Crystal structure prediction by combining graph network and optimization algorithm
Predicting crystal structure prior to experimental synthesis is highly desirable. Here the authors propose a machine-learning framework combining graph network and optimization algorithms for crystal structure prediction, which is about three orders of magnitude faster than DFT-based approach.
Main Authors: | Guanjian Cheng, Xin-Gao Gong, Wan-Jian Yin |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2022-03-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-022-29241-4 |
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