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Recent advances and outstanding challenges for machine learning interatomic potentials
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AI
DOI：10.1038/s43588-023-00561-9.png)
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Abstract
En 中文
Machine learning interatomic potentials (MLIPs) enable materials simulations at extended length and time scales with near-ab initio accuracy. They have broad applications in the study and design of materials. Here, we discuss recent advances, challenges, and the outlook for MLIPs.
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