Theory for dynamic matter: designing mechanisms for dissipative nanomaterials

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Professor Jason R. Green of the University of Massachusetts Boston is supported by an award from the Chemical Theory, Models and Computational Methods Program in the Chemistry Division to advance our fundamental understanding of how chemistry controls the form and the function of active materials. Active materials are materials designed to have one or more properties that can be significantly changed in a controlled fashion by external stimuli such as temperature, light, or chemical reactions. In the laboratory, chemical reactions are used to assemble, sustain, regulate, and destroy the structure of materials made from active, responsive molecules. By manipulating the chemical reactions, one can tune their properties. Such materials have many potential applications, for example in drug delivery and biosensing. However, the properties of these materials depend on the history and the details of how the structure was formed. As a result, it is a challenge to predict the yield and mechanical behavior from the properties of the constituent molecular building blocks. Professor Green and coworkers are developing theoretical frameworks to overcome this challenge. Their goal is to provide insight into the dynamic ability of matter to find alternative routes to stable, functional structures when fueled by chemical energy. Professor Green is also creating open-science computational notebooks that contain accessible, computationally tractable, and experimentally-relevant models for self-assembly.Self-assembly has practical promise as a simple technique to synthesize complex materials. Molecular components organize into active materials that can only sustain structure transiently as they dissipate energy. The principal challenges are understanding the time dependence of material properties and the effect of changing reaction conditions. This project is developing appropriate theoretical frameworks for understanding how non-equilibrium forces collectively drive structure formation and sculpt the vast space of assembly pathways. The goal is to predict which pathways are typical and which are rare at the macroscopic scale from stochastic chemical-kinetics that accurately model experiments. This research is making three major contributions: advancing in the modeling and simulation of the nonequilibrium assembly of active materials, advancing in the theory and practice for identifying the assembly patterns and causal mechanisms of structure formation, and collecting the stochastic-thermodynamics for a database of self-assembly models at and evolving away from equilibrium.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.