Modeling Shape Transformations in Liquid Crystal Elastomers - A Machine Learning Approach to Inverse Design

Watch a seminar presentation exploring the modeling of shape transformations in liquid crystal elastomers (LCE) and the development of machine learning approaches for inverse design. Discover how these stimuli-responsive, programmable actuators undergo shape-morphing in response to environmental changes through GPU-based finite element simulations. Learn about the mechanisms behind topological defects in LCE thin coatings and their role in complex surface transformations. Explore the newly discovered Frank-Read source mechanism in nematic liquid crystals, which drives disclination loop emissions similar to dislocation loops in crystalline solids. Gain insights into controlling microstructural evolution in both passive and active nematic liquid crystals, presented by Professor Robin Selinger from Kent State University at the INI Seminar Room 2.