Minisymposium Presentation

My research group’s expertise lies in the development of molecular models and simulation methods as well as machine learning workflows towards designing and characterizing new and improved soft macromolecular materials. In this talk, I will present our recent work towards developing machine learning workflows (e.g., CREASE [1,2]) to interpret soft materials’ structural characterization data from small angle scattering and microscopy. These methods provide an objective understanding of the distributions of length scales and patterns found within hierarchical structures in polymer materials. These workflows also help automate and/or accelerate structural characterization tasks towards establishing design-structure-property relationships in synthetic- & bio- polymers and formulations.

1. Christian M. Heil, et al. ACS Central Science (2022), 8, 7, 996-10072. Christian. M. Heil et al. JACS Au (2023) 3, 3, 889–904