and the average charge and hydrophobicity of each protein. The variability in the core size of AlphaFold2's predictions across organisms demonstrates that while machine learning methods have increased the accuracy of computational models for protein structure, significant improvements must be made to achieve results comparable to those in experiments.   

A Disordered Plant Microtubule Associated Protein Reorganizes Microtubules During Stress

Companion of Cellulose Synthase 1 (CC1) has been recently identified to maintain cellulose synthesis during salt stress in Arabidopsis. CC1 is predicted to be a multi-domain protein with an N-terminal cytosolic disordered region (CC1NTD), a transmembrane region, and a C-terminal apoplastic region based on bioinformatics and structural modeling using Alphafold2. Previously, the disordered region of CC1 was found to interact with cortical microtubules in a similar fashion to human Tau protein however the structural basis for the interaction has not been investigated. In this work we investigated the solution structure of CC1NTD and its interaction with microtubules using small-angle X-ray and neutron scattering. Size exclusion chromatography – small-angle X-ray scattering analysis reveals that CC1NTD exists as a redox-dependent equilibrium mixture of monomers and dimers. SAXS shows that there is a structural rearrangement of microtubules in the presence of CC1NTD that supports bundling of microtubules. Using contrast variation SANS at the contrast match point of the microtubules, we observed the structure of deuterated CC1NTD and showed that the protein has a regular distribution across the microtubule lattice that is consistent with a tetragonal arrangement of CC1NTD around the microtubules. Overall, our study provides insights into how a disordered plant microtubule associated protein can affect the cortical microtubule network when plants are subjected to stress. Current research is now focused on understanding the structural remodeling of microtubules during this process.  

    

Physical and Evolutionary Free Energy Landscapes of Devolved Protein Sequences

Protein evolution is guided by structural, functional, and dynamical constraints ensuring biological viability. Pseudogenes are former protein-coding genes identified in numerous prokaryotic and eukaryotic organisms that lack translational activity due to sequence deterioration. The resulting loss of selection pressure makes pseudogenes an intriguing example of naturally-occurring protein devolution. Mutational effects on pseudogenes’ former native structure and function remain largely unexplored in the literature. We characterized the physical and evolutionary free energy landscapes of human pseudogenes associated with various protein domains, respectively using the optimized physical model Associative Memory, Water Mediated, Structure and Energy Model (AWSEM) and the coevolutionary model Direct Coupling Analysis (DCA). We found that pseudogene mutations disrupt their native global network of stabilizing residue interactions. We also investigated pseudogene sequence variations in Cyclophilin A, Profilin-1, and SUMO-2 Protein that are more energetically favorable than native residues. Our analysis reveals that physically stabilizing mutations inhibit or alter pseudogenes' former biological activity.

    

Sensing Dielectric Relaxation in Thermal Unfolding of Lipase

The dielectric relaxation illustrates the response of a dielectric material to the external electrical perturbation. There occurs a fractional time delay when the electrically perturbed system returns to the equilibrium state. The time delay is caused by the lag in the emergence and decay of the molecular polarization in the material with respect to the oscillating electric field. The dielectric relaxation time varies with the chemical composition, structure, and the local milieu of the material. The relaxation dynamic provides crucial clues into the structural changes of the complex protein molecule. Thermal unfolding and aggregation of protein manifest as changes in dipole moment, alteration in charge distribution, and the dielectric properties of local ambience near the protein molecules. Herein, we have examined the structural as well as the electrical property changes due to temperature-dependent unfolding through non-faradic impedance spectroscopy using a small quantity of protein (5 micro-liter). The relaxation time was calculated from the impedance spectra. The relaxation time of the protein molecules is found to be decreasing with cold and hot denaturation of lipase enzymatic protein. Henceforth, the decreasing relaxation time corroborates with the gradual functional inactivation of the enzyme due to temperature which was validated by para-Nitrophenol (pNPP) assay. The outcomes of these experiments would provide crucial insights into the structural dynamics of the protein unfolding.   

Mutations on WFYY motif alters the PrimPol activity: Structural insights from atomistic MD simulations

PrimPol is a Primase and Polymerase enzyme with significance in reinitiating DNA replication

at stalled replication forks. The WFYY motif of PrimPol was previously reported to play an

essential role in stabilizing the incoming 3′-nucleotide. The W87G and Y90D mutations

significantly reduced the primase and polymerase activity of PrimPol. We have performed

microsecond scale molecular dynamics on wildtype, W87G, F88L, Y89D, and Y90D complexes

to investigate the structural implications of the single point mutations in PrimPol polymerase

activity. This study points towards the possible changes in the interdomain communication in

the PrimPol enzyme associated with single point mutations in the conserved motifs of the

enzyme.   

Molecular Mechanisms of Lipid-Induced Amyloid Fibril Formation from Global Fitting of Kinetic Models.

Elucidating the molecular mechanisms of amyloid fibril aggregation from soluble peptides is central

to building an understanding and the potential control of protein aggregation disorders, such as

Alzheimer's and Parkinson's diseases. A fundamental challenge in achieving this is the complexity of

the aggregation reaction network itself, which makes it difficult to analyse kinetic data of protein

aggregation in terms of the underlying mechanisms. Here we present a theoretical framework, based

on chemical reaction kinetics and global fitting, that allows the interpretation of quantitative

experimental measurements of α-synuclein aggregation on lipid membranes, a process linked to

Parkinson’s disease. These results provide a framework for modelling amyloid forming systems with

lipid-dependent interactions and has the potential to guide the rational design of small-molecule

inhibitors of α-synuclein aggregation.   

Deriving Effective Molecular Dynamics Potentials Using Iterative Boltzmann Inversion

Molecular dynamics (MD) is a powerful tool used to investigate protein folding and dynamics. The energy term in the Hamiltonian governing the dynamics of backbone dihedral angles has received a staggering amount of attention in recent years. Generally, with some exceptions, gas phase QM energy calculations are used to generate parameters of the dihedral energy functionals for a small group of amino acids, which are then shared among other amino acids. Recent work has demonstrated MD force fields which follow this template can not produce accurate amino acid residue-specific conformational dynamics in the unfolded state. We posit this can negatively affect computational studies of intrinsically disordered proteins (IDPs), which do not adopt a folded state and can be associated with diseases. Here, we attempt to modify the backbone dihedral parameters of glycine, the simplest amino acid, using a reference Ramachandran distribution derived from comprehensive set of spectroscopic data, which includes the effects of the aqueous environment, using the iterative Boltzmann inversion method. Improving the conformational dynamics of glycine will motivate a reparameterization of the dihedral terms for all amino acids using experimental data such that simulations can capture intrinsic conformational preferences of amino acid residues in water and potentially improve simulations of IDPs.   

Synergistic regulation of the Cdc42 GTPase cycle

Emergent properties of a system arise when  the systems parts interact in a wider whole. An example of such an emergent system is the cell division protein network of Saccharomyces cerevisiae. Here the cell division control protein Cdc42 accumulates in a single spot at the cell membrane. Cdc42 is a membrane-binding Rho-type GTPase and a highly regulated protein, it’s interacting with GEFs, GAPs, scaffold and other regulatory proteins.

To shine more light on the emergent properties of the system, we investigated a process at the centre of Cdc42: its GTPase cycle. We studied the entire GTPase cycle of Cdc42 in vitro and the effect of non-specific protein-protein interactions, the GEF Cdc24, GAP Rga2, scaffold protein Bem1, and combinations thereof, on it.

We developed a mathematical model to describe the GTPase cycle and characterise Cdc42's properties. The GEF Cdc24 exhibits cooperativity, and our data suggests that it synergises with Rga2. Surprisingly, we also found that non-specific protein-protein interactions positively affect the Cdc42 GTPase cycle. Taken together, our data suggests that Cdc42's GTPase activity is a dynamic property that is contingent on both specific and non-specific interactions with other polarity proteins, and the synergies arising from those interaction.   

Directed in vivo post translational modification in a different host

Post-translational modifications are an essential part of protein function. One modification that is particularly difficult to study is farnesylation. This modification adds a large hydrophobic chain to the protein, allowing it to interact with lipid membranes. It also unfortunately significantly lowers the solubility of the protein it is attached to. Studying this modification is particularly difficult in its native environment as they are generally associated with strongly binding cofactors (usually to counteract the effects of the hydrophobic modification). Here we show a method to not only express and farnesylate a protein in a non-native background, but we also discuss the methods for its purifications and characterization.

    

Cdc42 construct design for in vitro studies

Biological systems are complex by nature. To shine light on their inner workings, the multi-faceted lens of interdisciplinary research is required. One lens is the in vitro approach, in which the physical and biochemical properties and interactions of isolated components are investigated in detail. If the components are proteins, they need to be purified. This is generally done by attaching an N- or C-terminal purification tag to the protein of interest. The rational behind the placement of purification tags and their effect on the protein’s properties is rarely discussed, making in vitro studies less accessible to non-biochemists. Here, we explore the effect of protein construct design and purification tags on the S. cerevisiae protein Cdc42. Cdc42 is an essential small GTPase and the main regulator of polarity establishment and cell division in budding yeast. It’s part of a complex polarity protein network and highly regulated, making it an attractive target for in vitro studies. We show that the T7 lead is a requirement for the Cdc42 expression in the E. coli expression system and that purification tags can influence the expression and degradation levels of Cdc42-sfGFP and Cdc42-mNeonGreen sandwich fusions. Cdc42's GTPase activity, interaction with the GEF Cdc24 and scaffold Bem1 are largely unaffected by Cdc42's N- and C-terminal purification tags. The exception is Cdc42 tagged with an N-terminal Twin-Strep-tag, which shows precipitation issues and a decreased GTPase activity and Cdc24 interaction. We close with using the case of Cdc42 as an example for discussing criteria relevant for protein construct design in general.   

Characterization of HSP 70 chaperones using a solid-state nanopore Device

The heat shock proteins 70 (HSP70s) are produced by highly conserved genes that play an active role in diverse cellular processes including protein folding, disaggregation, and degradation. Using a solid-state nanopore device, proteins can be detected at a single-molecule level with high sensitivity to their volume, electrical charge, and shape information. This project aims to measure the HSP 70 chaperons using a solid-state nanopore sensing system for voltage dependence and pH dependence. Specifically, we intend to characterize archaeal chaperonin subtypes HSPα (TF56), and HSPβ (TF55) by measuring the ionic current blockages caused by this protein translocation through voltage-biased silicon nitride nanopores in an ionic solution. We plan to estimate the relative charge, shape, and size of protein molecules by the mean amplitude, the time duration, the integral of current blockages, and their distributions. In addition, we plan to further characterize these chaperons using atomic force microscopy and Dynamic light scattering.

    

Structure determination of moss PpCesA5 cellulose synthase trimer

Plant membrane proteins called cellulose synthases (CesAs) make cellulose, the most abundant plant polymer in the world found in plant cell walls. The cryo-EM structure of poplar PttCesA8 trimer has revealed structural insights, but an evolutionary context of CesA structure in other plant species is needed. The aim of my research proposal is to understand the role of plant CesA trimer oligomerization in functional cellulose synthesis and assembly. To approach this aim, I seek to characterize the structure of an early plant moss PpCesA5 in detergent and nanodiscs using SAXS/SANS and cryo-Electron Microscopy (cryo-EM). This structural analysis will provide information on residue-level oligomer interactions and global conformation of moss PpCesA5 trimers. Thus far, PpCesA5 has been successfully expressed in Sf9 cells. Current work involves optimizing the purification of higher order PpCesA5 oligomerization to capture this protein as a trimer and a hexamer of trimers. Future work involves an evolutionary structure comparison with poplar PttCesA8 and cotton GhCesA7 for insights on domains involved in oligomerization and function. This work reveals the importance of structural techniques such as cryo-EM to advance future work in biofuels and new biomaterials.   

Size-control of multiple structures with filament severing

Living cells contain a variety of cytoskeletal structures which serve specific functions related to their characteristic sizes and shapes. These structures are dynamic and assemble in a shared pool of their building blocks. Remarkably, cohabitating structures in this shared resource environment are able to maintain their specific size despite rapidly exchanging their building blocks in the shared pool. The mechanisms used by cells to enable this are not well understood. Here we consider the role of severing proteins in the assembly and size-control of coexisting structures. We study this process theoretically using master equations and with simulations. We statistically analyze the simulated length trajectories, and describe the probability distribution of lengths and the resulting length fluctuations as a function of different parameters of the theoretical model. Our study describes how severing proteins can aid in maintaining sizes of multiple competing structures in a pool of their building blocks

    

Designing a Singular Objective Light-Sheet (SOLS) Microscope for Visualization and Characterization of Cytoskeleton Networks

Light-sheet fluorescence microscopy (LSFM) has become a popular method for high resolution imaging of thicker (~>100??m) samples in biological research. Held in comparison to other high resolution imaging techniques, such as confocal microscopy, LSFM is notable for its low amount of photobleaching which increases the timescales over which samples can be imaged. In particular, one type of LSFM build termed a Single-Objective Light-Sheet (SOLS) has provided the ability to image samples mounted using traditional top down microscope slides, which was not possible in previous LSFM builds. The applications of this type of microscope are great in number, yet the build and alignment process of a SOLS microscope remains a complicated process, even for a user with a background in optical systems. Here, we present a simplified and reliable procedure for the construction of a modular SOLS lab microscope, thereby making this process accessible to researchers with minimal prior optics experience. We provide discussions on the advantages and disadvantages of using particular optical components over others, then design a step-by-step guide on how to construct and align a SOLS microscope using commercially available parts. After the build, we demonstrate the capabilities of the system by imaging in 3D reconstituted cytoskeleton networks and discuss future capabilities of similar systems.   

Length-control of Microvilli in Intestinal Epithelial cells

Actin structures called microvilli project from the apical surface of epithelial cells that line the intestines. Mature microvilli have precisely regulated lengths, and defects in microvillar lengths are associated with celiac disease. Studies using epithelial cells in vitro have determined that actin-binding proteins (EPS8 and NMIIC) are important for maintaining microvillar length, but how these proteins work together to maintain microvillar length are largely unknown. Here we study a theoretical model that describes molecular mechanisms mediated by proteins EPS8 and NMIIC, which can provide length-dependent feedback cues and control microvillar length. We study this process theoretically using stochastic simulations, and statistically analyze the simulated length trajectories. We describe the resulting probability distribution of lengths and the length fluctuations as a function of model parameters like the concentrations of EPS8 and NMIIC. Our study describes how actin binding proteins can work together to maintain sizes of these actin structures.   

Tuning the depolymerization and restructuring of actin networks via thymosin and cofilin

Actin is a key component of the cytoskeleton responsible for vital functions ranging from motility to structural support of cells. This multifunctionality is due, in large part, to the dynamic polymerization of actin monomers into semiflexible filaments, the depolymerization of filaments into monomers, and the changing lengths of filaments. Polymerization drives cell migration, while depolymerization and turnover mediate cell growth and restructuring. Thymosin-β4 and cofilin are two key actin-binding proteins that promote depolymerization by sequestering actin monomers or severing filaments, respectively.  Here, we incorporate thymosin and cofilin into entangled actin networks and visualize the subsequent in situ depolymerization and restructuring via confocal microscopy. We use fourier image analysis techniques to characterize the time-varying dynamics and restructuring of the networks and map their dependence on the concentrations of actin, cofilin and thymosin. Our results not only shed light on cellular processes that rely on actin polymerization and depolymerization, but also may inspire the engineering of non-equilibrium materials that leverage depolymerization as a route to dynamically transition from gel-like to fluid-like states.    

Pushing or pulling? A 2D model of the mitotic spindle.

The mitotic spindle is a microtubule-based subcellular apparatus that is responsible for segregating replicated DNA equally into two daughter cells. The placement of the daughter cells within a tissue is determined by the orientation of the spindle at metaphase, just before the DNA separates. In animal cells, spindle orientation is thought to be governed by forces that act on astral microtubules, which are those microtubules that grow towards the cell boundary (cortex), rather than the DNA. The canonical model for spindle orientation holds that motor protein complexes on the cell cortex exert a pulling force that reels the spindle into alignment. Less attention has been paid to a non-exclusive possibility, which is that spindle orientation relies on a pushing force generated by growing microtubules that hit the cortex. These models have proven difficult to distinguish using experimental manipulation. We are therefore building a minimalistic computational model in 2D to test how these possibilities could affect spindle dynamics and daughter cell positioning. Our preliminary results suggest that pushing forces are required for proper spindle positioning and angle alignment meaning that the canonical model is incomplete. Our ongoing work is to study the mechanism of microtubule-cortex interaction and the effects of cell shape and motor protein complex localization pattern on spindle orientation.   

Heterotypic Endosomal Interactions Drive Emergent Early Endosomal Maturations

Endosomes undergo a process of maturation as they progress through intracellular trafficking events. The most prominent model of early endosomal maturation involves a phosphoinositide driven gain or loss of specific proteins at the level of an individual endosome, but how this exchange is initiated is not understood. Here, we use Lattice Light Sheet imaging to track very early and early endosomes at the population level. We demonstrate that direct inter-endosomal contact drives the maturation from very early (APPL1 positive) to early (EEA1 positive) endosomes. Using fluorescence lifetime, we show that this endosomal interaction is underpinned by the asymmetric binding of EEA1 to early and very early endosomes through the C- and N-terminal, respectively. Thus, stochastic microtubule-mediated inter-endosomal interactions through EEA1 provides a mechanism to bring temporal and population level control to the process of endosome maturation. Our findings indicate that APPL1-to-EEA1 positive endosomal maturation is not a result of autonomous endosomal events but is driven via heterotypic EEA1-mediated endosomal interactions. These results support the intriguing proposal that the cell has evolved certain mechanisms to bound the variance of typically stochastic processes to ensure more deterministic trafficking outcomes.

    

Maximum Solubilities of Ergosterol and Stigmasterol in Various Lipid Membranes

The chemical structure of cholesterol is very similar to that of other sterols, such as bacteria sterol ergosterol and plant sterol stigmasterol. However, mammalian cells universally utilize cholesterol. Scientists have been wondering what makes cholesterol so unique that animal cells prefer cholesterol, not other sterols.  We recently measured the maximum solubilities of ergosterol and stigmasterol in various types of lipid membranes (DPPC, DOPC, POPC) using an anti-correlation light scattering technique. We found that cholesterol has the highest solubility in lipid membranes (~67 mole %) regardless the saturation of lipids, while other sterols have much lower solubilities.  Furthermore, ergosterol and stigmasterol have lower solubilities (15% - 22%) in unsaturated (DOPC) lipid bilayers and higher solubilities (40% - 55%) in saturated (DPPC) lipid bilayers. Our result shows that a small difference in sterol structure can result in a major difference in the behavior of sterols.  The uniquely high solubility of cholesterol is essential for cholesterol to perform its biological functions in mammalian cells.

    

Outer membrane crosslink density facilitates extracellular vesicle formation in E. coli

Bacteria produce small spheres of membrane known as membrane vesicles. Vesicles are likely produced through several different mechanisms, including the outward blebbing of the membrane. Blebbing of the bacterial membrane involves both structural changes to the membrane and separation of the membrane from the cell wall. Gram-negative bacteria, such as E. coli, contain both inner and outer membranes attached to an internal cell wall via protein crosslinkers. Past experiments have shown removal of the most prevalent crosslinker protein leads to an increase in vesicle production. Here we examine how the relative production of vesicles scales with the number of crosslinks between the outer membrane and the cell wall. Building off of prior theoretical work concerning the ability of a membrane to squeeze through holes in a cell wall, we model how the size of membrane regions detached from the cell wall influence vesicle production. Predictions from the model were tested via experimental measurements of vesicle production in bacteria with variable expression of crosslinker proteins. These results explain how proteins that attach the outer membrane to the cell wall regulate vesicle production.

    

Shape effect on interaction dynamics of tetrahedral nanoplastics and cell membrane

Cellular uptake of nanoplastics is instrumental in their environmental accumulation and transfers to humans through the food chain. However, the influence of the morphological characteristics of environmentally released nanoplastics is understudied. Using dissipative particle dynamics (DPD) simulations, we modeled the interaction between hydrophobic nanotetrahedra and a cell membrane, featuring high shape anisotropy and large surface curvature seen for environmental nanoplastics. We observe robust uptake of nanotetrahedra with sharp vertices and edges by the lipid membrane. Two local energy minimum configurations of nanotetrahedra embedded in the membrane bilayer were identified for particles of large sizes. Further analysis of particle dynamics within the membrane shows that the two interaction states exhibit distinct translational and rotational dynamics in the directions normal and parallel to the plane of the membrane. The membrane confinement significantly arrests the out-of-plane motion, resulting in caged translation and subdiffusive rotation. While the in-plane diffusion remains Brownian, we find that the translational and rotational modes decouple from each other as nanotetrahedra size increases. The rotational diffusion decreases by a greater extent compared to the translational diffusion, deviating from the continuum theory predictions. These results provide fundamental insight into the shape effect on the nanoparticle dynamics in crowded lipid membranes.   

Phase Separation Dynamics in Cell-Free Expression System

The cytoplasm is a multi-component mixture and exhibits phase separation, suggesting a role in spatiotemporal control of biochemical reactions. However, the effect of physical constraints on intracellular phase separation, such as confinement, molecular crowding, and viscoelasticity, is not fully understood. We study cytoplasmic phase separation in a bottom-up approach using a cell-free expression system (TXTL). TXTL is composed of an E. coli lysate, salts, and buffers including molecular crowder PEG. We demonstrate that phase separation of TXTL is driven either by dehydration or an increase in PEG concentration. When concentrating the mixture in a cell-sized emulsion, the system exhibit phase separation and partitioning proteins produced by simultaneous gene expression. Combining cell-sized confinement and bulk experimental analysis, we show the interplay of membrane wetting and viscoelasticity on cytoplasmic droplet formation.   

Chromatin decompaction modulates the liquid phase behavior in nuclei of living cells

The cell nucleus can be thought of as a living substrate that functions to store and process cells’ genetic material. The genetic material is not randomly stored, but instead is packed into a network of chromatin fibers, whose organization is linked to various phase-separated nuclear bodies. While the structure of chromatin has been extensively studied, it remains unclear how its biophysical organization and mechanical properties impact phase separation inside the nucleus. Here, we utilize a biomimetic optogenetic system to interrogate the role of the chromatin network on the liquid-liquid phase separation in the nucleus of a living cell. We tune the density of the chromatin network with a histone deacetylases inhibitor (HDACi) and drive phase separation by shining blue light to oligomerize the proteins in the nucleus. We demonstrate that phase separation can be strongly inhibited once the dense heterochromatin network is decompacted by HDACi. We further show that the intranuclear mechanical properties change, with a corresponding change in phase behavior, including changes in the size of the phase-separated droplets, and altered coarsening dynamics. Our findings highlight the importance of the material state of the chromatin network for liquid-liquid phase separation in the nucleus, and have implications for the biophysical regulation of biomolecular condensates.

    

Theory of chromatin organization maintained by active loop extrusion

The active loop extrusion hypothesis proposes that chromatin threads through the cohesin protein complex into progressively larger loops until reaching specific boundary elements. We build upon this hypothesis and develop an analytical theory for active loop extrusion which predicts that loop formation probability is a non-monotonic function of loop length and describes chromatin contact probabilities. We validate our model with Monte Carlo and hybrid Molecular Dynamics – Monte Carlo simulations and demonstrate that our theory recapitulates experimental chromatin conformation capture data. Our results support active loop extrusion as a mechanism for chromatin organization and provide an analytical description of chromatin organization that may be used to specifically modify chromatin contact probabilities.   

Multivalent binding proteins can drive collapse and reswelling of chromatin in confinement

Collapsed conformations of chromatin have been long suspected of being mediated by interactions with multivalent binding proteins, such as CTCF, which can bring together distant sections of the chromatin fiber. In this study, we use Langevin dynamics simulation of coarse grained chromatin polymer to show that the role of binding proteins can be more nuanced than previously suspected. In particular, for chromatin polymer in confinement, entropic forces can drive reswelling of collapsed chromatin with increasing binder concentrations. The reswelling transition happens at physiologically relevant binder concentrations and the extent of reswelling is mediated both by the concentration of binding proteins as well as the strength of confinement. We also study the kinetics of collapse and reswelling and show that both processes occur in similar timescales. We characterise this reswelling of chromatin in biologically relevant regimes and discuss implications for the spatial organisation of the genome.   

The effect of loops on the mean-squared displacement of Rouse-model chromatin

Many researchers have been encouraged to describe the dynamics of chromosomal loci in chromatin using the classical Rouse model of polymer dynamics by the agreement between the measured mean-squared displacement (MSD) versus time of fluorescently-labelled loci and the Rouse-model predictions. However, the discovery of intermediate-scale chromatin organization, known as topologically associating domains (TADs), together with the proposed explanation of TADs in terms of chromatin loops and loop extrusion, is at odds with the classical Rouse model, which does not contain loops. Accordingly, we introduce an extended Rouse model that incorporates chromatin loop configurations from loop-extrusion-factor-model simulations. This extended Rouse model allowed us to investigate the impact of loops and loop extrusion on the dynamics of chromatin. We show that loops significantly suppress the averaged MSD of a chromosomal locus, consistent with recent experiments that track fluorescently-labelled chromatin loci in fission yeast [Bailey et al., bioRxiv (2021)]. We also find that loops slightly reduce the MSD's stretching exponent from the classical Rouse-model value of 0.5 to a loop-density-dependent value in the 0.4-0.44 range. Remarkably, stretching exponent values in this range have also been reported in recent experiments [Bailey et al., bioRxiv (2021) and Weber et al., Phys. Rev. Lett. 104, 238102 (2010)].   

Biophysically informed modeling for mapping the effects of genetic and environmental perturbation on cell states

Improvements in single-cell genomics and scalable genetic manipulation have enabled the development of high-throughput, combinatorial perturbation experiments at single-cell resolution. Such advances present an opportunity to understand the impact of perturbations on the biophysics of transcription and resulting cellular states. However, current predictive models are largely phenomenological, limited to treating average expression levels, rather than causal mechanisms. Principled mechanistic analysis requires discrete, stochastic models of biological and technical noise. 

We develop a mechanistic, chemical master equation-based modeling framework for predicting perturbation responses in unseen conditions from single-cell datasets. Our approach fits biophysically meaningful models of transcription using splicing data available in these genomics experiments, parametrizing the cellular response by three kinetic rates as opposed to mean expression. We predict perturbation responses as changes in these parameters, which reveal the differential impacts of perturbations on molecular production and processing. This approach enables targeted, hypothesis-driven research on the causal properties of perturbations on cellular phenotypes, guided by mechanistically-grounded modeling.   

Targeted insertion of large genetic payloads using cas directed LINE-1 reverse transcriptase

A difficult genome editing goal is the site-specific insertion of large genetic constructs. We describe the GENEWRITE system, where site-specific targetable activity of Cas endonucleases is coupled with the reverse transcriptase activity of the ORF2p protein of the human retrotransposon LINE-1. This is accomplished by providing two RNAs: a guide RNA targeting Cas endonuclease activity and an appropriately designed payload RNA encoding the desired insertion. Using E. coli as a simple platform for development and deployment, we show that with proper payload design and co-expression of helper proteins, GENEWRITE can enable insertion of large genetic payloads to precise locations, although with off-target effects, using the described approach. Based upon these results, we describe a potential strategy for implementation of GENEWRITE in more complex systems.   

The nucleoprotein polymerization and nucleation on single-stranded DNA

RAD51 plays a key role in the homologous recombination process. We present a stochastic Monte Carlo lattice model to study how the polymerization of RAD51-RAD51 and the nucleation length distribution of bonded RAD51 on single-stranded and double-stranded DNA evolves over time. We will investigate how targeted RAD51 mutants could perturb the simulation parameters and how it will influence the outcome of the simulation model.   

Mechanical Basis for Epithelialization

Epithelial tissues are comprised of sheets of cells that shape animal bodies. The architecture and mechanical integrity of epithelial tissues underlies their function. Our work addresses the question of how physical interactions, such as cell density, stiffness, and cell-cell or cell-substrate connections, affect the development of epithelial tissue architecture. The role played by physical interactions in architecture development is difficult to study in vivo since tissue development is predicated on the existence of physical cell connections.  We developed a 2D computational model of epithelia in the plane perpendicular to most existing models of epithelia (such as vertex models), to investigate physical interactions in development. Our model simulates lateral cell surfaces as well as apical and basal tissue surfaces to investigate how physical interactions shape cell morphology. By using cell-cell border length as a readout, we find that a spatial constraint holding cells in proximity is required for the development of tissue architecture. We validated our in vitro predictions in experiments using cultured MDCK cells. Our work suggests that cell density is the primary factor in cell-cell border development and that cell-cell adhesion is subordinate. We are currently working to address the question of how physical constraints affect other epithelial processes.   

Stick-slip dynamics of crawling cells: nonlinear response of actin retrograde flow with varying substrate rigidity

Stick-slip motion, a common phenomenon observed during the crawling of cells, is found to be strongly sensitive to substrate stiffness. Here, we present a theoretical model for the stick-slip dynamics at the cell leading edge to investigate the nonlinear response of biphasic vs monotonic behaviour of the actin retrograde flow and cell traction force with substrate rigidity. Our model, based on a reaction-diffusion framework, incorporates known important interactions such as retrograde actin flow, myosin contractility, force-dependent assembly, and disassembly of focal adhesions integrated with the viscoelasticity of the cell-matrix system. Our study shows that the difference in cellular behaviours could arise due to the cell’s ability to sense and adapt to fast-varying forces. Our theory further elucidates how the substrate viscoelasticity alters these nonlinear cellular responses. Besides, it also predicts the loss of cell sensitivity to differentiate between soft and stiff substrates when the substrate viscosity is high and vice versa.

    

Interpretable models for transcriptional dynamics during cell fate transitions

Single-cell RNA sequencing experiments capture mixtures of cells at different physiological states, and enable the investigation of entire developmental trajectories. Current standard methods for fitting these trajectories typically rely on constructing cell-cell similarity graphs or high-dimensional functions, which have limited physical interpretability and do not provide directional information.

Seeking to construct firmer grounding for trajectory inference, we adapt concepts from stochastic biophysics and dynamical systems theory. To formalize the problem, we define a discrete model of RNA transcription and couple it to a sampling process. This approach yields a latent variable model, with RNA counts drawn from an occupation measure parametrized by kinetic rates. The latent variable model can be fit using the EM algorithm, providing biophysically meaningful parameters that characterize RNA production and processing during the developmental process. The framework generalizes to multimodal data, and reduces to current methods under particular simplifying assumptions. Compared to heuristic approaches, our model encodes a collection of concrete physical mechanisms, which facilitates statistical testing and provides guidance for further hypothesis-driven research.   

Cell plasticity in breast cancer evolution

Cancer is a disease driven by genetic and epigenetic instabilities that control and maintain aberrant signaling pathways. These aberrant behaviors are generated by accumulative mutations and epigenetic changes that allows uncontrolled growth and favor tumoral diversity of malignant phenotypes.  Here,  we study intrinsic cell components that contribute to its oncogenic phenotype using the collective molecular changes and  stochastic genetic alterations. For extrinsic cell components, we study the features related to microenvironmental variations that influence its phenotype perturbing the course of disease. We consider that molecular changes affect microenvironment and cellular function subjecting cells to stress due to the lack of sufficient glucose and oxygen. Likewise, we identify that the estrogens  play a major role in promoting the proliferation of both normal and cancer cells and the occurrence of breast cancer mutations. Finally, we incorporate these biological processes into a quantitative multiscale model to understand how microenvironmental conditions affect genetic dynamics and phenotypic diversity. Our results suggest that the evolution of malignancy and diversity in a tumor arise from and may be controlled by local cell plasticity. This supports the belief that control of local microenvironmental aspects could prevent tumor development and strongly suggest that it is possible to develop cancer treatment alternatives.

    

A Magnesium Tug-of-war Impedes Bacterial Antibiotic Resistance

Bacteria spontaneously generate ribosome variants that provide antibiotic resistance. However, such naturally occurring variants may also carry some physiological costs. We used modeling and quantitative experiments to investigate a spontaneously arising antibiotic-resistant L22 ribosomal protein variant (L22*) in Bacillus subtilis and determine its fitness cost. Specifically, elastic network modeling of ribosome conformational dynamics revealed that, compared to wild-type, L22* ribosomes associate more tightly with structural magnesium ions. Concurrently, quantitative single-cell experiments indicate that the L22* ribosome variant dominates a tug-of-war with ATP over a shared pool of magnesium ions, leading to reduced ATP levels. Consequently, growth of the L22* variant exhibits a higher dependence on extracellular magnesium availability, revealing a physiological cost. These data show that the association of magnesium ions with ribosomes regulates ATP activity. We postulate that such ion-based modulation may suppress antibiotic-resistant ribosome variants in bacteria that disequilibrate competition for magnesium ions.

    

Predicting phenotype to mechanotype relationship in cells based on intracellular signaling networks

We have developed a semi-quantitative-computational model to analyze the intracellular signaling network and how it impacts cellular mechanics in the presence of multiple external signals including growth factors, hormones, and extracellular matrix. We use this model to analyze the changes in cellular mechanics to external stimuli and identify the key internal elements of the network that drive specific outcomes within this phase space. The model is built upon Boolean approach to network modeling, where the state of any given node is determined using the state of the connecting nodes and Boolean logic. This allows us to analyze the network behavior without the need to estimate all the various interaction rates between different cellular components. However, such an approach is limited in its ability to predict network dynamics and temporal evolution of the cell state. So, we introduce dynamical aspects using mass-action kinetics as well as chemo-mechanical modulation of reaction rate constants at specific nodes of the Boolean network. Using this hybrid modeling approach, we provide a unique computational model to connect cells biochemical signaling profile to mechanical aspects of traction force generation, adhesion, and migration.

    

Resource allocation to cell envelopes and the scaling of bacterial growth rate

Although various empirical studies have reported a positive correlation between the specific growth rate and cell size across bacteria, it is currently unclear what causes this relationship. We conjecture that such scaling occurs because smaller cells have a larger surface-to-volume ratio and thus have to allocate a greater fraction of the total resources to the production of the cell envelope, leaving fewer resources for other biosynthetic processes. To test this theory, we developed a coarse-grained model of bacterial physiology composed of the proteome that converts nutrients into biomass, with the cell envelope acting as a resource sink. Assuming resources are partitioned to maximize the growth rate, the model yields expected scalings. Namely, the growth rate and ribosomal mass fraction scale negatively, while the mass fraction of envelope-producing enzymes scales positively with surface-to-volume. These relationships are compatible with growth measurements and quantitative proteomics data reported in the literature.   

The impact of growth rate on RNA-protein relationships in Pseudomonas aeruginosa

Our understanding of bacterial physiology during human infection is hampered by limited characterization of bacterial function in the infection site and a research bias towards in vitro, fast-growing bacteria. Recent studies have begun to address these gaps in knowledge by directly quantifying bacterial mRNA levels in human-derived samples using transcriptomics. However, mRNA levels are not always predictive of protein abundances, which are the primary functional components of a cell. Here, we assessed transcriptomes and proteomes of bacterial pathogen Pseudomonas aeruginosa (P. aeruginosa) using chemostats across four growth rates. We found a moderate genome-wide correlation among mRNAs and proteins across all growth rates, with genes essential for P. aeruginosa survival displaying stronger correlations than non-essential genes. We used statistical methods to identify genes whose mRNA abundances poorly predict protein abundance and calculated an RNA-to-protein (RTP) conversion factor to improve mRNA prediction of protein levels across strains and growth conditions. This study provides critical insights into infection microbiology by providing a framework for enhancing the functional interpretation of bacterial transcriptome data acquired from human infections.

    

Author not Attending

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Within the past decade, large strides in fluorescent microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent Chain Tracking (NCT), these methods elucidate translation dynamics lost by other investigatory techniques such as ribosomal footprinting or mRNA-seq; However, NCT has been limited to the observation of one or two mRNA species at a time within the same cell partly due to limits in the number of resolvable fluorescent tags. In this work, we present a hybrid computational pipeline where detailed mechanistic simulations produce realistic NCT videos and machine learning is used to assess experimental designs for their potential to resolve multiple mRNA species sharing a single fluorescent color. With careful application, this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a toy example NCT experiment with 7 different mRNAs species within the same simulated cell and use our ML labeling to label these spots with a 90% accuracy. The possibilities offered by this color palette extension will allow experimentalists access to a plethora of new experimental design possibilities -- especially for investigating cell signals that affect multiple mRNAs at a time.   

1H and 19F NMR Spectroscopy and DFT calculations to Investigate Tethering of Silver Nanoparticles (AgNPs) with Ofloxacin Antibiotic for Drug Delivery

Tethering of ofloxacin to the AgNPs via intramolecular bonding, forming ofloxacin-AgNPs combinations as a synergetic antibiotic compound is proposed. The ofloxacin-AgNPs combination was chosen as prototypical of the fluoroquinolone family tethered with metallic nanoparticles. The results of ¹H and ¹⁹F NMR chemical shifts, self-diffusion, spin-spin, and spin-lattice relaxation rates of the ofloxacin-AgNPs combinations confirm the intramolecular tethering via fluorine atoms and less significant the nitrogen atoms in the ofloxacin. Moreover, spin-spin and spin-lattice relaxation rates of the protons in methyl groups increased monotonically as AgNPs concentration increased due to the ionic and molecular arrangement in the sample medium. The tethering between metallic/metallic oxide nanoparticles with fluroquinolones antimicrobial is happened because of the hydrogen and coordination bonding between the nanoparticle surface and the fluorine atom as well as with hydroxyl group in the antimicrobial agent. The tethering alters the physicochemical properties of the system such as self-diffusion, viscosity, acidity, and molecular relaxation and ionic state of the buffer solution. The molecular dynamic simulations provide detailed insight into the dynamics of ofloxacin interaction with nanoparticle in aqueous solution. The calculated and the experimental NMR, UV-Vis and the thermodynamics parameters will be used to complete and validate the proposed molecular arrangements in the solvation shells in the vicinity of the AgNPs.   

In-silico investigation into nanoparticle formation, selective active compound delivery into cancer cells and transcytosis across the blood-brain barrier

Targeted delivery of drugs for the treatment of cancer is a major challenge. Current methods of treatment come with adverse side-effects arising from the lack of selectivity and growing resistance to these methods. This results in an urgent medical need to develop and optimise drug delivery vehicles that accumulate only at the target tissue. Using nanoparticles (NPs) to deliver chemotherapeutics has shown improved cellular uptake and selectivity towards cancer cells, reducing off-target effects. However, the mechanistic details of NP formation, drug cargo release, and selective delivery into cancer cells remain poorly understood. Here, we explore the delivery of polymeric NPs, loaded with a potent novel anticancer peptide, with the goal of improving the treatment for gliomas. We employ molecular dynamics (MD) simulations to assess the molecular-level details involved in the selectivity of these NPs for glioma cells in comparison to healthy brain cells, as well as the transcytosis of the NP across human brain microvascular endothelial cells (hBMECs), which comprise the blood-brain barrier (BBB). The simulations allow us to assess which factors contribute to the selectivity of NPs towards gliomas and the mechanisms behind their ability to cross the BBB.   

Investigating the correlation of PLGA polymer nanocomposites mechanical properties to stability and time-dependent cargo release for one-dose vaccine development

Nanomedicine, dependent upon delivery of therapeutic agents via nanocomposites, has proven effective in treating major diseases such as cancer and diabetes, and pathological processes including inflammation, vaccination, and microbial infection. The development of one-dose delivery of vaccines using nanomedicine is a particularly important focus. To enhance therapeutic efficacy of one-dose therapeutics, delivery systems must transport active agents to the target site in a stable and biocompatible manner at specific concentrations and be capable of time-specific cargo-release. We developed a tunable, stabilizer-free (poly (lactic-co-glycolic acid) (PLGA) nanocomposite formulation capable of encapsulating plasmid DNA and exhibiting timed release via changes in composition. We are investigating structural and mechanical properties of the PLGA nanocomposites using Dynamic Light Scattering, Atomic Force Microscopy, and Scanning Electron Microscopy to better understand the nature of the time-release activity and to enable the ability to specifically "tune" desired time-release properties. Results and correlations of mechanical and structural properties of PLGA nanocomposites to functional response will be reported.   

Design and Single Molecule Characterization of Dynamic DNA Origami Assemblies for Signal Transmission

While there has been much effort to miniaturize manufacturing methods of robotics to micron and millimeter scale, there are few approaches to integrate sensing, communication, and actuation at the nanometer to micron scale. In an effort to create new DNA-based nanoscale robotic materials, we have created a DNA origami structure designed to communicate signals over a distance of several microns, and to do so faster by several orders of magnitude than hybridization based dynamic DNA structures. Signal transduction assemblies can be triggered specifically at one end by an external stimulus, and we aim to communicate a signal through a sequence of conformational changes of dynamic modules within a filament assembly. To characterize this structure, we have used ensemble FRET and TEM microscopy as well single molecule TIRF microscopy of FRET and quenching systems to capture dynamic fluctuations of a single communication switch element (or oscillator).   

Motility-Induced Phase Separation in a chaotic environment

"Motility-Induced Phase Separation in a Chaotic Environment". In this project, we attempted to investigate the theoretical description of biological microswimmers and their active dynamics outside of homogeneous habitats. We used Brownian dynamics simulation to mimic bacteria as self-propelled particles (SPP) and direct numerical simulation to generate background cellular flow by solving incompressible Navier-Stokes equation using pseudospectral method. By post-processing the data, we explored the competition between mixing due to cellular flow and motility-induced phase separation. For the first time, we observed that when SPP motility dominates cellular flow, particles exhibit swarming behavior. We also observed that when the velocity of a turbulent flow is comparable to the velocity of SPP, particles accumulate in the region of strain dominating flow. A homogeneous mixture of SPP is another interesting result we acquired by maintaining the velocities of SPP to be much smaller compared to the background fluid which demonstrates that the turbulence is an effective mixer.   

An emergent property of collective migration: spatial organization of motility phenotypes

To invade new territories, groups of bacteria consume and collectively chase nutrients using chemotaxis. Though decades of quantitative studies have elucidated the dynamic of bacterial migration, how non-genetic diversity affects this dynamic is not fully understood. Collective migration requires coordination, but cells within a genetically-homogenous population exhibit diverse motility behaviors. Previous work in our lab demonstrated that how fast bacterial cells climb chemical gradients depends on their swimming phenotypes. As a result, cells are spatially organized based on their chemotactic performances; cells with higher performances lead at the front, where the attractant gradient is low, and cells with lower performances stay at the back, where the attractant gradient is high. While this was demonstrated in liquid, the same principle predicts that spatial organization of phenotypes is different in other environments. Here, we tested this prediction by measuring diffusions, chemotactic performances, and spatial organizations of motility phenotypes in populations that are migrating in porous environments. Our results will demonstrate that populations can leverage non-genetic diversity to migrate through multiple environments by altering their leader-follower structures.   

An effective hydrodynamic description of marching locusts and their local structure

The formation of locust swarms, one of the worlds’ most devastating insect plagues, begins when flightless juvenile locusts form “marching bands”. Marching through semi-arid habitats in search for nutrients and future breeding grounds, locusts show a remarkable example of coordinated motion, whose understanding can be of key importance for forecasting plagues’ progression. To better predict the movement patterns of the desert locust Schistocerca gregaria, we investigated how well movement of locust bands can be described by physical models and how they respond to external terrain restrictions (funnelling and splitting). To do so, locusts were recorded in the field negotiating obstacles and moving through funnels set up by the experimenters. Using automated video tracking, we then reconstructed individual trajectories of the locusts.  

We found that locusts show highly coordinated movement and, in analogy to a two dimensional fluid, exhibited stationary flow for long periods. The highly polarized flow of locusts showed consistency with the one dimensional version of the Toner-Tu equations, a generalization of the Navier-Stokes equations to describe a flow of active particles. The effective equation relates the gradient of the pressure to the acceleration and through this we found that the ‘pressure’ is roughly linear with the density at the segments with the highest polarization.

We further analyzed the topology of the group and found that the density of nearest neighbors around a focal individual is nearly isotropic once locusts’ body shapes are accounted for, indicating random arrangement of individuals. However, despite this apparent randomness we observe that there is some degree of local ordering in the radial distribution of densities. The radial distribution function in high density regions shows visible second neighbor peaks similar to that of an ordered fluid, supporting our fluid dynamics based approach.   

Characterization of swimming behavior of Daphnia magna in presence of a Dopamine agonist

 Daphnia are aquatic microcrustaceans often called water fleas. They are a commonly studied model organism in ecology, ecotoxicology and evolutionary biology. Daphnia swimming behavior is dependent on several factors like body size, light, water temperature, presence of food and predators. They propel themselves through liquid by periodically beating their second antennae in a breaststroke motion which results in directed motion. They can drastically change the direction of their movement by irregular motion of the second antennae.  Due to the complexity of their motion, the description of their locomotion has been largely qualitative and vaguely quantitative. Our study creates a granular level quantitative classification of baseline motion parameters in a swimming Daphnia. We further study the impact of a dopamine agonist in the swimming dynamics of Daphnia magna. Application of a D1-dopamine receptor agonist gives rise to a counter-intuitive beat pattern of the organism. We characterize these unique beat patterns of the antenna in untreated daphnids compared to daphnids treated with the agonist . Daphnia motion is studied using high speed imaging, two and three dimensional tracking techniques.    

Spatial patterning of mitochondrial metabolism in mouse oocytes

Metabolism provides a continuous flux of energy that keeps living systems out of equilibrium and gives rise to biological form and function. Energy production is patterned across space and time within cells via the organization of mitochondria and spatial distributions in mitochondrial activity. In mouse oocytes, there exists a gradient in metabolic activity with distance from the meiotic spindle. The physical mechanism that gives rise to this emergent pattern is unknown. I am using quantitative microscopy, molecular perturbations, and biophysical modeling to decipher the mechanism behind the formation of subcellular spatial patterns of mitochondrial metabolism in mouse oocytes. Understanding these mechanisms will not only teach us quantitative cell biological principles that underlie the patterning of energy metabolism but will also reveal the physics of how energy fluxes influence the collective behavior of living active matter.

    

Parameter-free and robust collective pattern formation of cell types in a bacterial biofilm

Multicellular organisms organize cell types in a segmented manner during development. In contrast, communities of unicellular organisms are not thought to be able to organize in such a sophisticated way. We recently found that a Bacillus subtilis bacterial biofilm organizes nitrogen stress response in a segmented pattern (Chou et al., Cell 2022). Mathematical modeling and genetic probing of the underlying circuit showed that this patterning is generated by a clock and wavefront mechanism, similar to that driving vertebrate somitogeneisis. Single cell tracking showed that individual bacteria oscillate in nitrogen stress response, creating segments as the biofilm expands. We showed that the clock and wavefront process spatially organizes distinct cell types in different segments of the biofilm. We now show that this patterning is parameter-free and robust against growth conditions. Biofilms grown in diverse conditions are capable of forming the concentric ring pattern, and the oscillation can be predicted in a parameter-free manner. Together, these findings reveal that a clock and wavefront mechanism organizes differentiated bacterial cell types in space and time, thereby challenging the paradigm that such patterning mechanisms are exclusive to plant and animal development.   

Bacterial structural features responding to environmental stress

Bacterial membranous structures have been reported to function as cell-to-cell communication and stress responses to alleviate a stimulated environment. Recently, the electron microscope was used to detect the membrane ultrastructure through pre-isolation of the exposed bacteria and the subsequent static observation, and the light microscopy resolved microscopic membrane dynamics without ultrastructural information. However, the insights of formation and morphologies of bacterial structural features at the nanoscale in native state was still lacked. Here, we developed a workflow of liquid-phase TEM imaging to investigate the bacteria membrane-structural changes in response to environmental stresses in magnetospirillum magneticum (AMB-1 strain). We found that the bacterial survive for a short period under the harsh environment, during which the bacterial changing its structure and morphology to defense against the external stress. The formation of outer membrane projections including outer membrane tubes (OMTs) and outer membrane vesicles (OMVs) are associated with stress conditions under electron irradiation. Our study suggested the notion that both of OMTs and OMVs are the stress inducing factors before the diderm bacterial lysed, and the bacterial stress response to environmental stimuli is one complex process with multiple reactions. We hope the developed TEM imaging under environmental conditions will be helpful in the growing field of studying bacterial membrane structures.

    

High-throughput CRISPR-based reconstruction of mutations along evolutionary trajectories

Evolution experiments in laboratories provide ideal systems to study evolutionary processes. Our lab has conducted a long-term evolution experiment with 96 yeast populations, independently evolving for around 14,000 generations. We see populations achieve similar phenotypic values. However, the evolved genotypes of the populations are quite different. Each population has its own trajectory, with stochasticity at the sequence level caused by forces such as mutation and drift. Yet, global patterns of declining fitness adaptation over time have been seen across all populations. Epistatic interactions between acquired mutations and the genetic background are also believed to influence evolutionary trajectories. These interactions have been proposed to make mutations less beneficial in fitter backgrounds. We aim to reconstruct mutations acquired along the evolutionary trajectory, in a variety of genetic backgrounds along the course of evolution. A recently-developed CRISPR-based method allows us to engineer many desired edits across the whole genome. We aim to study the effects of frequently observed, putatively beneficial mutations as well as their distributions of fitness effects. Using distinctly evolved lines from the experiment, we seek to answer questions about how adaptive mutations constrain evolutionary trajectories and better understand the relationship between highly beneficial mutations and the epistatic interactions they have with various genetic backgrounds.   

Elucidating the genome wide consequences of rewiring the yeast polarity network

Polarity establishment plays an important role in biological functions that are observed throughout the tree of life. In the budding yeast Saccharomyces cerevisiae a polarized spot of the evolutionary conserved protein Cdc42 marks the position of new bud formation, making polarity establishment an essential part of the cell cycle. Due to its role as a model organism, many of the proteins that are involved in regulating the polarized distribution of Cdc42 have been identified in S. cerevisiae. Interestingly, the effects of losing a protein considered to be central in polarity establishment (Bem1) can be compensated during evolution by the subsequent deletion of two other proteins (Bem3 and Nrp1) rather than requiring the emergence of a new protein that takes over the lost function. This suggests that other proteins in the cell have changed their interaction profile to buffer the polarity defects by establishing an alternative pathway for Cdc42 polarization. Here, we use a recently developed transposon mutagenesis assay for yeast to uncover the key players in this alternative pathway based on their altered essentiality after the deletion of Bem1, Bem3 and Nrp1. We find that the evolutionary repair of polarity establishment has consequences for a diverse set of cellular processes seemingly unrelated to cell polarity. Surprisingly, we observe that the reorganization of the polarity network not only leads to an increased essentiality, but also an increased dispensability of genes related to these processes.   

Accumulating mutations lead to frequent adaptation of non-genic loci and de novo gene birth

Over evolutionary timescales, genomic loci switch between functional and non-functional states through processes such as pseudogenization and de novo gene birth. Here we ask about the likelihood and rate of functionalization of non-functional loci. We simulate an evolutionary model to look at the contributions of mutations and structural variation using biologically reasonable distributions of mutational effects. We find that a wide range of mutational effects are conducive to functionalization, thus indicating the ubiquity of this process. Interestingly, in the special case of  de novo gene birth, whereby non-functional loci begin to express a functional product, we find that expression level changes lead to rare, extreme jumps in fitness, whereas sustained adaptation is driven by product functionality. Our work supports the idea that the potential for adaptation is spread widely across the genome, and our results offer mechanistic insights into the process of  de novo gene birth.

    

A minimal in vitro system for cell polarization

Polarity establishment is an evolutionary conserved mechanism for a cell to directionally redistribute proteins in order to divide, migrate, differentiate and grow. We know that yeast cell polarity is established by an accumulation of active Cdc42, a small Rho-type GTPase protein, on the membrane with enhancement of activating protein Cdc24 and scaffold protein Bem1. The interactions between these partially disordered proteins, membrane binding, crowding, and lipid dynamics drive the system towards polarization. Yet, we do not understand how these properties relate to the pattern formation that initiates polarity establishment. We have established all components to reconstitute Cdc42 based polarization: the three protein constructs with fluorescent tags and a 2D lipid bilayer. We are characterizing the membrane binding dynamics of our proteins through FRAP and TIRF microscopy and through a quartz crystal microbalance. We will induce binding of our proteins on the membrane through crowding agents. The combination of intrinsically disordered regions in the proteins and together with crowding effects should drive the system into a phase transition that could lead to polarization establishment. We also model these dynamics with a stochastic, reaction-diffusion based Gillespie simulation. Through a combination of experiments and modelling, we aim to get a better understanding of how single-molecule dynamics as well as collective dynamics lead to the pattern formation that initiates cell polarity.

    

Pattern propagation driven by surface curvature

Pattern formation and dynamics on curved surfaces are abundant in biological systems. Although past studies have revealed that surface curvature affects pattern dynamics and plays biological roles, a comprehensive understanding is still lacking. In this presentation, we report a novel mechanism of pattern propagation driven by surface curvature. By employing reaction-diffusion systems exhibiting Turing pattern on curved surfaces, we show for the first time that static patterns on a flat plane can propagate on a curved surface. Numerical and theoretical analyses reveal that the symmetry of the surface and pattern are involved in conditions for the pattern propagation.   

Quantifying grooming in paired macaques

Quantitative tools are increasingly being used to study social interactions in natural, freely moving contexts. However the development of such tools for primate research has lagged behind that of other animals. To understand primate sociality, we need to measure how behavior varies as a function of the environment, social contexts, and bodily movement. Here, we present MacTrack (Macaque Tracking), a holistic behavioral tracking system which uses deep learning-based landmark tracking to predict the location of 134 landmarks (68 facial, 24 body, and 21 per hand) of interacting rhesus macaques. Using unsupervised learning, we find strong similarity between postures across behavioral tasks and social contexts and reveal novel, segregated behavioral motifs corresponding to previously indistinguishable behaviors (i.e., face groom vs. limb groom). Moreover, we explore how administration of oxytocin, a neuropeptide linked to social bonding and affiliation, impacts allo-grooming in opposite-sex pairings. We show that oxytocin dosages result in a greater number of grooming bouts and that, prior to grooming solicitation, monkeys in successful and unsuccessful grooming bouts display different behavioral phenotypes. By combining primatology and machine learning, this work advances our understanding of the macaque behavioral repertoire, with potential implications for understanding the building blocks of complex behaviors in humans.   

Cell-free action potentials as a dynamical system

Action potentials, voltage spikes in the neuron, play an essential role in biological communication.  This unique analog/digital dynamical system has been the subject of extensive study, yet until recently action potentials have not been generated outside the living cell.  By constructing a dressed down system using only the essential biological components (lipid membrane, voltage gated ion channels, and an ionic gradient), we are able to generate and regulate action potentials in vitro.  The system is modeled using a mean field approach to explore the available types of behavior within the phase space.  These simulated results are used to guide our experimental implementation, and we demonstrate that our artificial excitable system is capable of producing much of the same dynamics as measured in real neurons.

    

One nose but two nostrils: interaction between two hemispheres aligns bilateral responses

Odors are detected by olfactory receptor neurons in the nose, which project to the ipsilateral olfactory bulb (OB). Each olfactory cortex on one hemisphere receives olfactory information from ipsilateral OB, plus contralateral information from the other hemisphere cortex. Since the projection from OB to cortex is largely random, odor representations in two cortices are presumably independent. Surprisingly, experiments in mice showed that the two representations are aligned, suggesting the inter-hemispheric projections must be structured. But how such structure emerges remains an enigma. 

We hypothesized that the inter-hemispheric projections are plastic and are shaped by constant experience of different environmental odors. Then we modeled this online learning process with local Hebb's rule, and found that: bilateral alignment of odor representations can be achieved; with larger OB to cortex expansion ratio, the projection can be sparser. Further, we found a power law with exponent 1/2 between alignment quality and projection sparsity. A theory was developed for the (unique) Hebbian solution, and explained two scalings.

To explore the landscape in larger parameter space, we optimized an alignment loss function over projection matrices, with global stochastic gradient descent (SGD) update rule. We showed that SGD outperforms Hebb’s rule and may find perfect alignment solutions. This difference between local Hebbian and global SGD rules, and their connections, may be understood analytically.

    

Frameworks for understanding goal-directed agents

E. coli networks, as a model organism, can respond to a variety of input. E. coli's preferred food source is glucose, but if glucose is absent, E. coli is able to consume lactose instead by producing the protein lactase. To optimize the production of lactase, an E. coli network should predict its environment rather than just respond to it. The model of mRNA transcription in E. coli used in this research can be used to predict complex stimuli, such as naturalistic video. If a simple unicellular organism can do model-based reinforcement learning, it might be capable of other kinds of reinforcement learning. We therefore look to lessons from lower-level organisms for future reinforcement learning directions.   

Kinematic Trade-offs in Elastic Mechanisms

Elastic spring mechanisms are used both in biology and robotics to drive ultra-fast movements that outperform direct muscle-driven or motor-driven systems. One challenge in comparing the kinematic performance of spring-driven versus motor-driven systems is the many ways in which performance can be measured - e.g. maximum velocity, take-off duration, and maximum power output. We explored trade-offs between these different metrics of kinematic performance using a simplified model for both spring-driven and motor-driven systems. We found that hybrid systems with a motor and spring in series can balance trade-offs between high velocity and short take-off duration. Surprisingly, we found that tuning the stiffness of the system's spring to maximize stored elastic energy does not necessarily maximize the power output. These results suggest that the design of elastic mechanisms can be fine-tuned to optimize specific performance objectives.   

Horizontal Burrowing in Granular Media by Breaking Symmetries

Self-burrowing robots are a class of robot that can move underground. These robots can find applications in geotechnical site investigation, sensor deployment, save and rescue, and construction. Breaking the symmetry is believed as the key to burrowing in the granular medium. In this study, we proposed, fabricated, and tested burrowing robots with a minimalistic and modular design. The robot mainly consists of a tip (flat, cone, or auger), and a pair of cylindrical parts. The robot can achieve extension-contraction with the utilization of a linear actuator and have options for tip rotation with an embedded gear motor. With the flat tip, the robot was almost symmetric and had reciprocal kinematics, so it could hardly move. With a cone tip, the robot was no longer symmetrical, and it could move horizontally through cyclic extension-contraction. Introducing cone tip rotation during the extension period breaks the symmetric kinematics and could increase the burrowing speed of the robot. The burrowing speed was the highest for the robot with an auger tip that rotated during the extension period. All the asymmetries contributed to the difference in resistance during the robot movement. A generic load-displacement-based model was proposed to quantify the effect of asymmetries and predict the movement of developed burrowing robots.

    

Dynamics of Morphogenesis in a Giant Single-Celled Organism Feeding on Light

In developmental biology the emergence of macroscopic pattern and morphology is commonly studied as a consequence of cell-to-cell interaction. However, there are macroscopic cells which exhibit organ-like regions, while having a shared cytoplasm throughout, thus presenting a challenge to this paradigm.

Here we study dynamics of morphogenesis in Caulerpa. It is a marine green alga consisting of differentiated organs resembling leaves, stems and roots. While the individual can reach meter-long scales, it is a single multinucleated giant cell.

We track over weeks algal segments regenerating under various illumination protocols.  The main control parameters are the temporal-pattern and -average of the photon flux. Caulerpa is a photo-autotroph, hence light also plays the role of a main energy source. Using Active Contours, we study the time evolution of curves delineating the two-dimensional projection of the samples. 

Studying this seemingly primitive light-fed Homeostatic System offers an opportunity to explore relationships among morphogenesis, time-restricted feeding, and anticipatory behaviour.   

Standard Lagrangians in Population Dynamics: New Physical and Biological Insights

The Lagrangian  formalism is developed for the population  dynamics of interacting species that are described by several well-known models. The formalism is based on standard Lagrangians, which represent differences between the physical kinetic and potential energy-like terms. A method to derive these Lagrangians is presented and applied to selected theoretical models of the  population dynamics. The role of  the derived Lagrangians and the energy-like terms in the population  dynamics is investigated, and it is shown that the obtained standard Lagrangians can be used to study oscillatory behavior of the models and  the period of their oscillations.These and other physical and biological insights gained

from the derived standard Lagrangians are discussed   

Magnesium mediates local and global conformation changes of the 2'-deoxyguanosine riboswitch

In prokaryotes, 2-3% of the genes were found to be regulated by a class of mRNAs named riboswitches, usually residing in 5' untranslated region of genes, and control expression mainly by premature transcription termination or inhibition of translation initiation via binding to certain metabolite. To date, a family of purine-sensing riboswitches, which share similar secondary and tertiary structures, have been discovered and studied for their structures and mechanistic basis of gene regulation. The 2'-deoxyguanosine (2'-dG) riboswitch is classified as a close variant of the guanine-sensing riboswitches. When it binds the 2'-dG molecule, it induces the termination of the transcription process. Thus, it is important to understand how the ligand-binding region (aptamer domain) of the riboswitch is affected. In general, positively charged metal ions (specially Mg²⁺) aid in neutralization of the highly negative RNA backbone, permitting the formation of complex bends, folds, and long-range contacts characteristic of complex RNA structures. In this work, we used explicit solvent molecular dynamics simulation and explored the combined effects of ligand binding and Mg²⁺ on the 2'-dG riboswitch at atomic level. We revealed how the absence of ligand and Mg²⁺ weaken the terminal P1 helix and lead to conformation transformation, and how ligand binding and Mg²⁺ affect the stability of other secondary and tertiary motifs of the riboswitch that may also contributes to the reorganization of the riboswitch. The findings are also supported by our SHAPE (Selective 2' Hydroxyl Acylation analyzed by Primer Extension) probing experiments.   

Effects of the Structure of Lipid-based Agents in their Complexation with a Single Stranded mRNA fragment as studied by Molecular Dynamics Simulations

Fully atomistic molecular dynamics simulations are employed to compare the propensity of two groups of lipid-based agents to form structurally and energetically stable complexes with an mRNA fragment in an aqueous environment. The first group is comprised of cationic ionizable agents while the second includes amphoteric phosphatidylcholine lipids. The effects of various factors on the kinetics of their self-assembly as well as on their complexation with RNA are examined. Characteristic timescales for the realization of each process are provided. The role of the structural details and of the charge of the lipid-based agents on the morphology and the composition of the clusters formed, as well as on the preferential conformation of the mRNA chain with respect to the clusters are explored. The energetic affinity of the examined agents with mRNA is assessed and the role of the different kinds of interactions in the complexation process is determined. By combining information from the analysis of static, dynamic, and thermodynamic properties of the formed complexes, attributes that are mostly relevant to each stage of the lipid-lipid and the mRNA-lipid association are highlighted, providing thus new insight towards the efficient design of lipid-based formulations for RNA delivery.

    

Supervised learning speeds up parametrization of chromatin simulations

The physical organization of the genome in three-dimensional space regulates many biological processes, including gene regulation and cell differentiation. Given the complexity of biological systems, molecular modeling of chromatin structure provides essential insight into the factors driving genome organization. A common modeling approach is to parametrize a polymer model using an experimental Hi-C contact map as a constraint. Existing approaches in this framework leverage the maximum entropy principle to optimize the polymer model parameters. The maximum entropy approach requires running simulations iteratively until the parameter values converge, which is computationally expensive. Here, we show that supervised machine learning enables dramatically faster parametrization of chromatin simulations. We train a graph neural network to predict polymer model parameters from experimental Hi-C contact maps by training on simulated contact maps with known parameters. Our approach is comparably accurate to the maximum entropy approach, but at a fraction of the runtime. We anticipate that our method will be particularly applicable to the single-cell setting, as single-cell Hi-C variants can generate thousands of Hi-C contact maps.   

Importance of Sugar–Phosphate Backbone and Counterions to First-Principles Modeling of Nucleobases

DFT-based first-principles calculations were carried out to understand the electronic structure difference among a backbone-free nucleobase, a backbone-containing Na counterion nucleotide, and a backbone-containing H counterion nucleotide and their difference in the adsorption on graphene and on graphitic-carbon nitride. The study discovered that the inclusion of a sugar–phosphate backbone changes the electron affinity of most nucleobases from electron acceptors to electron donors. The methyl-terminated backbone-free model cannot replicate the steric effect induced by the sugar–phosphate backbone during the adsorption of nucleobases on 2D materials. Overall, we established that the sugar phosphate backbone should be included in the study of DNA nucleobase adsorption on 2D material. We also showed that when it comes to the adsorption on 2D materials, the backbone-containing H counterion model is superior to the Na counterion model because the Na counterion produces a LUMO near the Fermi energy, which may significantly affect the interaction with the 2D material.   

Coarse-grained RNA Simulations with Concerted C2'/C3'-endo Sugar Pucker Transitions

All-atom molecular dynamic simulations are generally restricted by the time scale that can be sampled. To address this issue, various coarse-grained RNA models have been developed. These models often assume the ribose, a 5-membered ring, is fixed in only one conformation, typically the C3’-endo found in A-form helices. The models neglect the C2’-endo conformation found in B-form helices and other RNA structures and are known to influence ion binding and catalytic function in addition to secondary structure propensity. Accordingly, we have developed a coarse-grained RNA force field to include transitions between the two sugar pucker states in order to accurately reproduce RNA structures and thermodynamics. To model the sugar pucker, we train a coarse-grained collective variable that distinguishes between the two states. Using this collective variable, we interpolate between two sets of force field parameters to reflect the structural differences between the two conformational states properly. The parameters of the entire model are optimized against RNA structures utilizing our contrastive divergence algorithm. Our coarse-grained RNA model opens up the opportunities to study complex RNA dynamics especially those coupled to sugar pucker transitions.

    

Bacterial replication initiation as precision control in biology

Replication initiation in bacteria is one of the most precise physiological controls in biology.  Curiously, E. coli produces more than one order of magnitude larger number of DnaA proteins than needed, the widely conserved master regulator proteins in bacteria. More than 90% of the DnaA proteins are titrated by 300 binding sites encoded in the chromosome known as the DnaA boxes. In this work, we demonstrate that the number of DnaA boxes is optimal for initiation noise reduction and far more effective than autoregulation of DnaA production. We developed several novel experimental methods to control the number of DnaA boxes. As we increase the number of DnaA boxes, initiation is delayed steadily. However, the initiation noise (measured by CV) shows a non-monotonic behavior with the minimum at the wild-type number. We propose a model based on the DnaA flux to explain our results. We further discuss general implications of our results for precision control in biology.   

Noisy production and epigenetic feedback of a cell polarization protein in budding yeast

As gene expression involves interactions between relatively small numbers of molecules, it is prone to fluctuations. Indeed, it has been shown that protein concentrations may vary considerably between cells and within the same cell over time. Although noisy gene expression is often detrimental and selected against by evolution, it can be beneficial in some cases, since it diversifies the population. A mechanism of epigenetic feedback could enhance the positive benefits of noise by allowing lucky individuals to pass on their state to the offspring, bringing about a temporary selective advantage. We investigate this phenomenon in budding yeast by examining population distributions of the cell polarization protein Cdc42. The noisy production of this protein leads to variability in cellular Cdc42 concentrations between cells. In certain genetic backgrounds, lucky cells possessing a high Cdc42 concentration will divide faster than cells with a low concentration. Moreover, their daughter cells should get a head start in their own cell cycle because they partly inherit the Cdc42 concentration from their parents. By measuring and modeling population distributions of Cdc42 in different conditions, we aim to characterize the effects of noisy production and epigenetic feedback on population fitness and the possibility of bridging fitness gaps in the course of evolution.

    

Electromagnetic Effects on Bacterial Growth

Microbial infections are increasingly more difficult to treat due to the development of antibiotic resistance, prompting research into non-pharmaceutical methods for controlling the spread of bacteria. Electromagnetic fields (EMFs) have been shown to inhibit growth and induce structural changes in bacteria. We use a mathematical framework to describe the formation of bacterial cells and altered physiological processes caused by exposure to EMFs. In this study, we examine how weak magnetic fields influence stress responses and the electrochemical processes that govern cellular biosynthesis in common Gram-positive and Gram-negative bacteria.   

Impact of spectrally separated light on Rhodobacter sphaeroides

     There is a fine balance between the amount and type of light needed for efficient photosynthesis before oxidative stress and photodamage occurs. In addition, many organisms are able to prevent excess light energy from reaching their photosynthetic active sites as a protection strategy. However, this homeostasis is not clearly understood and there are many remaining questions in how wildly fluctuating energy from the environment is efficiently moderated to a usable form without complete disruption of photosynthetic systems, especially under ever changing conditions due to climate change. Although much research has focused on the stress response of plants to excess light, there is a lack of research quantifying how organisms are affected by and adapt to different wavelengths, intensities, and overall incident spectra of light. Photosynthetic microbes are a prime target for such studies because of their relatively simple photosynthetic apparatus compared to plants, ease of manipulation in mutagenesis experiments, and the overall simplicity of experimental design when working with a single celled organism. 

     By utilizing a spectrally separated supercontinuum laser light source aimed at a “Bacteria Farm” system, developed by Mehmet Kilinc, a physics graduate student in Dr. Nathan Gabor’s research group, we grow bacterial cultures under predefined wavelengths and power. From these growths, we quantify the response of R. sphaeroides to wavelength and intensity of light through differences in the transcriptome of R. sphaeroides resulting from energy exposure. RNA-sequencing is conducted using Illumina’s HiSeq platform after rRNA depletion in order to perform a deeper analysis of the metatranscriptome under each light condition without interference from ribosomal RNA. This project begins to help identify essential genes in light stress response aimed at testing the idea that photosynthetic systems have evolved to suppress power fluctuations rather than maximize energy absorption. Analyzing the transcriptomic profile of R. sphaeroides under different energetic fluctuations will characterize the mechanism through which this bacterium adapts and responds to spectrally and intensity-separated light in order to utilize available light energy efficiently.

    

Self-organization as a buffer for evolution, using cell polarity in budding yeast as a model

The successful survival and proliferation of living cells is based on incredibly complex networks consisting of large numbers of mutually interacting proteins. Core cellular functions maintained by these networks are typically highly robust against mutational perturbations. How the evolutionary robustness of core functions is established remains an open question. As a concrete model system, we study polarization in the budding yeast Saccharomyces cerevisiae. Polarization in budding yeast is centered around the small Rho GTPase Cdc42, whose accumulation on the membrane drives cell budding at a single site. The polarization machinery in yeast has previously been shown to be highly resilient to genetic perturbations: crippling of the network by deleting a near-essential scaffold protein gene (BEM1) is followed by a reproducible evolutionary trajectory, in which subsequent inactivation of several related genes in the network recovers near wild type fitness levels.

We propose that evolutionary resilience of functional protein networks is facilitated by self-organizing properties, i.e. the idea that the components of a network can reactively change their behavior and mutual relationships to provide a buffer against perturbing effects. Thus, we expect that mutational perturbations are countered by a collective response of the network, as opposed to e.g. direct functional compensation by another similar network component. To test our hypothesis, we will experimentally map out the behavior of a set of core polarization proteins in space and time along the evolutionary trajectory described above by means of high throughput fluorescence microscopy. Furthermore, we seek a novel paradigm to describe how self-organizing properties of the polarization network can facilitate evolutionary resilience. To this end, we will explore whether multicomponent phase separation of polarization proteins can be a relevant framework to describe the behavior of the system and its evolution.   

Spindle dynamics and orientation depends in forge generators configuration

During cell division, the mitotic spindle forms inside cells and segregates chromosomes. The spindle's position sets the division plane, which is essential for proper growth and development. Force mechanisms regulating the position of the spindle are not yet understood. Here, we develop a coarse-grained model of spindles in cells, which accounts for microtubule dynamics, pulling forces from cortically bounded motor proteins, and fluid drag. We show that the spindle's resistance to rotation is largely driven by pulling forces from the motor proteins rather than the drag imposed by the cytoplasm. We also show that the arrangement of motor proteins affects the spindle's resistance to rotation for configurations where multiple motors stack at the same region, the spindle's resistance to rotation significantly reduces. Our findings are consistent with measurements in human tissue culture cells, where the spindle resistance to the rotation has been quantified.   

Decoding p38-Mediated Stress Response in Human Cells Using a Novel FRET Sensor

The p38 signaling pathway is the lesser understood of the three major MAPK signaling pathways in mammals, and its dysregulation is a factor in a multitude of immune disorders, cancers, and inflammatory diseases. p38α, the most ubiquitously expressed member of the p38 MAPK family, is activated by dual phosphorylation of a Thr-Gly-Tyr motif. This relatively simple activation mechanism somehow results in a complex and nuanced differential activation of several transcription factors appropriate to the activating stress that regulate differentiation, apoptosis, inflammatory response, etc. 

Through real time imaging of a FRET based p38 reporter in vivo and Hoechst nuclear staining, we have demonstrated that human cells respond to various stresses with unique changes to p38 activation state, localization patterns relative to the nucleus, and dynamics spanning several hours. Our aim is to decode stress response in human cells and potentially identify behaviors that would prove useful for medical research. Further experimentation with HIV-associated and SARS Cov-2-associated proteins could also provide unique insights into how these diseases affect immune response.    

Listening to nuclear membrane

Fluctuations of nuclear membranes are detected with exceptional resolution. The motion of localized membrane (   

Analysis of the dynamics of the growing and branching network of filamentous fungus Podospora anserina.

The success of filamentous fungi in colonizing most natural environments can be largely attributed to their ability to form an expanding interconnected network, the mycelium, or thallus, constituted by a collection of growing hyphal apexes producing hyphae and subject to branching and fusion. In this work, we characterize the hyphal network expansion and the structure of the filamentous fungus Podospora anserina under controlled culture conditions. To this end, temporal series of pictures of the network dynamics are produced, starting from germinating ascospores (1 node) and ending when the network reaches thousands of connections. The completely automated image reconstruction steps allow a post-processing and a quantitative analysis of the spatio-temporal dynamics. Taking advantage of the network's properties we can numerically identify each individual hypha and its nature (apical or lateral). With this method we plan to discriminate hyphal fusion (anastomoses) from mere overlapping. Thanks to the reconstruction of each hypha, we can analyse the growth of the network at both local and global scale.   

A novel electrical device demonstrates localized stimulation triggers cell-type-specific proliferation in biofilms

Biological systems ranging from bacteria to mammals utilize electrochemical signaling. While artificial electrochemical signals have been utilized to characterize neural tissue responses, the effects of such stimuli on non-neural systems remain unclear. To pursue this question, we developed a novel experimental platform that combines a microfluidic chip with a multi-electrode array (MiCMA) to enable localized electrochemical stimulation of bacterial biofilms. The device also allows simultaneous measurement of the physiological response within the biofilm with single-cell resolution. We find that stimulation of an electrode locally changes the ratio of the two major cell types comprising Bacillus subtilis biofilms, namely motile and extracellular matrix-producing cells. Specifically, stimulation promotes the proliferation of motile cells, but not matrix cells, even though these two cell types are genetically identical and reside in the same microenvironment. Our work thus reveals that an electronic interface can selectively target bacterial cell types, enabling control of biofilm composition and development.   

Bio-inspired Helical Burrowing Robots in Granular Media: experimental observations

Erodium seed awns are moisture sensitive. They coil and uncoil in response to the humidity change in the environment. This coiling-uncoiling motion drives a seed to bury itself like a corkscrew. We present a seed-awn inspired self-burrowing robot which is driven by two augers and stabilized by a fin structure in between. Its burrowing behavior was investigated in the laboratory. Different combinations of auger geometry (handedness, pitch) and control strategies (rotational speed and direction) resulted in different burrowing speeds. To unify the observed burrowing behaviors, the propulsive and resistive forces were examined using additional thrusting and dragging tests. It is observed that rotation of an auger not only reduces the resistive force, but also generates a propulsive force, which depends on the auger geometry, the rotational speed and direction. The burrowing behavior of the robot can thus be predicted from the geometry-rotation-force relations.

    

DEM-MBD Coupled Simulation of a Burrowing auger-shaped Robot in Dry Sand

This study demonstrates the application of a coupled discrete element method (DEM)

– Multi-body Dynamics (MBD) framework in simulating the self-burrowing behavior of a robot in dry sand. In robotics, a robot can be modeled using MBD, in which each component of the robot is modeled as interconnected rigid or flexible bodies whose motions obey the laws of motion and are limited by kinematic constraints. In this study, DEM is coupled to MBD using Chrono – an open-source physics engine – to model the self-burrowing behavior of a two-auger robot in dry sand. The self-burrowing robot consists of two horizontal augers that are connected using two motors defined in DEM. A typical co-simulation loop starts with the DEM module that solves the inter-particle and particle-structure forces and displacements; the particle-structure forces are then transferred to the MBD module to solve the dynamics of the robot; the updated kinematics information is then transferred back to the DEM module. The design of the augers and the geometric parameters was studied to better understand the effect of geometry on the driving force of the robot. The values of the pitch ratio of the shaft and cone were changed to comprehend the effect of the blades of the augers on the self-burrowing driving force.

    

Experimental study on the reduction of penetration resistance by rotation

Numerous organisms live with or within the soil, and some have evolved efficient strategies to move within soil. Seeds of the Erodium cicutarium and Pelargonium can bury themselves into the ground for future germination with a continuous rotational motion. Worm lizards tunnels by oscillating their heads along the long axis of the trunk. It is believed that the penetration resistance of a penetrator could be reduced by incorporating the rotational movement during the penetration process. A holistic experimental campaign was conducted to reveal the correlations between rotational penetration resistance and its influence factors. The results indicate that the reduction of the penetration resistance increases significantly at first and then gradually with the increase of the relative slip velocity (the ratio between the rotational velocity and the vertical velocity), the roundness of the penetrator, and the interfacial friction angle between the penetrator and the granular media. However, both the relative density and particle shape of the granular media do not exhibit significant effects on the reduction of the penetration resistance. The robotic application of the findings was demonstrated by a soft burrowing robot with a rotating cone.   

Mechanical feedback controls the emergence of dynamical memory in growing tissue monolayers

The growth of a tissue, which depends on cell–cell interactions and biologically relevant processes such as cell division and apoptosis, is regulated by a mechanical feedback mechanism. We account for these effects in a minimal two-dimensional model in order to investigate the consequences of mechanical feedback, which is controlled by a critical pressure, p_c. A cell can only grow and divide if its pressure, due to interaction with its neighbors, is less than p_c . Because temperature is not a relevant variable, the cell dynamics is driven by self-generated active forces (SGAFs) that arise due to cell division. We show that even in the absence of intercellular interactions, cells undergo diffusive behavior. The SGAF-driven diffusion is indistinguishable from the well-known dynamics of a free Brownian particle at a fixed finite temperature. When intercellular interactions are taken into account, we find persistent temporal correlations in the force–force autocorrelation function (FAF) that extends over a timescale of several cell division times. The time-dependence of the FAF reveals memory effects, which increases as pc increases. The observed non-Markovian effects emerge due to the interplay of cell division and mechanical feedback and are inherently a non-equilibrium phenomenon.

    

Hydrodynamic enhancement of p−atic defect dynamics

We investigate numerically and analytically the effects of hydrodynamics on the dynamics oftopological defects in p−atic liquid crystals, i.e. two-dimensional liquid crystals with p−fold rotational symmetry. Importantly, we find that hydrodynamics fuels a generic passive self-propulsion mechanism for defects of winding number s= (p−1)/p and arbitrary p. Strikingly, we discover that hydrodynamics always accelerates the annihilation dynamics of pairs of ±1/p defects, and that, contrary to expectations, this effect increases with p. Our work paves the way towards understanding cell intercalation and other remodelling events in epithelial layers.   

Accessible materials characterization of lipid nanoparticles for nucleic acid delivery

Nucleic acids can revolutionize human health outcomes, as evidenced by mRNA lipid nanoparticle (LNP) vaccines used to combat COVID-19. Despite the success of these non-viral delivery vectors, their physicochemical properties are not well understood, making them difficult to tune and optimize. However, the materials and methods used for their production are expensive, making fundamental studies on them cost prohibitive for many researchers. In this work, we leverage high-throughput methods to prepare a variety of LNP formulations and analyze their structural properties. Our techniques combine open-source liquid handling robots with analysis techniques using well plates such as plate reader fluorescence and UV/Vis assays, as well as small-angle x-ray scattering (SAXS). This platform allows the synthesis and material characterization of a breadth of conditions with minimal reagent volumes, creating an accessible and largely autonomous workflow for fundamental LNP research.   

Crosslinking of coiled-coil peptide "bundlemers" into network films

‘Bundlemer’ building blocks are homotetrameric coiled coils assembled from computationally designed peptides in aqueous solution.. These self-assembled bundlemer nanoparticles have great potential for the creation of high performance materials resulting from their coiled coil structure and the ability to almost arbitrarily design their exteriors for desired interbundle interaction. This work focuses on crosslinking bundlemer building blocks using a thiol-ene photo click reaction. Our bundlemers are easily modified to include a thiol reactive group via cysteine incorporation and alkene with the addition of an alloc protected lysine. In the presence of a free radical initiator and UV light, we can crosslink bundlemers into high-modulus gels and crosslinked films. We have explored the effect of peptide sequence, concentration, reactive group ratios, and solvent on the mechanical performance of our resulting materials.  Additionally, transmission electron microscopy revealed that the alloc hydrophobically functionalized bundlemers form specific lattice-like nanostructure when cast into films from aqueous solution.  The nanostructure formed relative to the bundlemer functionality and  solution conditions will be discussed.

    

Multifunctional 2D hydrogels based on graphene and cellulose derivatives

Through the self-assembly of the biomaterial hydroxypropyl cellulose (HPC) and the two-dimensional material graphene oxide (GO), a new type of two-dimensional material that can be electrically and thermally controlled was constructed. The reversible hydrophilic/hydrophobic switching of HPC enables the 2D hydrogel excellent water transport capacity under temperature stimulation, which also leads to significant changes in the optical properties. Briefly, the ability of HPC to switch between hydrophobic and hydrophilic states enables it to exhibit birefringent responses in the two-dimensional (2D) environment of GO and layers. When the HPC undergoes a phase transition, it induces a change in the ordering and arrangement of the GO surface bound to it. Next, a composite material consisting of conductive reduced graphene oxide (rGO) and 2D hydrogel was developed. Using the conformational and alignment changes of HPCs as switches to mediate electrical energy transfer via Joule heating and thermal stimulation, electrothermal control valves were constructed to modulate optical properties and water transport. The as-prepared conductive 2D hydrogel exhibits excellent mechanical properties (Young's modulus of 2.5 GPa) and excellent electrical conductivity (176S cm-1) without sacrificing the superior swelling capacity. Furthermore, based on the motion of the GO layer regulated by the phase transition of the polymer chains, we fabricated a 2D rGO/HPC hydrogel-based artificial muscle. Attribute to the conductive rGO region, the movement of artificial muscle can be controlled by applying bias. Here, a general and sustainable method to synthesize new low-dimensional robust multifunctional hydrogels is demonstrated. The sustainable method for self-assembly of HPCs in the two-dimensional confinement states of GO and rGO presented here is applicable to the entire family of polymers with low critical solution temperatures (LCST). These stimuli-responsive composite 2D materials are considered excellent candidates for fluid transport systems, smart actuators, and bio-engineering applications. 

    

On the influence of long-ranged interactions on absorbing state phase transitions

While the role of local interactions in non-equilibrium phase transitions is well studied, a fundamental understanding of the effects of long-range interactions is lacking. In particular, most attention was paid to systems where the long-ranged nature results from the underlying network structure. In our work, we study the critical dynamics of reproducing agents subject to long-ranged chemical interactions and limited resources. We emphasize the importance of the agent's diffusion speed relative to the diffusion speed of the signalling substance. In the limit of fast signal transduction, which gives rise to a Coulomb-like interaction, renormalization group analysis reveals distinct scaling regimes for attractive or repulsive interactions. In the limit of slow signal transduction the dynamics is dominated by a diffusive fixed point. Further, we suggest a novel nonlinear mechanism that stabilizes the continuous transition against the emergence of a characteristic length scale due to a chemotactic collapse.   

Hydrophilicity Controllable rGO Sponge for Living Bioelectrogenesis Electrode

Herein, we report on a novel bioelectrode material that consists of partially reduced graphene oxide (rGO) sponge and Shewanella Onedensis MR-1 bacteria. We develop a new facile approach for the enhancement of output current of the sponge-bacteria electrode by optimization of the surface chemistry of sponge-electrode surface. We achieve simultaneous tuning hydrophilicity and conductivity of rGO by adjusting the reduction temperature of graphene oxide (GO). Thermal reduction is a sustainable approach that allows us to produce the scaffolds for bacteria growth with excellent biocompatibility without usage of chemicals. We find the rGO-sponge-electrode exhibit a GO-reduction-temperature reliable bio-current generation performance due to the discrepancy in rGO’s hydrophilicity and conductivity, where the sponge-bacteria shows a superior performance with the bio-current density reached 135 mA·m^-2 in chronoamperometry test at the reduction temperature of 375°C. Furthermore, in contrast to existing polymer-based microbial electrode requiring several days activation time to form a conductive network, our rGO-sponge-electrode doesn’t require the activation time. The proposed here novel biocompatible graphene-based electrodes can be used for the design of the next generation of renewable energy-powered devices.   

Characterizing Tether Friction on Natural Objects for Robotic Teams

In field robotics, it is commonly assumed that tether-environment contact is an adversarial circumstance that should be avoided. While tether contact can increase the complexity of planning and control, harnessing the capstan effect provides an opportunity to increase the strength of robotic systems and apply larger loads. In this work, we discuss our published research intended to bridge this gap between physical complexity and function. The capstone of this work is the demonstration of a small (less than 0.5kg) legged robot on sand, detritus, and smooth low-friction surfaces supporting the tugging of more massive loads (4.8 kg).

One physical contribution in this work is the critical evaluation of the simplistic capstan equation, and its applicability to realistic unstructured settings. For example, we measure the tension amplification of wraps around redwood trees and rocks that do not have regular shapes or textures. We find that the capstan equation provides accurate estimates despite this irregularity, and can provide a realistic lower bound of predicted tension amplification. More formally, we test the ability to predict tension amplification for multiple wrapped objects in series, as opposed to all tether wrapping on a single object. We find that the capstan equation extends remarkably well to multi-capstan and other more complex scenarios, and as a result provides useful estimates to inform real-world robotic implementation.   

The nonequilibrium thermodynamics of flocking of active spins

The collective coherent motion known as flocking is a nonequilibrium phenomenon and is sustained by a continuous input of free energy. By studying the energy dissipation of the active Ising model (AIM), we show that the energy cost can be decomposed into two parts, namely the cost for self-propelled motion and an additional energy dissipation required to align spins in order to maintain the flocking order. We find that this additional alignment dissipation reaches its maximum at the flocking transition point in the form of a cusp with a discontinuous first derivative with respect to the interaction strength. To understand this singular behavior, we analytically solve the two-site and three-site AIM models and obtain the exact dependence of the alignment dissipation on the flocking order parameter and control parameter, which explains the cusped dissipation maximum at the flocking transition. Our results reveal a trade-off between the energy cost of the system and its performance measured by the flocking speed and sensitivity to external perturbations. This trade-off relationship provides a new perspective for understanding the dynamics of natural flocks and designing optimal artificial flocking systems.   

Platinum-doped graphene: The next generation gas sensing

Carbon-based nanostructures functionalized by transition metals have attracted attention as efficient sensors and storage mediums of various gases. In this project, we use density functional theory (DFT) to investigate sensing and storage capacity of H₂, S₂, and CH₄ gases on Pt-doped graphene. We establish a hierarchy of models of Pt chemisorption to graphene, including single Pt atoms, Pt₁₃, and Pt₅₅ atomic clusters. For the Pt clusters, we adopt the cuboctahedron geometry with its triangular side facing graphene, which is found to be energetically favorable compared to the icosahedron geometries. To investigate the sensibility at different levels of H_2, S₂, and CH₄ adsorption, we examine the changes in electronic transport properties upon the gradual adsorption of gas molecules to the energetically favorable sites around Pt, which are identified by using a combined strategy of ab initio random search and molecular dynamics (MD). We find that gas adsorption alters the resistivity of Pt-doped graphene based on the gas type and the number of adsorbed gas molecules. These results indicate that Pt-doped graphene can be utilized for the next-generation gas sensors.

    

Evaluation of Dopamine Detection using 2D-hBN: A First Principle Analysis Towards Selective Sensing Application

Dopamine is an important biomolecule that plays a vital role in the biological system. One of the major challenges in detecting dopamine is that it possesses a similar oxidation potential as ascorbic acid. Thus, a careful selection of material is required to selectively detect dopamine. In the present study, 2D hBN sheet has been explored for atomistic evaluation of different biomolecule adsorption using density functional theory formalism. Dopamine, ascorbic acid, glucose and urea have been selected to evaluate the specificity of the material. The adsorption of different biomolecules over 2D-hBN sheet reveals distinctive changes in electronic band gap. Phononic dispersion of the molecule adsorbed structure validates the stability of the sensing material. Furthermore, the Löwdin population analysis also unfolds the probable cause of alteration in oxidation potential of dopamine in the presence of 2D-hBN sheet. Charge density difference plot of optimized geometries demonstrates the electrostatic interactions between the substrate and analyte. Finally, the selectivity of hBN towards dopamine sensing is also validated through Löwdin population analysis.   

The effects of the surface oxidation on Rare-Earth Tritellurides: Experimental and Theoretical investigation

Two-dimensional (2D) layered rare-earth tritellurides (RTe₃) have gained attention as superconductors and near room-temperature charge density wave materials. Similar to other 2D tellurium-based systems, RTe₃ materials suffer from environmental stability problems. Experimental results show that RTe₃ sheets (with R = La, Nd, Sm, Gd, Dy, and Ho) exposed to air tend to oxidize and form thin TeO_x layers confined to the surface, edges, and grain boundaries. However, the oxidation agents and the characteristics affecting the oxidation resilience are unknown. Therefore, we perform extensive density functional theory (DFT) calculations to study the reactivity of both humidity (H₂O) and oxygen (O₂) on top of pristine and defective LaTe₃ and HoTe₃ monolayers. For pristine RTe₃, we find that oxygen molecules exhibit finite dissociation barriers and strong chemisorption binding energies. Conversely, H₂O is found to play a negligible effect as an aging catalyst. For defective RTe₃ monolayers, we observe 3 to 4 times stronger binding energies of oxygen atoms to the inner R-Te slab. Moreover, the dissociation barriers for H₂O become finite, indicating an enhancement of H₂O molecules’ interaction with the material at the defective sites. In addition, our DFT calculations reveal that in-plane tensile strain can lead to a decrease in the oxidation resilience of RTe₃ materials, which merits further studies.

    

An Ab-initio Perspective on Simultaneous Detection of Uric Acid and Ascorbic Acid Using Graphene Oxide

Simultaneous detection of uric acid and ascorbic acid from different biofluids is an open research problem as both of them have similar oxidation potential. Incorporating graphene oxide as the sensing substrate will significantly enhance the system's selectivity towards uric acid and ascorbic acid detection. The percentage of sp² carbon atoms inside graphene oxide structure is the most important parameter to delineate the degree of oxidation or reduction in graphene oxide. Thus, an extensive first principle analysis has been carried out to select a suitable percentage of sp² carbon atoms in graphene oxide structure which can simultaneously detect uric acid and ascorbic acid. The structural stability and integrity of the selected adsorbed geometries are validated through phonon dispersion calculations. The obtained electronic band gap, along with projected density of states analysis, confirms that after uric acid and ascorbic acid adsorption, the conductivity of the system alters significantly, and thus a change in band gap is visible. Furthermore, the charge redistribution upon adsorption of two different analytes over graphene oxide substrate is validated by Löwdin population analysis. The charge difference density plot also confirms the electrostatic nature of substrate and analyte interaction.    

Electron Spin Densities in Open-Shell Polycyclic Aromatic Hydrocarbons by Self-Interaction-Corrected Density Functional Approximations

Electron spin densities in open-shell systems such as polycyclic aromatic hydrocarbons are studied using recent locally scaled self-interaction-correction (LSIC) (Zope et. al. Phys. Chem. Chem. Phys., 2021, 23, 2406-2418) method and the Perdew-Zunger SIC (PZSIC) method within the FLOSIC scheme. Descriptions of such systems are usually challenging for density functional approximations due to pronounced electron delocalization and spin polarization effects because of the planarity of their structure and electron conjugation. Spin densities calculated are compared against benchmark QCISD results. Results show that PZSIC tends to overcorrect the density delocalization tendency of LSDA and PBE-GGA. On the other hand, the LSIC method with the simplest LSDA functional gives a more balanced description of spin densities resulting in better agreement with benchmark QCISD results.   

Plasmon mediated deposition of transition metal catalysts on titanium nitride nanoparticles

Abstract:

Plasmonic photocatalyst can efficiently absorb light to generate photoexcited electrons to drive energy extensive catalytic reactions. We have successfully synthesized composite plasmonic catalysts by visible-light-induced deposition of transition metal nanocatalysts such as Ni and Pt on refractory plasmonic titanium nitride (TiN) nanoparticles. Titanium nitride nanoparticles can absorb broad spectrum solar light to generate photoexcited electrons which reduce transition metal precursor salts to deposit the metal atoms on the surface. Notably we could deposit different size Ni or Pt nanocatalysts ranging from single atoms to nanoclusters on titanium nitride by varying the light intensity and deposition time. Additionally, the reaction conditions such as pH could be optimized to maximize the loading of the nanocatalysts on titanium nitride nanoparticles surface. We are also looking to into the effect of vacancies on TiN surface on the loading density of nanocatalysts deposited on it. The findings of this study can be used to develop a visible light mediated synthesis of plasmonic catalysts under mild conditions, which will enable their widespread applications.   

TMD Materials and Chiral Molecules

The similarity of Transition metal dichalcogenide (TMD) materials and chiral molecules build an unprecedented bridge in physical chemistry, which both have strong spin-orbital coupling, and would be promising for spintronic and valleytronic applications. Because spin valley diffusion current can be generated and manipulated with circularly polarized photons, the spin selectivity allows us to characterize this charge density and probe valley-polarized exciton dynamics, promisingly to unravel multi-layers of application in molecule-TMD heterojunction, e.g. chirality distinction.   

Dipolar Bath Mediated Cross Polarization in Dissolution Experiments

 It has been over 10 years since cross polarization (CP) was proved useful for dynamic nuclear polarization dissolution experiment (d-DNP) by shortening polarizing time in glassy samples doped with paramagnetic impurities with a variety of possible sequences [1].

In d-DNP CP sequences the hydrogen spins are allowed to achieve a large polarization first that is then transferred to either ¹³C or ⁶Li spins via CP including the possibility of using the dipolar bath to indirectly transfer spin order. Optimization of polarization conditions, temperature and magnetic field would allow also to implement and improve sequences that rely on the dipolar bath rather than in direct transfer of polarization between easily polarizing hydrogen and low gamma nuclei such as ¹³C spins [1].

Several aspects of cross polarization for low temperatures with respect to d-DNP experiments are reviewed specifically for cases involving different hardware conditions. 

1.-A.J. Perez Linde, PhD thesis, University of Nottingham, UK, 2009.   

Charge-Transfer States in Molecular Donor-Acceptor Dyad: Importance of State-Specific Solvation

Charge-transfer states arise at interfaces which are important in a variety of scenarios, such as charge-separation in the reaction centers of photosynthetic systems and at donor-acceptor regions in opto-electronic devices. Charge-transfer excited-states are delicate to capture accurately with ab Initio electronic structures as they require inclusion of non-local exchange interactions along with the distinction between non-equilibrium and equilibrium solvation.

To illustrate the importance of non-equilibrium and equilibrium solvation we explore a recent class of donor-acceptor dyads based on the fluorescent BODIPY functionalized with triphenylamine (TPA) shows the peculiar property of dual fluorescence. It is hypothesized that instead of the sensitized charge-transfer state being optically dark it provides an additional bright radiative pathway. For donor-acceptor dyads we use time-dependent density functional theory to characterize the energetic alignment of excitonic and charge-transfer states in a BODIPY-TPA molecular complex. We observe that using a long-range exchange corrected functional in combination with state-specific solvation scheme, as opposed to linear-response solvation, gives a qualitatively correct alignment of the exciton and charge-transfer states with an enhancement in oscillator strength for the equilibrium solvated charge-transfer state, in agreement with experiment. This work provides rationalization of experimentally observed  of charge-transfer state emission and provides a foundation to explore charge-transfer using ab Initio excited-state non-adiabatic dynamics.  

    

A systematic study of the kinetic compensation effect in thermal desorption

The kinetic compensation effect (KCE) is an observed systematic variation in the apparent magnitudes of the Arrhenius parameters the energy of activation E_a and the preexponential  factor ν of many activated processes as a response to perturbations. The variations often result in a linear correlation, which is often explained as being a consequence of a mutual offsetting between E_a and ln ν. We conduct a systematic study on the kinetic compensation effect through kinetic Monte Carlo simulations, to study the effects on the rates when an 'experimental parameter' has been altered during the thermal desorption of quasi spherical adsorbates from different surface configurations.By numerically calculating the activation energy, while the following parameters are varied: lateral interaction strength, surface morphology, concentration of an additive, in addition to studying the effects of repulsive interactions (anti compensation effect). Our results show a mutual variation which yields a partial compensation effect, as opposed to a complete mutual offsetting. We attempt to understand the transient behavior of the parameters to provide a picture of the microscopic origins of the KCE in this system, and perhaps to help understand its origins in other systems.   

Ultrafast spectroscopy of an azide in the vibrational strong coupling regime

Vibrational strong coupling (VSC) promises systematic modification of chemical reactivity. There are now reports of reaction rate modulation, altered product branching ratios, bulk structural modification, etc. Ultrafast studies of vibrational polaritons might reveal the elusive mechanisms behind VSC-facilitated chemistry. Until now these studies have been applied to only a limited number chemical species, mainly W(CO)₆.

We apply femtosecond mid-infrared pump-probe spectroscopy to a typical organic compound, diphenylphosphoryl azide (DPPA), known to have a rather large Rabi splitting. The N₃ asymmetric stretch mode around 4.6 μm is coupled to a cavity mode, with the cavity made of two planar gold mirrors. We compare the in-cavity pump-probe spectrum to the out-of-cavity transient spectrum to investigate the early time dynamics of the upper and lower polariton states. Also, we will discuss the influence of the metallic surface, where localized surface plasmons and phonons may affect the response of the vibrational polaritons.

Understanding the ultrafast dynamics of a variety of chemical species is crucial for future research on how a chemical bond responds under VSC. This research opens the way to studying modified click chemistry under VSC.   

The Influence of Chlorine In Corrosion Initiation on Alumina Using A Cluster Model: A First-Principles Study

The US spends more than $100 billion annually to address the problem of corrosion.  As even a modest reduction in corrosion has the potential to save billions of dollars each year, there is significant benefit to a rigorous understanding of corrosion initiation.  This work uses an ab-initio approach via Density Functional Theory to explore the onset of localized corrosion by investigating the stability of alumina film in the presence of halides.  

A cluster model is used to expose a variety of local environments which may be present on the surface of alpha-Al₂O₃.  Nanoclusters of several sizes were used to generate a range of potential environments for chlorine adsorption, offering insight into chlorine adsorption on dissolving and repassivating alumina films from relatively few simulations.  This work provides a structural and electronic description of the preferred chlorine adsorption environment and the initial system response.  Preliminary results reinforce the link between chlorine adsorption and under-coordination, with further structural analyses ongoing.  Additional in-progress including Projected Density of States calculations describes the electronic environment present during adsorption.   

Nonequilibrium thermodynamics for quantum systems strongly coupled to baths

Recent experimental advances in miniaturization of thermoelectric devices necessitate corresponding thermodynamic theory. Standard quantum thermodynamics (quantum statistical mechanics) assumes negligible system-bath coupling, but this assumption breaks down at nanoscale, where energy of the system is of the same order as the coupling. Thermodynamic formulation for nonequilibrium quantum systems strongly coupled to baths has not been fully developed yet. Several suggestions are available in recent literature. Here, we use a formulation utilizing von Neumann expression for reduced density matrix as system thermodynamic entropy to analyze the Carnot cycle in a nanoscale device. The formulation is the only one available today consistent with microscopic dynamics. We check consistency of the formulation by evaluating efficiency and entropy production of a single level model of the device coupled to macroscopic hot and cold fermionic reservoirs for weak (idealized) and strong (realistic) system-bath couplings at reversible driving. We show that lack of energy resolution in the formulation results in efficiency lower than the Carnot efficiency even at reversible driving and negative entropy production for some processes. To restore intuitively expected reversible behavior at adiabatic driving and consistency with the second law of thermodynamics, an energy-resolved thermodynamic formulation has to be developed.   

Dynamical thermal activated effects of vacancy molecular and atomic gas adsorption in graphene

Modern detection technology requires highly sensitive electrochemical materials to temperature, pressure, irradiation flux, thermal conductivity, and other complex properties in industrial applications, and doped graphene represents a major promising material. Here, we present a quantum-classical molecular dynamics (QCMD) study of molecular and atomic Hydrogen (H), Oxygen (O), Nitrogen (N), and Boron (B) adsorption, dispersion, and atom substitution mechanisms and effects on the electron transport of a graphene sheet in a range temperature of 300–1200K. The QCMD simulations are performed, based on self–consistent charge tight binding density functional theory (SCC-DFTB) to describe atoms B and N atom substitution processes during irradiation of monoatomic and molecular B and N gas, as close as possible to experiments for saturation rates. We validate our results by comparing the density of states calculations to those obtained by plane wave density functional theory. Finally, the open-boundary nonequilibrium Green’s function method is applied to obtain the conductivity of graphene as a function of H, O, N, and B coverage, as well as B/N-doped for voltages up to 300 mV.

    

Modulation of Atom Stacking Hierarchy Leads to New Intermetallic Nanocrystal Structures

A library of compositionally and structurally well-defined Au-Cu alloy nanocrystals has been prepared via scanning probe block copolymer lithography. These libraries not only allow one to map compositional and structure space but also the conditions (e.g., cooling rate) required to access specific structures. This approach enabled the realization of a previously unobserved architecture, an intermetallic nanoprism, that is a consequence of hierarchical atom stacking. These structures exhibit distinctive diffraction patterns characterized by non-integer-index, forbidden spots, which serve as a diagnostic indicator of such structures. Inspection of the library's pseudospherical particles reveals a high-strain cubic–tetragonal interfacial configuration in the outer regions of the intermetallic nanocrystals. Since it is costly and time-consuming to explore the nanomaterials phase space via conventional wet-chemistry, this parallel kinetic-control approach, which relies on substrate- and positionally-isolated particles, may lead to the rapid discovery of complex nanocrystals that may prove useful in applications spanning catalysis and plasmonic sensing.   

Computational research of Electrocatalytic methane oxidation on α-Fe2O3 study by density functional theory

  We investigate the electrocatalytic methane oxidation to high-order alcohols on Iron oxide by density functional theory in this work. Electrocatalysts such as Ironoxide is expecpected to have pospective performance on hydrogen production and dealing with hazardous chemicals suchas CO₂, NOx and SOx. Especially, MOR(methane oxidation reaction) has gained attentions because of it's waste disposal ability. The Fischer-Tropsch reaction, Oxidation process of methane to high-order alchol or aldehydes,is very solution to harzardous chemiclas. 

  Iron oxide is promising catalysts of methane oxidation, and It is also known water splitting electro catalyst meterial. Because not enough research has been done on this, It is worthy to investigate its computational feature for future application.

  In this research, we apply DFT+U(Density Functional Theory plus Hubbard U) and NEB(Nudeged Elastic Band) method to verify electrochemical mechanism of methane to higher order alchols on Fe catalysts, thorough iron oxide-zirconia as a medium. There are some different type of surface structure we investigate on, where we use implicit solvation models properly assimilate electrocatalytic environment. Through this series of studies, we propose a feasible mechanism and its feature affected by its reaction envirnoment.

    

Using STM to observe DMP molecules dosing on the gold surface

I'd like to report the work of using STM to detect the DMP molecules on gold surface, we dose DMP molecules in the liquid helium temperature (5K) and in the ultrahigh vacuum condition. We investigate the orbital information of DMP molecules in that temperature and vacuum. Finally, we get some data about the intrinsic properties of DMP molecules.   

Acid Site's Shape Selectivity in Dimethyl Ether Carbonylation Reaction over 8-Membered Ring Zeolites : a First-principles Study

Zeolite is in the spotlight as an eco-friendly catalyst for various reactions. It can typically promote dimethyl ether (DME) carbonylation reaction to methyl acetate (MA). In this reaction, CO addition reaction to surface methyl group (SMG) is known as rate determining step (RDS). Stabilizing the cationic transition state of RDS can increases the reactivity, and zeolites which have eight-membered ring (8MR) is suitable. In this research, the DME carbonylation reaction mechanisms over 8MR zeolites, especially CO addition reaction, are studied using a First-principles calculation. Chabazite (CHA), erionite (ERI), ferrierite (FER), linde type A (LTA), stilbite (STI) are selected as 8MR zeolites. CHA, LTA has a symmetric circular shape 8MR, but ERI, FER, STI has an aliphatic shape 8MR. Circular 8MR zeolites have little difference in reaction energy and activation energy according to acid site because of highly symmetric ring shape. However, aliphatic 8MR zeolites differs in reaction energy and activation energy depending on the acid site. At the acid site with a large curvature, negatively charged oxygens within 8MR can stabilize the cationic transition state better compared to the small curvature acid site. Based on these results, the reactivity according to the shape of the zeolite and the site is compared, and the reaction conditions with optimal reactivity is explored.   

Adsorption of Methane and Argon Mixture on Planar Graphite

We report on the adsorption equilibration data for Methane and Argon mixture (50:50 mixture) on planar graphite. Time evolution of the composition of a gaseous mixture of Argon and Methane in the vapor phase during adsorption on graphite sample over broad range of initial pressures at a fixed temperature was measured. A correlation between the final compositions as a function initial starting pressure of the gas mixture will be presented and discussed.

    

Small polaron induced visible light photochromism in tungsten oxide hydrates- A mechanistic aspect.

Class of transition metal oxides which act as photochromic materials undergo a reversible color change from native transparent state (characterized by visible and infrared (IR) transmittance) to blue colored state (characterized by the transmission of only visible light and blocking IR). This is due to the intercalation/deintercalation of small cations (e.g.: H⁺) under external stimuli such as sunlight. In this work tungsten oxide hydrates which exhibit reversible photochromism under visible light illumination were prepared by a sol-gel process, in powder and thin film form from a parent sol. The mechanism of coloration is attributed to a two-stage optical phenomenon: (i) formation of photocarriers, leading to the generation of protons which gets intercalated in WO₆ octahedron clusters (ii)  formation of  small polarons, which is evidenced by the absorption of NIR radiation. A small polaron absorption model proposed in the literature has been applied to explain the optical conductivity measurements using spectroscopic ellipsometry. XPS data showed the formation of reduced oxidation states in colored tungsten oxide hydrates, which is a need for small polaron hopping. The optical phonons of tungsten oxide hydrates and structural order were studied by vibrational spectroscopy and XRD. The photochromism observed under solar radiation opens-up cost-effective routes to realize energy saving window glazing.

    

Theoretical Methodology to predict Melting-Like Transition Modeling in Clusters using Artificial Neural Network.

Clusters with 100 or fewer atoms exhibit melting-like transitions fundamentally different from bulk melting. A better understanding of how clusters melt is essential for applications of cluster materials in electronics, especially catalysis. We are developing a methodology for the simulation and analysis of cluster melting. We did classical Parallel Tempering Monte Carlo simulations of argon clusters modelled with a 6-12 Lennard-Jones potential. The potential energy distribution, heat capacity, and a sample of cluster configurations were obtained at different temperatures. The configurations were represented by features based on the pair distribution function and arrangement of nearest neighbours. We determined the freezing temperature T_f and melting temperature T_m>T_f using an Artificial Neural Network (ANN) classifier. The ANN Classifier also helps characterize the solid-liquid coexistence and yields the solid fraction at every temperature. The ANN classifier is computationally efficient; 30 PTMC replica with 64000 steps gives nearly converged results.   

Synthesis of nanometric crystals of sodium and calcium zirconates as solid heterogeneous catalyst for biodiesel production.

Diesel varieties are mainly produced from two different sources oil and biomass. In the first case, oil is a non-renewable resource while diesel produced by biomass it is called biodiesel.  A better sustainable way to produce biodiesel is to take advantage of the availability of wasted cooking oil, when it has been discarded from the food industry, as it is found in large quantities. Our work was synthetize sodium and calcium zirconates (1:1), NZO and CZO. Obtain nano-solid heterogeneous catalyst of NZO and CZO. Via solid-state reaction used to obtain each zirconate. Reagent purities were studied by XRD, SDT and TEM. As a pretreatment process, sodium and calcium carbonate reagents were dehydrated by 10 min and zirconate oxide by 20 min both at 100 °C, to be sure that the stoichiometry does not vary. Sodium carbonate was hydrated (XRD PDF 01-072-1152), so it was left overnight at the right temperature to obtain the carbonate, without decomposing. Calcium carbonate PDF  After the solid-state reaction, it is observed by XRD and TEM confirm the zirconates formed (900 °C/1h). For CZO indicate, one impurity compound and unreacted reactants and NZO monophase. Nanocrystal sizes fabrication was done by mechanically mixed with aqueous medium room air atmosphere. We clarify that the wet grinding process does not favor the formation of hydroxides, detected by XRD (1-3 %) and TEM. Interestingly, metallic calcium was observed by TEM in CZO, this indicates that it must decrease the time and temperatures used, when the CZO manufacturing process is repeated. The crystal sizes calculate by Sherrer equation of CZO around 17– 78 nm. TEM analysis observes 20– 27 nm for CZO, with metallic calcium in another shade and NZO show 10 -33 nm crystals dimension. Nano-materials as catalysts remain to be tested.

 

    

Síntesis y caracterización de nanopartículas de Ag por método electroquímico

Las nanopartículas de plata (AgNP) se sintetizaron por método electroquímico, utilizando un cátodo de plata metálica y un ánodo en agua desionizada. La polaridad se invirtió cada 60 segundos generando una variación de voltaje para obtener tres concentraciones diferentes: 16 ppm, 24 ppm y 34 ppm. Las nanopartículas sintetizadas se caracterizaron estructural, óptica y morfológicamente por XRD, UV-Vis y Microscopía Electrónica de Transmisión (TEM), respectivamente. Los patrones XRD mostraron los picos en 38.11? y 64.42? de Ag. El pico de resonancia del plasmón superficial en los espectros de absorción de la solución coloidal de plata mostró una absorción de 422 nm a 429 nm. La medición TEM proporcionó un tamaño de partícula promedio para las concentraciones de 16 ppm, 24 ppm y 34 ppm de 4,23 nm, 3,95 nm y 3,27 nm, respectivamente. Los AgNP se probaron contra la bacteria común Escherichia coli.   

2D breathable graphene-based windows for smart sustainable housing

The next generation of smart multifunctional structures and devices requires the development of materials with sensing/actuating properties such as the capability to sense and respond to triggers, adapt to the environment, and switch their properties and functions on demand. Here, we propose a novel concept of sensing/actuating in 2D materials based on both in-plane and out-of-plane rearrangement of 2D flakes on demand. To form such breathable in three dimensions 2D materials, we develop a novel approach to regulate interactions between GO flakes using pH. In this work, we program the sensing/actuating properties of 2D graphene-based multilayers by pH-assisted tuning of the interactions between the flakes to achieve 2D lateral length and area change. Simultaneously, our one-stage method leads to the self-assembly of multilayers with out-of-plane anisotropy to fulfill the requirements of bending theory. Due to the versatility of our approach, it is also applicable to other 2D materials with adjustable surface charge density such as MXenes. Furthermore, we apply the “bimetallic strip model” to calculate the thermal expansion coefficients for our charged and uncharged 2D materials. This model explains the change in the physical state of metals by lateral expanding or deforming that is applicable to 2D materials.  We apply our lightweight low dimensional breathable materials to construct flamboyant windows that can open/close in response to a tiny change in room climate during the day.  Our inspired by gothic architecture flamelike 2D windows provides energy saving climate control and novel concept in the functional design of sustainable houses. Importantly, this work gives a novel insight into the mechanism of bending/unbending of 2D materials. We show that our approach is applicable to the whole family of 2D materials with regulated surface charge density from GO to MXenes. Such 2D actuators are robust, thin, and flexible and can be used for soft robotics and energy-efficient architecture, tissue engineering, bionic devices, and biomedical applications.

Reaching the Bound for Quantum Information Scrambling of Reactions

Bounds such as the one discovered by Herzfeld [1] for quantum scrambling of atoms or by Maldacena [2] for many-body quantum chaos set an upper limit proportional to kT/h on the growth of Lyapunov exponents. We recently used out-of-time-order correlator (OTOC) time derivatives, quantum analogs of Lyapunov exponents in the limit of classical chaos, to show that this bound is not exceeded by quantum vibrational energy flow in molecules [3]. Here we explore quantum information scrambling in isomerization reactions modeled by an adiabatic double well either alone, bilinearly coupled to an oscillator, or bilinearly coupled to a harmonic bath. The scrambling rate is related to dynamics near saddle points in the activated dynamics regime at high temperature. This rate drastically decreases at low temperature, signal the onset of a regime the reaction takes places by tunneling, consistent with the bound on scrambling rate, . We also study the effect of friction on scrambling rates in isomerization reactions by numerical and analytical treatments.

 

[1]      K. F. Herzfeld, Zur Theorie der Reaktionsgeschwindigkeiten in Gasen, Annalen der Physik 364, 635 (1919).

[2]      J. Maldacena, S. H. Shenker, and D. Stanford, A Bound on Chaos, Journal of High Energy Physics 2016, 106 (2016).

[3]      C. Zhang, P. G. Wolynes, and M. Gruebele, Quantum Information Scrambling in Molecules, Phys. Rev. A 105, 033322 (2022).

    

Chiral-induced spin selectivity provides a nexus between the geosphere and biosphere: The role of spin-polarized muons and lithospheric iron oxide-silicate rock interactions in the emergence of biomolecular homochirality and the implications for emerging diseases in a weakened geomagnetic field

The dominant hypothesis for the origin of life posits that serpentinization was the driving process for the emergence of biomolecules and life in the Precambrian era. The biomolecules of life are homochiral and biomolecular homochirality is coupled with electron spin selectivity. Recent studies proposed that interactions between mirror symmetrical pairs of chiral biomolecules and cosmic spin-polarized muons (Globus et al., 2020, The Astrophysical Journal) or spin-polarized electrons ejected from magnetized iron oxide (magnetite) bedrocks by solar ultraviolet irradiation (Ozturk et al., 2022, Proceedings of the National Academy of Sciences) resulted in the emergence of biomolecular homochirality. In agreement with those works, I propose that the emergence of biomolecular homochirality in the Precambrian era was mediated by spin-control enantioselective synthesis induced by spin-polarized electrons ejected from iron oxide (magnetite)-silicate banded iron formations by iron nuclei-derived spin-polarized muons. I also proposed that the coupling between biomolecular homochirality and electron spin selectivity suggests that spin-control reactions could also modulate life, including diseases in the biosphere, after the Precambrian era. Furthermore, those spin-control reactions-mediated diseases would exhibit a vibrating drumhead-like spatiotemporal pattern (also known as a checkerboard pattern), semiannual (~6-month periodicity), and quasi-biennial (~2.2-year periodicity) oscillations in synchrony with the activity of a weakening geomagnetic field due to its coupling with cosmic muon intensity. Here, I provide evidence suggesting that interactions between aberrant cosmic iron nuclei-derived spin-polarized muons and new iron oxide (magnetite)-silicate rocks derived from serpentinization in a severely weakened geomagnetic field could result in the generation of an aberrant lithospheric magnetic field that mediates the spin-control synthesis of aberrant chiral biomolecules and emerging disease in the biosphere.   

Comparing Efficiencies of isotope 48Calcium Reduction and Recovery Methods

The neutron abundant 48Ca isotope has a very low natural occurrence (0.187%). Highly enriched

starting material for the production of nuclei in particle accelerators including the Argonne

Tandem Linac Accelerator System (ATLAS) is exceptionally valued. We aim to recover

enriched 48Ca metal from a mixed CaCO3+Zr sample with unknown quantity of 48Ca. The goal

is to carry out two chemical reactions within a standard ECR ion source resistively heated oven.

A sample of natural CaC03+Zr with a ratio 1:2 of Ca:Zr by mass was prepared. An oven

temperature calibration with power input set values was performed prior to baking the sample,

expelling CO2 in a gaseous state and yielding CaO which is then reduced at a slightly higher

temperature via reduction with Zr metal to form Ca metal and ZrO2. The Ca metal is evaporated

to a small area of a pre-weighed tantalum deposition plate while the ZrO2 remains in the oven

crucible. The process was repeated using a resistively heated vapor deposition system to record

and compare both Ca metal production efficiencies with a goal of finding a process for use with

the enriched 48Ca material. In the vapor deposition system, a CaCO3 and Zr mixture with the

same ratio is pressed and placed in a tantalum pinhole boat, which creates a directional vapor of

Ca metal under high temperature. The Ca is deposited onto a pre-weighed glass substrate and

reweighed after deposition to determine the Ca mass. Calcium metal recovery efficiencies will be

reported.   

Computational model for 3D cell migration through a viscoelastic extracellular matrix

Cell Migration is important for many physiological processes, such as embryonic development and wound healing, and it also underlies cancer metastasis. Recent studies have shown that the complex biophysical properties of the surrounding extracellular matrix (ECM) are critical for cell migration. Furthermore, while the mechanisms of cell migration in 2D have been relatively well-studied, how cells mechanically interact with their environment during 3D cell migration remains less understood. In contrast to 2D cell migration, 3D cell migration requires cells to remodel and/or squeeze through dense ECM networks, which causes cell migration in 3D to be significantly more challenging. Therefore, we have worked on developing a discrete agent-based computational model to help understand how cells mechanically navigate through a 3D viscoelastic ECM during single and collective cell migration. In the model, we explicitly account for binding kinetics between matrix fibers, cell protrusions, and focal adhesions between cells and the surrounding ECM. By explicitly accounting for these transient interactions, we believe that our model will help elucidate the biophysical mechanisms of cell migration through complex 3D environments.   

Hybrid coil design for shapeable magnetic field for Transcranial Magnetic Stimulation

Transcranial Magnetic Stimulation (TMS) coils are often designed specifically for either depth brain or focal stimulation [1]. A new technique that provides both depth and focality as well as steerability during TMS using temporal interference (TI). TI TMS operates based on the frequency difference of two stimulation signals that operate in the kHz range. The frequency difference between the two induced electric fields within the brain results in an envelope which provides increased focality of the stimulated area. The brain acts as a complex signal filter which filters out a portion of the higher frequency stimulation and allows the lower frequency difference to dominate [2][3]. Dual site TMS stimulates two areas of the brain with high focality [4][5][6]. Dual site TMS is currently done with two independent coils. Our research on developing novel hybrid coil designs that allow the use of a single TI TMS coil to rapidly steer between different target regions with reduced placement errors and reduced spatial limitations of the chosen targets. Using simulation software, we compare our hybrid designs with single, dual, and butterfly [7] type TMS coils with respect to depth of penetration and focality for dual site TMS.   

Direct evidence for antiferrodistortive (AFD) structural phase transition in incoherent lattice fluctuations, Jahn-Teller (JT) lattice distortion from Rutherford Backscattering Spectrometry-Ion Channeling (RBS- ICh) & local microstructure in Cr & Fe implanted dilute metalic quantum paraelectrics SrTiO3.

Properties of quantum materials are tuned by pressure, magnetic field & doping. Dilute semiconductor perovskite STO exhibits unconventional superconductivity over a wide range of carrier densities 10¹⁹-10²¹cm⁻³, Fermi level traverses a number of vibrational modes & it maintains gap to T_c ratio of BCS weak-coupling limit, despite being in anti-adiabatic regime. At lowest SC-densities, lone remaining adiabatic phonon van Hove singularity is anomalously soft transverse-optic mode associated to ferroelectric instability. Recent works suggest emergence of multiferroic (magnetic & ferroelectric) quantum critical behavior, interplay between ferroelectricity vs SC and SC mediated by odd-parity ferroelectric modes. Presence of soft phonons & their possible role as scattering centers raised suspicion that T² resistivity is not due to e-e scattering. LT RBS- ICh is used to probe displacive phase transition & lattice distortion. It provides direct evidence of incoherent lattice fluctuations as function of temp across AFD at T_a=105 K. JT effect occur for degenerate filled & empty molecular orbitals. Critical channeling angle Ψ_c & ratio of minima of angular RBS-lCh spectral yield χ_min for Sr & Ti sublattices determine JT lattice distortion in transition element (Cr & Fe) implanted STO. JT effect at Cr⁵⁺ & Fe⁴⁺ centers in STO lattice are investigated by RBS- ICh. Valence mismatch between substituent & host plays key role. Similar values of Ψ_1/2 for Sr sublattice indicates no displacement of Sr. Impurity hardly causes displacements of Sr ions but causes displacement of Ti ions from ideal lattice sites. Cr & Fe impurities predominantly leads to distortion of Ti sublattice, infers Cr/Fe is actually located at Ti positions but not in interstitial. Temp dependence of Thermal vibrational amplitudes (ρ) of Sr & Ti also displacements of Ti⁴⁺ are calculated based on Linhard's continuum model. FWHM is strongly affected by incoherent atomic displacements. Change in ρ value indicating a dynamic or static displacement of Sr & Ti atoms. With Temp ρ changes across AFD, infers different lattice constants. Local microstructure & atomic distortions studied with HR-TEM (FIB prepared), XPS, GID-XRD & Raman Scattering. Implanted STO shows a minor tetragonal phase corresponds to lattice expansion along c-axis & it's not randomly oriented.