Multiscale Modeling of Soft Matter
The bottom-up prediction of the physical properties of polymers and soft materials at multiple time and length scales is one of the grand challenges in engineering and soft matter physics. To address this issue, we have recently established an Energy-Renormalization (ER) approach to coarse-graining polymers and soft materials and predicting their temperature-dependent behaviors by exploiting polymer physics, glass theories, and mechanics. This achievement has addressed one of the critical challenges (i.e., the temperature transferability issue) in multiscale modeling of polymers. The established ER approach and computational algorithms are one of the essential contributions under the scope of the Materials Genome Initiative (MGI).
Materials-by-Design for Polymer Nanocomposites
Nanostructured polymer materials (i.e., thin films and nanocomposites) have been widely applied in engineering and technology. At a nanoscale, their thermomechanical performances are strongly influenced by the surfaces and interfacial interactions with filler and substrate materials. Using multiscale modeling, our research has uncovered how the chemically specific structures and intermolecular interactions govern the size-dependent behaviors of polymer thin films under nanoconfinement. We have established a materials-by-design framework to predict the glass transition, modulus and toughness of polymer nanocomposites by applying advanced computational techniques (i.e., coarse-graining and machine learning) and by drawing the “thin film-composite” analogy.
Thermomechanical Behaviors of Architectured Materials
The emergence of graphene and other sheet-like 2D materials offers great promise for advancing the performance of next-generation materials. Employing a multiscale modeling approach, our research has uncovered that the multilayer graphene can achieve remarkably high toughness by initiating stick-slip and strain localization mechanisms under loading. Recently, we have explored the thermomechanical behaviors of bulk graphene materials composed of disoriented nanosheets (so-called graphene “melt”). Remarkably, our simulation predicts that the graphene melt exhibits fluid-like properties analogous to linear-chain polymers, having a high glass-transition temperature. Our results, for the first time, demonstrate an analogy between graphene melt and polymers through theoretical considerations, which is crucial to develop an extension of structure-property relationships for sheet materials.