Interpretable machine-learning strategy for soft-magnetic property and thermal stability in Fe-based metallic glasses

Interpretable machine-learning strategy for soft-magnetic property and thermal stability in Fe-based metallic glasses

Abstract Fe-based metallic glasses (MGs) have been extensively investigated due to their unique properties, especially the outstanding soft-magnetic properties. However, conventional design of soft-magnetic Fe-based MGs is heavily relied on “trial and error” experiments, and thus difficult to balanc...

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Autores principales: Zhichao Lu, Xin Chen, Xiongjun Liu, Deye Lin, Yuan Wu, Yibo Zhang, Hui Wang, Suihe Jiang, Hongxiang Li, Xianzhen Wang, Zhaoping Lu
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
Materias:
Materials of engineering and construction. Mechanics of materials
TA401-492
Computer software
QA76.75-76.765
Acceso en línea:https://doaj.org/article/41ec3b121f114d65904cce3446f4e76f
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https://doaj.org/article/41ec3b121f114d65904cce3446f4e76f

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