General-purpose machine-learned potential for 16 elemental metals and their alloys

General-purpose machine-learned potential for 16 elemental metals and their alloys

Abstract Machine-learned potentials (MLPs) have exhibited remarkable accuracy, yet the lack of general-purpose MLPs for a broad spectrum of elements and their alloys limits their applicability. Here, we present a promising approach for constructing a unified general-purpose MLP for numerous elements...

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Main Authors: Keke Song, Rui Zhao, Jiahui Liu, Yanzhou Wang, Eric Lindgren, Yong Wang, Shunda Chen, Ke Xu, Ting Liang, Penghua Ying, Nan Xu, Zhiqiang Zhao, Jiuyang Shi, Junjie Wang, Shuang Lyu, Zezhu Zeng, Shirong Liang, Haikuan Dong, Ligang Sun, Yue Chen, Zhuhua Zhang, Wanlin Guo, Ping Qian, Jian Sun, Paul Erhart, Tapio Ala-Nissila, Yanjing Su, Zheyong Fan
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-024-54554-x
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https://doi.org/10.1038/s41467-024-54554-x

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