(37b) A Systematic Coarse-Graining Method to Predict the Structure and Properties of Polymer-Nanoparticle Mixtures

The properties of polymeric materials are influenced by many length and time scales, which if accounted for in atomistic simulations would take an impractical amount of time to simulate. This is especially a problem for high molecular weight systems. For polymer-nanoparticle mixtures, added layers of complexity are introduced when predicting their properties due to the additional length scale in the system at the interface of the two components and the confinement effects between nanoparticles. To circumvent long simulations, we propose a systematic coarse-graining method that extracts the essential atomistic information of a polymer-nanoparticle mixture and uses it in a simulation at the mesoscopic level, which has the capability of simulating longer times and larger lengths enabling predictions of experimentally observable properties. Our coarse-graining scheme is two-fold: (1) equilibrium coarse-graining is done to obtain the coarse-grain interactions that ensure the nanoparticle structure is accurately reproduced and (2) dynamic coarse-graining is performed to obtain the parameters for the dissipative forces so that hydrodynamic effects are appropriately accounted for at the coarse-grain level. To validate our coarse-graining method, rheological properties of a model polymer-nanoparticle mixture are compared across length scales.