Our research aims to understand the fundamental mechanisms underlying the shape, assembly, and flow behavior of soft materials at the nanoscale in order to learn the design principles for controlling their macroscopic functional properties for medical, energy, and electronics applications. We develop computational models, simulations, and AI/ML methods to provide reliable predictions for the structural and dynamical properties of deformable nanoparticles, virus capsids, electrolyte solutions, machine lubricants, hydrocarbons, and polymers. A prominent theme is to explore the effects of nanostructure elasticity (physical and entropic)—aka softness—on the assembly and transport outcomes. We have two broad research thrusts to furnish fundamental understanding and advance the rational design of soft materials: 1) linking nanoscale structure with mechanistic behavior and property control of soft materials, and 2) integrating nanoscale simulations with AI/ML techniques for rapid exploration of the soft matter design space.
