(2jb) Integrating Molecular Modeling and Machine Learning for Insight into Bulk and Interfacial Phenomena

I am currently a postdoctoral research fellow in Prof. Zhen-Gang Wang's research group at the California Institute of Technology. I received two fellowships to sponsor my postdoc: 1) Engineering postdoctoral fellowship (eFellows) administered by the American Society for Engineering Education with funding provided by the National Science Foundation (see https://efellows.asee.org/about for more info) and 2) President's Postdoctoral Fellowship Program from Caltech (see https://ppfp.caltech.edu/ for more info). My expertise is bulk and interfacial properties of charged (specifically weak) polymers as well as energy storage using electric double layer capacitors. I use different computational methods such as classical density functional theory (cDFT) and monte carlo simulation to model and explore electrostatic effects in polymers and soft matter related to coacervation, surface adhesion, and capacitive performance.

I obtained my M.S. under the supervision of Dr. Jianzhong Wu at University of California, Riverside. My research focused on understanding the relation between ion structure (e.g., neutral chain length) and the material's characteristics (e.g., pore size distribution, surface area, etc.) on the capacitance and dynamics in supercapacitors using cDFT and machine learning. I then transitioned my focus towards modeling the charge regulation from small molecules to polymers and surfaces during my PhD with Dr. Jianzhong Wu. We developed molecular thermodynamic models to describe amino acids and polypeptides to describe their bulk and interfacial behavior in semi-quantitative agreement with experiments for activity coefficient, apparent equilibrium constant, solubility, osmotic coefficient, adsorption, and interfacial adhesion. In addition, we developed new theoretical techniques such as Ising density functional theory which allows for a complete description of the inter- and intramolecular interactions present in weak polyelectrolytes in non-uniform fluids (e.g., near a surface). In my postdoctoral work at Caltech with Dr. Zhen-Gang Wang, I investigate the importance of long-range electrostatic correlations on the polymer conformation and coacervation behavior of bioadhesive polypeptides.

Research Interests

My research group will focus on understanding the thermodynamic properties of polymers (specifically, ion-containing) at the bulk and near an interface. Particular topics of interest include bioadhesion, drug delivery, surface fouling, and energy storage. These topics require knowledge on how and when the polymers form a coacervate, adsorb to a surface, and regulate the local environment as well as the impact that the interface has on the coacervate and adsorption characteristics. Of specific interest is the non-equilibrium and dynamical nature of many of these processes which has been difficult to explore computationally. While my group will take advantage of the latest theoretical and simulation tools available, we also will look to advance the current state-of-art through the development of new theoretical techniques. Further exploration of these topics will utilize machine learning algorithms to design and optimize molecular models as well as predict the thermodynamic properties of polymers.

Teaching Interests

My academic training and prior teaching experiences has equipped me with the background necessary to teach core curriculum courses in chemical engineering. In particular, I am interested in teaching 'Thermodynamics' at the graduate and undergraduate level. One special topic course that I would like to teach is 'Statistical Mechanics' due to its broad reach and use in both theoretical and experimental research. Another course I would like to offer is 'Molecular Thermodynamics of Complex Fluids' which will focus on recent developments in applied thermodynamics and molecular simulations. A major part of this course will be to have each student identify a research problem and demonstrate how one can tackle this problem along with the expected research. This course would be valuable to undergraduate students at the junior and senior level by introducing them to computational/theoretical research and to current graduate students to incorporate computational methods into their research.