Coarse-grained simulations to predict structure and properties of polymer nanocomposites
Polymer Nanocomposites (PNC) are a new class of materials characterized by their large interfacial areas between the host polymer and nanofiller. This unique feature, due to the size of the nanofiller, is understood to be the cause of enhanced mechanical, electrical, optical, and barrier properties observed of PNCs, relative to the properties of the unfilled polymer. This interface can determine the miscibility of the nanofiller in the polymer, which, in turn, influences the PNC's properties. In addition, this interface alters the polymer's structure near the surface of the nanofiller resulting in heterogeneity of local properties that can be expressed at the macroscopic level.
Considering the polymer-nanoparticle interface significantly influences PNC properties, it is apparent that some atomistic level of detail is required to accurately predict the behavior of PNCs. Though an all-atom simulation of a PNC would be able to accomplish the latter, it is an impractical approach to pursue even with the most advanced computational resources currently available. In this contribution, we develop (1) an equilibrium coarse-graining method to predict nanoparticle dispersion in a polymer melt, (2) a dynamic coarse-graining method to predict rheological properties of polymer-nanoparticle melt mixtures, and (3) a numerical approach that includes interfacial layer effects and polymer rigidity when predicting barrier properties of PNCs.
In addition to the above, we study how particle and polymer characteristics affect the interfacial layer thickness as well as how the polymer-nanoparticle interface may influence the entanglement network in a polymer melt. More specifically, we use a mean-field theory approach to discern how the concentration of a semiflexible polymer, its rigidity and the particle's size determine the interfacial layer thickness, and the scaling laws to describe this dependency. We also utilize molecular dynamics and simulation techniques on a model PNC to determine if the polymer-nanoparticle interaction can influence the entanglement network of a polymer melt.