(621b) A Systematic Coarse-Graining Method to Predict the Properties of Polymer Nanocomposites

It is well known that the properties of polymeric materials are influenced by multiple length and time scales that are intimately connected. This creates a problem for high molecular weight systems where the size and time requirements for atomistic simulations of such materials are pragmatically impossible to fulfill even for the upper echelon of supercomputers. On top of this, an added layer of complexity is introduced when predicting the properties of polymer nanocomposites (PNCs) due to the mutli-component nature of the system. To deal with these issues, we propose a systematic coarse-graining method that extracts the essential atomistic details of a PNC and uses this information in simulations at the mesoscopic level, which have the capability of simulating longer times and larger lengths. This allows for the prediction of experimentally observable PNC properties which are based on an atomistic foundation. In our coarse-graining scheme, molecular dynamics (MD) simulations are performed to ascertain the atomistic information required to be matched at the mesoscopic scale, which information at this scale is obtained through dissipative particle dynamics (DPD) simulations. Our coarse-graining scheme is two-fold: (1) equilibrium coarse-graining is done on polymer-polymer and polymer-particle interactions via the well established iterative Boltzmann inversion method, and (2) dynamic coarse-graining is performed to obtain the parameters for the dissipative forces occurring between polymers as well as polymers and particles that are inherently generated when the resolution of the simulation is lowered. To check our coarse-graining method, rheological properties of the atomistic and mesoscopic scales are compared.