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Machine learning assisted search for Fe–Co–C ternary compounds with high magnetic anisotropy.

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Title: Machine learning assisted search for Fe–Co–C ternary compounds with high magnetic anisotropy.
Authors: Xia, Weiyi, Sakurai, Masahiro, Liao, Timothy, Wang, Renhai, Zhang, Chao, Sun, Huaijun, Ho, Kai-Ming, Chelikowsky, James R., Wang, Cai-Zhuang
Source: APL Machine Learning; Dec2024, Vol. 2 Issue 4, p1-10, 10p
Subject Terms: ARTIFICIAL neural networks, CONVOLUTIONAL neural networks, MAGNETIC materials, MAGNETIC anisotropy, MAGNETIC properties
Abstract: We employ a machine learning (ML)-guided framework to explore rare earth free magnetic materials, specifically focusing on Fe–Co–C ternary compounds for potential use in permanent magnets. Utilizing a specifically trained crystal graph convolutional neural network model, we efficiently screen a vast space of nearly a million substitutional structures to select 620 promising structures for further investigation by first-principles calculation. We predict five low-energy metastable Fe–Co–C compounds with formation energy less than 150 meV/atom above the convex hull. These compounds exhibit high magnetization (Js > 1.0 T) and significant magnetic anisotropy (K1 > 1.0 MJ/m3), making them promising candidates for permanent magnet applications. The phonon calculations indicate these compounds are dynamically stable. Our ML-guided framework demonstrates the utility of rapidly identifying novel materials with tailored magnetic properties. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
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Abstract:We employ a machine learning (ML)-guided framework to explore rare earth free magnetic materials, specifically focusing on Fe–Co–C ternary compounds for potential use in permanent magnets. Utilizing a specifically trained crystal graph convolutional neural network model, we efficiently screen a vast space of nearly a million substitutional structures to select 620 promising structures for further investigation by first-principles calculation. We predict five low-energy metastable Fe–Co–C compounds with formation energy less than 150 meV/atom above the convex hull. These compounds exhibit high magnetization (J<subscript>s</subscript> > 1.0 T) and significant magnetic anisotropy (K<subscript>1</subscript> > 1.0 MJ/m<sup>3</sup>), making them promising candidates for permanent magnet applications. The phonon calculations indicate these compounds are dynamically stable. Our ML-guided framework demonstrates the utility of rapidly identifying novel materials with tailored magnetic properties. [ABSTRACT FROM AUTHOR]
DOI:10.1063/5.0208761