Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties

Accelerating amorphous polymer electrolyte screening by learning to reduce errors in molecular dynamics simulated properties

Screening polymer electrolytes for batteries is extremely expensive due to the complex structures and slow dynamics. Here the authors develop a machine learning scheme to accelerate the screening and explore a space much larger than past studies.

Bibliographic Details
Main Authors: Tian Xie, Arthur France-Lanord, Yanming Wang, Jeffrey Lopez, Michael A. Stolberg, Megan Hill, Graham Michael Leverick, Rafael Gomez-Bombarelli, Jeremiah A. Johnson, Yang Shao-Horn, Jeffrey C. Grossman
Format: Article
Language:English
Published: Nature Portfolio 2022-06-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-022-30994-1

Internet

https://doi.org/10.1038/s41467-022-30994-1

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