His current research interests are in nanoscale self-assembly, soft-matter simulation, polymer rheology, biomimetic materials, and machine learning. The central focus of his work is to reveal the underlying microscopic origins of observed macroscopic material behaviors in order to advance the design of soft materials for applications in nanomedicine, energy devices, and stretchable electronics.
Research Areas:
- Engineering Health
- Health@Luddy - Crosscutting
- Data Science
- Intelligent Systems
- Molecular and Nanoscale Engineering
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 primary research thrusts to furnish fundamental mechanistic understanding and enable rational, application-specific design of advanced nanomaterials: 1) linking surface patterns and molecular-scale characteristics with adaptive structure and property control of soft-matter-based nanosystems, and 2) integrating machine learning with soft-matter simulation to enhance their performance and predictive power for rapid exploration of the high-dimensional material design space.
Interests:
- biological materials
- biomimetics
- electrolytes
- molecular dynamics (MD)
- nanomedicine
- self-assembly
- soft materials
- viscoelasticity
