Soft Materials at the Nanoscale

The aim of our research group is to understand the shape, assembly, and flow of soft materials at the nanoscale in order to advance their functional properties for medical and energy applications. We design computational models of soft materials such as deformable nanoparticles, virus capsids, electrolyte solutions, machine lubricants, and polymers. Our approach examines the behavior of these model systems using analytical tools, simulation techniques, and machine learning methods, with each tool aiding the other. 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 machine learning with nanoscale simulations for rapid exploration of the soft material design space. Visit our GitHub organization softmaterialslab to learn more about our projects.