Bulletin of the American Physical Society
APS March Meeting 2018
Monday–Friday, March 5–9, 2018; Los Angeles, California
Session F43: Advancing Polymer Physics by Integrating Simulation and Theory I: Dynamics and CoarseGrainingFocus

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Sponsoring Units: DPOLY DCOMP Chair: Arthi Jayaraman, Univ of Delaware Room: LACC 503 
Tuesday, March 6, 2018 11:15AM  11:27AM 
F43.00001: A conformationally averaged iterative method for hydrodynamic interactions in Brownian dynamics simulations of polymer solutions Charles Young , Linling Miao , Charles Sing Brownian Dynamics (BD) simulations are a powerful tool for investigating polymer rheology and dynamics. They can be quantitatively compared to rheological measurements as well as direct imaging of single DNA molecules. Despite their utility, large BD polymer simulations remain a challenge; hydrodynamic interactions (HI) are necessary to capture solventmediated dynamics, but require computationally expensive calculations. Specifically, the decomposition of a mobility matrix is required every few time steps to account for the effects of HI on the Brownian noise. We introduce a conformationally averaged (CA) iterative method for calculating HI. We first obtain an averaged mobility matrix from a freely draining BD simulation. This averaged mobility matrix is used to perform additional simulations, which are subsequently used to obtain yet another mobility matrix in an iterative procedure until a selfconsistent HI is obtained. The CA method significantly reduces computational times because the expensive decomposition is required only once per iteration. We compare the speed and accuracy of the CA method to traditional BD simulations for single chain dynamics in flow and semidilute dynamics at equilibrium. Finally, we discuss how to extend our method to semidilute solutions in flow. 
Tuesday, March 6, 2018 11:27AM  11:39AM 
F43.00002: Developing and Validating Predictions of a Model for Reversible Scission and Deformation of Wormlike Micelles Abdulrazaq Adams , Michael Solomon , Ronald Larson Wormlike micelles formed from the assembly of amphiphilic molecules (e.g. block copolymers) break reversibly in solution. The VasquezCookMcKinley (VCM) model for nonlinear rheology of such micellar solutions includes the reversible scission and deformation of these micelles but their results have yet to be validated with complimentary methods. We compare the predictions of the VCM model, which treats micelle networks as Hookean dumbbells that break at halflength to form two shorter dumbbells, to an analogous Brownian dynamics (BD) simulation. We find a discrepancy between the predictions of the VCM model and BD simulation and offer a revision to the VCM model to obtain predictions matching the BD simulation. The revision allows for tracking of the internal configuration of the micelle such that the relative orientations of shorter micelles are retained in the longer micelle resulting from the fusion of the shorter micelles. A general method for retaining this information is offered which can be applied to more general models of micelle breakage, rejoining, and flow orientation. Our new model also allows for the possibility that this relative orientation might affect the rate of fusion of micelles. 
Tuesday, March 6, 2018 11:39AM  11:51AM 
F43.00003: Simulation of the Kinetics of Chain Exchange Between Triblock Copolymer Micelles using Dynamical SelfConsistent MeanField Theory Shane Holden , Robert Wickham Motivated by recent experiments, we study the kinetics of chain exchange between BCCordered micelles in asymmetric ABA and BAB triblock copolymer melts using dynamical selfconsistent field theory (dSCFT). dSCFT reduces the problem of many interacting chains to that of the motion of a single chain under the influence of a dynamical mean force field determined selfconsistently from the other chains. This approximation enables us to simulate a large ensemble of long chains for long times. After characterizing the equilibrium properties, we systematically examine the decay time of the fraction of core (A) blocks remaining in their original micelle. For BAB, we examine the influence of the length of the second corona block on this decay. We compare to analogous AB diblock copolymers, and comment on the effect of chain architecture. For ABA, we investigate the scenario of sequential core block extraction. In both cases, we characterize the configuration of the core block as it extracts and diffuses between micelles, and comment on the free energy barrier to chain extraction. 
Tuesday, March 6, 2018 11:51AM  12:03PM 
F43.00004: Achieving Temperature Transferable CoarseGraining of GlassForming Polymers via Energy Renormalization Wenjie Xia , Frederick Phelan Jr. , Sinan Keten , Jack Douglas The bottomup prediction of the properties of polymeric and glassforming materials based on molecular dynamics simulation is a grand challenge in soft matter physics. Coarsegrained (CG) modeling is often employed to access greater spatiotemporal scales required for many applications. However, there is currently no temperature transferable and chemically specific coarsegraining method that allows for modeling of polymer dynamics over a wide temperature range. Here, we pragmatically address this issue by “correcting” for deviations in activation free energies that occur upon coarsegraining. In particular, we propose an energyrenormalization (ER) strategy to coarsegraining polymers based on relationships drawn from the AdamGibbs theory of glass formation, in conjunction with the localization model of relaxation. By testing different glassforming materials ranging from fragile polymers to small molecules, we show that our ER approach can faithfully estimate the diffusive, segmental and glassy dynamics of the AA model over a large temperature range spanning from the Arrhenius melt to the nonequilibrium glassy states. Our proposed CG approach offers a promising strategy for developing thermodynamically consistent CG models with temperature transferability. 
Tuesday, March 6, 2018 12:03PM  12:15PM 
F43.00005: Polymer Conformations & Dynamics in NanoConfinement as a Function of Chain Length and Confining Radius James Pressly , Robert Riggleman , Karen Winey Understanding the structure and dynamics of polymers under nanoconfinement is critical in a variety of applications and industries, including semiconductor manufacturing, natural gas extraction, and polymer nanocomposites. Despite its importance, the relationship between the effect of chain length and pore radius on polymer properties (entanglement density, chain conformation, diffusion coefficient, relaxation time) is not well understood, with several studies indicating conflicting results. Using molecular dynamics, we simulated several systems with polymer chain lengths of N = 25500 confined to discrete cylindrical pores of radii r = 2.520σ and examined their properties in confinement. These results are combined with unconfined polymer physics theories to develop scaling laws that describe confined polymer chain conformation and dynamics. Most interestingly, our results indicate a nonmonotonic change in diffusion coefficient, D, as the pore radius is decreased, with longer chains exhibiting larger changes in D. We believe this is caused by the competing effects of chain disentanglement (increases D) and wall friction (decreases D). 
Tuesday, March 6, 2018 12:15PM  12:27PM 
F43.00006: Polymer Dynamics under Diamond Network Confinement Tianren Zhang , Karen Winey , Robert Riggleman The dynamics and conformation of polymers under nanoconfinement have been actively studied over past few decades. Both simulation and experimental results have shown that properties of polymers are affected by confinements including changes in molecular mobility, changes to the local dynamics, and reduced interchain entanglements. The majority of these studies have focused on parallel confining surfaces and cylindrical pore confining geometries. How confinement geometries with multiple length scales such as porous networks impact polymers is yet to be fully explored. In our study, we construct a diamond network confining geometry with two characteristic length scales (strut diameter and distance between strut junctions) to mimic porous network confinement. Through MD simulations, we studied the effect of multiscale diamond network confinement on diffusion and conformation of polymers whose chain length spans from unentangled to entangled in bulk simulations. Our early results show that as the distance between junctions increases, the diffusivity increases, and entanglement density decreases. We also analyze the chain relaxation based on Rouse modes and show separate, competing effects of the changes in the local friction near the wall and chain disentanglement. 
Tuesday, March 6, 2018 12:27PM  12:39PM 
F43.00007: Identifying Polymer States by Machine Learning Qianshi Wei , Roger Melko , Jeff Chen The ability of a feedforward neural network to learn and classify different states of polymer configurations is systematically explored. Performing numerical experiments, we find that a simple network model can, after adequate training, recognize multiple structures, including gaslike coil, liquidlike globular, and crystalline antiMackay and Mackay structures produced from Monte Carlo simulations. The network can be trained to identify the transition points between various states, which compare well with those identified by independent specificheat calculations. Our study demonstrates that neural network provides an unconventional tool to study the phase transitions in polymeric systems. The direct use of molecular coordinates as input into the network underlies the robustness and simplicity of our approach, and suggests that other simulation tools, such as molecular dynamics, could be incorporated in supervised learning as well. The outcome of this work provides a compelling reason to incorporate machine learning techniques into molecular simulations more generally, as a powerful hybridized computational tool for the future study of softmatter systems. 
Tuesday, March 6, 2018 12:39PM  12:51PM 
F43.00008: Systematic CoarseGraining of Polymer Field Theories by Phase Field Mapping Jimmy Liu , Kris Delaney , Glenn Fredrickson Phase field mapping is a novel coarsegraining technique for polymer field theories adapted from the forcematching method for particle theories. It uses a complexvalued d+1dimensional field theory to produce a realvalued ddimensional field theory that is more computationally efficient to simulate. The mapping can be done from an inexpensive calculation in the finegrained theory, such as a selfconsistent field theoretic (SCFT) simulation in one spatial dimension. The resulting optimized phase field (OPF) model is similar in form to polymer density functional theories and just as fast to simulate, but it approximates the finegrained theory directly rather than asymptotically. We apply the method to two systems−a diblock copolymer melt, and a homopolymer/diblock blend−and compare the OPF models' performance to SCFT in terms of their predicted structures, length scales and energy scales. 
Tuesday, March 6, 2018 12:51PM  1:03PM 
F43.00009: Developing Chemically Specific CoarseGrained Conjugated Polymer Models Using the TAFFI Framework Brett Savoie The development of chemicallyspecific coarsegrained models of polymers is a critical tool to overcome timescale and lengthscale limitations of simulating realistic condensed phase behavior. Here we present an update on extending the recently developed topologyautomated forcefield interactions (TAFFI) framework to include versatile coarsegrained potentials. The major advantage of TAFFI is the systematic/evenhanded development of quantum chemistry derived atomistic models. Using the broad chemical coverage of TAFFI in conjunction with multistate structurebased coarsegraining provides a unique opportunity to develop transferrable coarsegrained potentials. The performance of variable resolution TAFFICG models of conjugated polymers will be presented showing the limits transferability and predictions of selfaggregation behavior. 
Tuesday, March 6, 2018 1:03PM  1:39PM 
F43.00010: Exploring Nanoparticle Structure and Thermodynamics Using FieldTheoretic Simulations Invited Speaker: Robert Riggleman , Jason Koski , Huikuan Chao , Benjamin Lindsay , Jing Cao While polymer nanocomposites have been an active area of research for multiple decades due to their utility in designing systems with controlled optical, mechanical, and barrier properties, numerous unresolved questions surround the field. Most tellingly, phase diagrams are only accepted for the simplest of systems, and direct mappings between theoretical and experimental phase diagrams are rare in the field. In recent years, our group has developed a suite of fieldtheoretic simulations techniques to study inhomogeneous polymer/nanoparticle composites, which we call the polymer nanocomposite field theory, PNCFT. By incorporating the nanoparticles at essentially the same level as the polymers, the framework is amenable to analytical treatment, fieldtheoretic simulations that sample the fullyfluctuating model without approximation, and with our recent dynamic meanfield theory techniques. In this talk, I will describe the key features of our models and some of our recent applications to study both equilibrium and nonequilibrium processes in polymer/nanoparticle systems. In one example, I will show how our nonequilibrium methods capture the structure of polymergrafted nanoparticles that are cast from solvent with a polymer matrix and not amenable to thermal annealing. We find that the experiments do not observe macrophase separation even in conditions where it is expected due to the kinetic arrest of the system. In another example, I will describe a detailed picture of the thermodynamics of block copolymer nanocomposites, where we find that the interactions between nanoparticles is mediated by the chain entropy and the interfacial tension between the domains of a microphase separated block copolymer. 
Tuesday, March 6, 2018 1:39PM  1:51PM 
F43.00011: Bonded Potentials of CoarseGrained Polymer Models Qiang Wang In most coarsegrained (CG) polymer models, bonded interactions are heuristically taken to be analogous to those in atomistic models, which consist of bond stretch (twobody), angle bend (threebody), and sometimes torsion (fourbody) potentials, but among consecutive CG segments (superatoms), instead of atoms, on the same chain. These bonded potentials are used to reproduce only the local intrachain structures. Also, they and nonbonded CG potentials are often obtained sequentially, sometimes even independently. In our recent work [D. Yang and Q. Wang, Soft Matter 11, 7109 (2015)], however, we showed that bonded CG potentials (taken to be isotropic pair potentials), in the most commonly used structurebased coarse graining (which reproduces some distribution functions of the original system), need to reproduce the intrachain segment pair correlations functions at all length scales, and that bonded and nonbonded CG potentials are coupled and need to be obtained simultaneously. Here we show how to achieve these in various ways by combining theories and simulations, for the case where each CG segment represents the centerofmass of a group of consecutive monomers on the same chain. 
Tuesday, March 6, 2018 1:51PM  2:03PM 
F43.00012: TheoryInformed CoarseGrained Simulations of Polymer Liquids Marina Guenza , Mohammadhasan Dinpajooh A number of coarsegrained models have been developed recently, such as IBI, Force Matching, and more. Starting from liquid state theory, in the Integral Equation Theory of CoarseGraining (IECG), we formally investigate how structural, thermodynamic, and dynamical properties, as measured in a CG simulation, are affected by the coarsegraining procedure. CG Molecular Dynamics (MD) simulations validate the theoretical predictions by direct test with atomistic simulations. 
Tuesday, March 6, 2018 2:03PM  2:15PM 
F43.00013: Towards a Computational Workflow for Polymer Melts Based on the Integral Equation CoarseGraining Method Mohammadhasan Dinpajooh , Marina Guenza Atomistic simulations are not close to representing common long chain polymer melts despite access to massively parallel supercomputers. Therefore, multiscale modeling, which combines the atomistic and coarsegrained (CG) methods, are required to study local and global properties of polymer melts. The Integral Equation CoarseGraining (IECG) method is a promising CG approach that is based on the liquid state theory principles and represents each polymer as one or more blobs. The IECG method affords analytical solutions in the limit of highdensity liquids of large macromolecules, where CG is most needed. In this work, we present the factors that determine the computational efficiency of the IECG method and the scalability of the related simulations for various levels of CG. Finally, the implications are discussed for a multiscale workflow that is accompanied with techniques for mapping back and forth between the atomistic and CG descriptions. 
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