Rational Design of Polymer Nanocomposites to Advance Their Thermomechanical Performance via Predictive Multiscale Modeling

Understanding and predicting the thermomechanical responses of polymer nanocomposites are challenging as they are greatly influenced by many factors, such as interfacial energy and filler volume fraction, giving rise to the presence of nanoscale interfaces. To better design of polymer nanocomposites, we have recently established an atomistically informed coarse grained (CG) modeling approach to investigate how the nanoscale interfaces and molecular characteristics influence the mechanical and glass transition properties of polymer nanocomposites. Taking cellulose reinforced polymer nanocomposite as a relevant model system, we present a multiscale materials by design framework using CG modeling combining with advanced computational algorithms for prediction of thermomechanical properties of nanocomposites. Our established framework is validated by recent experiments and breaks new ground in predicting key structure and property relationships for optimum and tailored design of polymer nanocomposite materials.