Green Research Group

While we can synthesize a vast range of molecular structures, we have far less control over the nonequilibrium processes that organize them into functional systems at nanometer and micron scales. However, living systems seem to have overcome this challenge, using flows of matter and energy to create multiscale materials, drive motion, regulate reaction networks, replicate structure, and process information. Our research develops theory for designing materials and devices that use chemical energy to perform these dynamical functions in the laboratory.

We develop theory and computational techniques for synthetic and biological materials—such as self-assembling structures in active materials and molecular switches for neuromorphic computing —that use reaction and transport processes to assemble, sustain, and reorganize structure or generate work. We build coarse-grained models and theory grounded in statistical mechanics, nonlinear dynamics, and stochastic thermodynamics. Using these models and data-driven inference, we quantify tradeoffs between speed, accuracy, stability, and energy use and infer mechanisms from experimental data. Our goal is to deliver predictive frameworks that guide experiments and enable the rational design of energy- efficient synthetic materials.