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An accurate and transferable machine learning interatomic potential for nickel

Engineering and Technology

An accurate and transferable machine learning interatomic potential for nickel

X. Gong, Z. Li, et al.

This groundbreaking research by Xiaoguo Gong, Zhuoyuan Li, A. S. L. Subrahmanyam Pattamatta, Tongqi Wen, and David J. Srolovitz unveils a magnetism-hidden Deep Potential model for nickel, offering precise predictions of essential material properties crucial for advancing applications in engineering and technology.

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