A micromechanical-based model of stimulus responsive liquid crystal elastomers

Stimulus responsive elastomers are advanced engineered materials that perform desired functionalities when triggered by external stimuli. Liquid crystal (LCEs) one important example exhibit reversible actuation cycled above and below their nematic-to-isotropic transition temperature. Here, we propose a micromechanical-based model is centered on the evolution of chain distribution tensor LCE network. Our model, framed within statistical network, enables mesoscale description mechanical response under an thermal stimulus. We compare to prior experimental observations bending 3D printed elements with controlled director alignment.