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...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-11-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-022-00914-4 |