A Multi-State Comparative Coarse-Grained Modeling of Semi-Crystalline Poly(vinyl alcohol)

Abstract

Poly(vinyl alcohol) (PVA) is a promising material with exceptional mechanical properties, adhesion, and abrasion resistance. To accurately predict its mesoscopic properties, such as crystal size and morphology, while improving computational efficiency, novel coarse-grained (CG) potentials are developed using iterative Boltzmann inversion (IBI) coupled with density correction. These CG potentials are derived from various thermodynamic states based on two different mapping schemes to overcome the limitations of traditional CG potentials in predicting the glass transition, crystallization, and melting temperatures. By comparing the simulation results obtained from these CG potentials with atomistic molecular dynamics (MD) simulations and experimental data, we identify the most suitable CG model of semicrystalline PVA that effectively reproduces both atomistic structures and thermodynamic properties. In particular, X-ray diffraction (XRD) experiments are used to further validate the accuracy of the CG potentials. This multistate comparative CG strategy provides efficient and accurate CG models for deeper investigations of PVA and other semicrystalline polymers. Our study paves the way for establishing a systematic and comprehensive database of CG potentials, serving as a valuable resource for future research on semicrystalline polymers.

A Multi-State Comparative Coarse-Grained Modeling of Semi-Crystalline Poly(vinyl alcohol)