Hierarchical modeling of polystyrene melts: From soft blobs to atomistic resolution

TL;DR

This paper introduces a hierarchical backmapping method that efficiently equilibrates high-molecular-weight polystyrene melts by transitioning from soft blob models to detailed atomistic representations, enabling accurate multiscale simulations.

Contribution

The authors develop a novel hierarchical backmapping strategy that bridges mesoscopic and atomistic scales for polymers, specifically demonstrating its effectiveness on polystyrene.

Findings

The method accurately reproduces mesoscale properties of polystyrene.

Backmapped melts show structural and conformational agreement with reference data.

Hierarchical approach improves efficiency of equilibrating complex polymer melts.

Abstract

We demonstrate that hierarchical backmapping strategies incorporating generic blob-based models can equilibrate melts of high-molecular-weight polymers, described with chemically specific, atomistic, models. The central idea behind these strategies, is first to represent polymers by chains of large soft blobs (spheres) and efficiently equilibrate the melt on mesoscopic scale. Then, the degrees of freedom of more detailed models are reinserted step by step. The procedure terminates when the atomistic description is reached. Reinsertions are feasible computationally because the fine-grained melt must be re-equilibrated only locally. To develop the method, we choose a polymer with sufficient complexity. We consider polystyrene (PS), characterized by stereochemistry and bulky side groups. Our backmapping strategy bridges mesoscopic and atomistic scales by incorporating a blob-based, a moderately CG, and a united-atom model of PS. We demonstrate that the generic blob-based model can be parameterized to reproduce the mesoscale properties of a specific polymer -- here PS. The moderately CG model captures stereochemistry. To perform backmapping we improve and adjust several fine-graining techniques. We prove equilibration of backmapped PS melts by comparing their structural and conformational properties with reference data from smaller systems, equilibrated with less efficient methods.