Improving rotational isomeric state theory for application to mechanical properties prediction

Abstract

Rotational isomeric state (RIS) theory has long been used to predict mechanical response trends in polymeric materials based on the polymer chain conformation it addresses. Successful adaptation of this methodology to the prediction of elastic moduli would provide a powerful tool for guiding ionomer fabrication. Recently, a multiscale modeling approach to the material stiffness prediction of ionic polymer has been developed. It applies traditional RIS theory in combination with a Monte Carlo methodology to develop a simulation model for polymer chain conformation on a nanoscopic level. A large number of end-to-end chain lengths are generated from this model and are then used to estimate the probability density function which is used as an input parameter to enhance existing energetics-based macroscale models of ionic polymer for material stiffness prediction. This work improves this Mark-Curro Monte Carlo methodology by adapting the RIS theory in a way to overcome early terminations of polymer chain while simulating the conformation of polymer chains and thus obtains more realistic values of chain length. One solvated Nafion ® case is considered. The probability density function for chain length is estimated with the most appropriate Johnson family method applied. The stiffness prediction is considered as a function of total molecular weight.