Session E68: Undergraduate Research V

Golf ball simulation and aerodynamic characteristics

The flight trajectory of a golf ball depends upon the net effect of gravity, lift, and drag. The latter two forces result from the complex interaction between the ball surface and the air through which it moves, and are characterized in terms of drag and lift coefficients that depend upon the geometry, speed and spin rate of the ball as well as the density of the air. Our research focused on using both wind-tunnel results and ANSYS software analysis to obtain reliable lift and drag coefficients for different flight condition and ball dimple-pattern, and use the results to inform a robust flight simulation MATLAB program.   

Dynamics of Jet Drop Formation in Multi-Bubble Systems

Waves crashing in the ocean generate large numbers of bubbles, which burst and can produce jets that break up into sea spray aerosol droplets. Wind can carry these aerosol drops into the atmosphere and seed cloud formation. Much of the research on bursting bubbles focuses on isolated bubbles; however, bubbles from breaking waves normally exist in close proximity to other bubbles. We therefore investigate how the presence of a neighboring bubble affects jet drop formation from a bursting bubble. Combining high-speed imaging experiments with numerical simulations, we show that a bubble bursting near another bubble ejects drops angled away from the neighbor bubble. We relate this ejection angle to the asymmetry in the collapsing bubble cavity and explore how bubble separation and bubble size affect the process. The observed effects could eventually help to improve aerosol production models and clarify the accuracy of previous assumptions.   

Physics of droplet generation in inkjet bio-printing with micrometer-sized nozzles

The printability regimes in inkjet bioprinting are the sets of printing conditions described using the , in which a stable . Previous experimental and simulation works of printability have mainly focused on millimeter-sized nozzles, while it is uncertain whether their conclusions can be applied to micrometer-sized nozzles. Because the capillary effect is significantly enhanced in the micrometer scale, the printability regimes in the micrometer scale are likely to differ greatly from that in the millimeter scale. In this study, the printability regimes in the micrometer scale are calibrated through three-dimensional computational fluid dynamics simulations. Our works are expected to be critically helpful in design of inkjet bioprinting with micrometer-sized nozzles.
  

Understanding the Behavior of Charged Nanoparticles in Water

Nanoparticles have been extremely useful in the treatment of diseases, such as cancer and bacterial infections, as well as for cleaning up pollutants like oil or minerals from water. Since it is hard to image any water-based solution in electron microscope, the behavior of charged nanoparticles in water is not well understood. This has been a barrier to the development of applications for nanoparticles.
The focus of the work presented here is to examine charge screening of positive and negatively charged gold nanoparticles (+/- AuNP) in water with different concentrations of salt. Aggregation and flocculation will be studied using a combination of transmission electron microscopy (TEM) and scanning transmission electron microscope (STEM), using liquid cells fabricated from nanoparticles in various solutions encapsulated by graphene. The degree of aggregation is determined by measuring the radial distribution function (RDF) of a field of particles in an image. RDF is directly related to the surface charges of nanoparticles. This information yields a much better understanding of the aggregation behavior of nanoparticles in water.   

The Stochastic Force Spectrum of a Micro-Swimmer

We seek to understand the dynamics of micro-swimmers by quantifying the stochastic forces generated by their motion. We are currently working with Chlamydomonas Reinhardtii—a green algae commonly used to study microscopic locomotion. Our approach is to use optical tweezers and a direct force calibration known as the photon momentum method (PMM) to measure micro-swimmer forces. The power spectral density (PSD) of the force dynamics is analyzed, providing information about the frequency content of the force signals. A simple stochastic model based on the generalized Langevin equation predicts the power spectral density to have a Lorentzian-type curvature. We compare our experimental data to the theoretical model to test if the model can predict our experimentally measured PSD. This approach allows the calculation of thermodynamic quantities such as work, power, efficiency, etc. to describe the microscopic motion. Our analysis seeks to apply concepts from stochastic thermodynamics to understand micro-swimmer dynamics.   

Pattern Formation in Driven Particulate Suspensions

Systems that are driven by energy from external sources are ubiquitous, and the rich phenomenology they display (e.g., ordered phases and pattern formation of bacteria, or nanoparticles in a fluid) is described by physical models that do not rely on conventional equilibrium physics. We study theoretically and computationally a class of such active-matter models with self-propelled motion and interactions and classify the resulting non-equilibrium ordered states using techniques from statistical physics.   

Density Driven Instability during Proppant Injection in a Hele-Shaw Cell

We report an experimental investigation of granular matter suspended in a liquid injected between two parallel plates with a constant separation distance called a Hele-Shaw cell. These experiments are motivated by proppant injection in hydraulic fracturing of shale used to extract hydrocarbons. The cell is fully filled in with a similar ambient fluid to avoid capillary effects and pinning and dipinning dynamics of the front. We image the dynamics and deposition of the grains as they spread inside the cell as a function of injection rate and volume fraction of the grains. A finger-like instability is observed for sufficiently density difference between the particles and the ambient fluid. We will discuss the observed phase diagram as a function of the injection-rate of the fluid, its packing fraction and time. We demonstrate a correlation between the timescale for the sedimentation of the particles and for the onset of fingers as well as subsequent bifurcations. Corresponding length scales are studied as well, i.e. the finger lengths and widths as a function of the packing fraction of the injected fluid. Early analysis suggest that for a fixed packing fraction, regardless of the flow-rate, the sedimentation time determines the onset of the instability.   

The Missing Model of the Liquid State, from Crystalline Solid State to Random Gas State

Liquid state of materials has not had a successful physics-based model, for example, water, the most abundant and life-dependent, although the components of a successful model have been well-developed and successfully employed in applications, for examples, semiconductor physics-based solid-state electronics in communication (stereo, TV, PC, cell phone) and control (simple to complex robotics). The two missed culprits in physics are the long range order in the crystalline solid state which continues persistently into the higher kinetic energy fluidic liquid state, and also the dynamics of isolated molecules in a random ensemble of the gas phase at higher kinetic energies which continue persistently into the lower kinetic energy fluidic liquid state. The recent success of this new approach of combining the solid-state and gas-state to model the liquid state of pure water (such as the 80+ mega-ohm pure drinking water sold at the grocery stores for 75 cents) is described and extended to all the liquid states of materials in this presentation. [1] Binbin Jie, Tianhui Jie and Chihtang Sah, Studies of Water VI. Journal of Semiconductors, 2018, 39(11): 111001. [2] Bin Jie, Tianhui Jie, Chih-Tang Sah, submitted to APS March Meeting 2019.   

Exploring self-organized criticality in driven cold gases

Recent experiments with strongly interacting, driven Rydberg ensembles have unambiguously demonstrated aspects of self-organized criticality (SOC) in the dynamics of the Rydberg pseudospins. Such experiments present a means for precise control of the microscopics from which SOC emerges and offer a new playground for the exploration of SOC with cold atoms. Here we simulate the dynamics of such Rydberg ensembles through numerical integration of the corresponding effective field theory. In particular, we discuss an experimentally feasible loading scheme by which the prototypical avalanche dynamics can be maintained and controlled. This gives access to three distinct dynamical regimes: i) a subcritical regime of periodically occurring avalanches ii) an extended SOC regime featuring scale invariance and fractal real-space structures, and iii) a supercritical regime with constant avalanche activity. This relates Rydberg atom dynamics with SOC in neural networks, where similar scenarios have been observed. We sharpen this connection by analyzing the dependence of SOC on the size and dimensionality of the ensembles.   

Head-on Collisions of Vortex Rings with Solid Bodies

The head-on collision of vortex rings with slender wires creates complex vortex reconnection and breakdown behavior. Specifically, the interaction results in the rapid emergence of secondary vortical structures. These structures suggest that vortex lines are being created in the fluid; however, as, in the finite Reynolds number regime, vorticity must either close in on itself or begin or end on a boundary, the origin of the secondary structures is not well understood. We experimentally investigate the emergence and evolution of this behavior by varying the vortex ring dyeing technique, geometry of the wire, and Reynolds number. This allows us to characterize the interaction of the vortex core with the secondary vortical structures.   

Nonequilibrium power-law correlations in a system of tight-binding fermions with gapped spectrum

A quantum quench is explored in a system of tight-binding fermions in which a smooth, linearly-varying chemical potential is rapidly switched off at the same time a staggered chemical potential is turned on. The initial particle density profile is a ``domain wall'' shape and evolves unitarily under a Hamiltonian which possesses a gap in its spectrum. In the ground-state of the Hamiltonian generating time evolution, correlations decay exponentially with distance, while in this non-equilibrium setting, a steady state quickly forms within a central subsystem in which power-law correlations persist. The long-time average of the particle density, current and various correlation functions are shown to be obtainable from an effective momentum distribution which depends on the details of the Hamiltonian and the initial state. Intriguing similarities between the results in this model of free fermions and similar results obtained within interacting systems are discussed.   

Stochastic Simulations of Single-Cell Circadian Oscillations in Arabidopsis thaliana

Chemical oscillations are a universal feature of living systems. In plants, for example, the daily periodicity of many functions is regulated by the oscillatory expression of circadian gene networks present in each cell. We analyze the chemically reacting system that controls the circadian rhythms in cells of the plant Arabidopsis thaliana by numerically solving a continuous kinetic model whose parameters were deduced from experimental data [1]. We find that the model exhibits slowly decaying oscillations and is situated near a Hopf bifurcation in parameter space. Then we implement Gillespie’s Stochastic Simulation Algorithm to simulate the system at the single-cell level and account for random fluctuations in particle numbers [2]. Finally, we comment on the relationship between the two approaches and on the possible biological significance of the model’s mathematical features.

[1] Locke et al. Stochastic Simulations of Single-Cell Circadian Oscillations in Arabidopsis thaliana. J. Theor. Bio. 234 (2005) 383.
[2] Gillespie, Daniel T. Exact Stochastic Simulations of Coupled Chemical Reactions. J. Phys. Chem. Vol. 81, No. 25, 1977. 2340-2361.   

NSF IRES: Exploring the Effects of Single Point Mutations of Arabidopsis thaliana Cryptochrome 1 (AtCry1), a Plant Protein Involved in Blue Light Response

Cryptochromes are proteins that act as photoreceptors regulating development and the circadian clock in plants. It has been shown that mutations in cryptochromes, specifically AtCry1, alter the functionality of the proteins. These flavoprotein photoreceptors mediate growth, leaf expansion, and floral initiation. They act through blue-light dependent photoreduction of flavin adenine dinucleotide (FAD) via an electron transport chain. In the dark state, the flavin is oxidized and when stimulated with blue light, it is semi-reduced and in the active state which arguably causes protein conformational change and signal transduction. This photoreduction of FAD can be tracked using visible light absorption as the spectra of the oxidized and semi-reduced forms differ. Specifically, the oxidized FAD has a absorption at 450nm and once semi-reduced, the 450nm peak decreases and there is an increase in absorption at 550nm. Mutants studied show significant difference in appearance and plant growth in blue light when compared to native plants. Differences in absorption between mutant and native proteins were used to analyze potential differences in the photochemistry involved in plant growth.   

Membrane Simulations with Amyloid Beta

Amyloid Beta is a misformed protein that is a key characteristic of Alzheimer’s disease. A plethora of research has been carried out to determine the structure of amyloid beta and mechanisms behind the plaque formation. We model 1-3 amyloid beta peptides in 3 different configurations inside a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) membrane in order to simulate a key step in the formation of amyloid plaques: the formation of pores in the cell wall of neurons due to amyloid beta. Our preliminary findings identify a configuration of amyloid beta in the membrane that appears to promote the formation of pores.
  

Focused Ultrasound as a Replacement for Endodontic Therapy

Focused ultrasound has exhibited promising results as a therapeutic modality in its ability to minimize the invasiveness of a number of medical treatments that are physically and mentally traumatic to the patient. We propose the investigation of its use for non-invasive endodontic therapy (a.k.a. a “root canal”), with the ultimate goal of removing microbial infection from the root canal system of a contaminated tooth.
To avoid thermal damage to adjacent healthy tissues, we considered using the mechanical effects created by ultrasound, specifically that of cavitation. To generate proof-of-concept data, we designed, constructed, and tested a series of ultrasound transducers that delivered sufficiently low frequencies operating below 300 kHz and pressures below -30MPa to induce cavitation in degassed water with less than 3ppm. Our initial experiments have shown that sufficient ultrasound energy can be transmitted through intact ex vivo human teeth to elicit nonlinear streaming in the root canal of intact ex vivo human teeth. We have also demonstrated the use of equivalent parameters to kill bacteria. We will further determine and refine the optimal ultrasound parameters for eliciting bactericide in the intact tooth.