My group's research expertise lies in development of coarse-grained models and computational approaches involving liquid state theory, molecular simulation, and machine learning for designing and characterizing macromolecular materials. Specifically, in this talk, I will present a couple examples from my group’s recent work that demonstrate how we use these computational approaches together with experimental results from collaborators to obtain molecular-level insight into structure and phase behavior in polymer nanocomposites and solutions.

Connecting molecular modeling, simulations, and machine learning with experiments to advance polymer science and engineering

Fall 2022 abstracts, posters, and presentations will launch in mid-September.

ACS Fall 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.