Machine learning assisted search for Fe–Co–C ternary compounds with high magnetic anisotropy.
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| Název: | Machine learning assisted search for Fe–Co–C ternary compounds with high magnetic anisotropy. |
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| Autoři: | Xia, Weiyi, Sakurai, Masahiro, Liao, Timothy, Wang, Renhai, Zhang, Chao, Sun, Huaijun, Ho, Kai-Ming, Chelikowsky, James R., Wang, Cai-Zhuang |
| Zdroj: | APL Machine Learning; Dec2024, Vol. 2 Issue 4, p1-10, 10p |
| Témata: | ARTIFICIAL neural networks, CONVOLUTIONAL neural networks, MAGNETIC materials, MAGNETIC anisotropy, MAGNETIC properties |
| Abstrakt: | 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 |
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| Databáze: | Complementary Index |
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