Hierarchical modelling of polystyrene melts: from soft blobs to atomistic resolution. Issue 2 (13th December 2018)

• Record Type: Journal Article
• Authors: Zhang, Guojie; Chazirakis, Anthony; Harmandaris, Vagelis A.; Stuehn, Torsten; Daoulas, Kostas Ch.; Kremer, Kurt
• Is Part Of: Soft matter. Volume 15:Issue 2(2018)
• Page Start: 289
• Page End: 302
• Publication Date: 2018-12-13
• Subjects: Soft condensed matter -- Periodicals; 530.413
• DOI: 10.1039/c8sm01830h
• Languages: English
• ISSNs: 1744-683X

Abstract

Abstract : A hierarchical backmapping simulation method, involving models with three different resolutions, is developed to equilibrate large atomistically-resolved samples of long polystyrene 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 is first to represent polymers by chains of large soft blobs (spheres) and efficiently equilibrate the melt on large scales. 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. We consider polystyrene (PS) which is sufficiently complex to serve method development because of stereo-chemistry and bulky side groups. Our backmapping strategy bridges mesoscopic and atomistic scales by incorporating a blob-based, a moderately coarse-grained (CG), and a united-atom model of PS. We demonstrate that the generic blob-based model can be parameterised to reproduce the mesoscale properties of a specific polymer – here PS. The moderately CG model captures stereo-chemistry. 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.