Accelerated prediction of atomically precise cluster structures using on-the-fly machine learning
Abstract The chemical and structural properties of atomically precise nanoclusters are of great interest in numerous applications, but predicting the stable structures of clusters can be computationally expensive. In this work, we present a procedure for rapidly predicting low-energy structures of n...
Main Authors: | Yunzhe Wang, Shanping Liu, Peter Lile, Sam Norwood, Alberto Hernandez, Sukriti Manna, Tim Mueller |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2022-08-01
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Series: | npj Computational Materials |
Online Access: | https://doi.org/10.1038/s41524-022-00856-x |
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