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

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.