A machine learning enabled hybrid optimization framework for efficient coarse-graining of a model polymer

A machine learning enabled hybrid optimization framework for efficient coarse-graining of a model polymer

Abstract This work presents a framework governing the development of an efficient, accurate, and transferable coarse-grained (CG) model of a polyether material. The framework combines bottom-up and top-down approaches of coarse-grained model parameters by integrating machine learning (ML) with optim...

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Bibliographic Details
Main Authors: Zakiya Shireen, Hansani Weeratunge, Adrian Menzel, Andrew W. Phillips, Ronald G. Larson, Kate Smith-Miles, Elnaz Hajizadeh
Format: Article
Language:English
Published: Nature Portfolio 2022-11-01
Series:npj Computational Materials
Online Access:https://doi.org/10.1038/s41524-022-00914-4

Internet

https://doi.org/10.1038/s41524-022-00914-4

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