Suppression of Creep in Model Polymer Nanocomposites

While the elastic properties of polymer nanocomposites (PNCs) have been widely studied, the ability of nanoparticles (NPs) to suppress creep in a polymer matrix has received comparatively less attention, and creep suppression is essential for the use of composites in structural applications. It is believed that the primary mechanism of reinforcement in PNCs is the presence of a layer near the NPs' surfaces where the polymer monomers have modified mobility. Thus, understanding how the dynamics in this layer changes as a function of stress, NP size, and polymer-nanoparticle interaction is critical. In this work, we use molecular dynamics simulation to investigate the PNC's creep response with different NP sizes and polymer-nanoparticle interactions. Our results indicate that the small NPs with strong polymer-nanoparticle interaction can best suppress materials' creep response and stiffen the material. A recently developed, machine-learning field called softness is applied to describe the local structures in our composites. We find that the softness is modified near the NP surfaces and largely reduced for attractive polymer-particle interactions, though the range over which softness is modified differs from the range over which the relaxation time is different from the bulk.