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...

Full description

Bibliographic Details
Main Authors: Zhichao Lu, Xin Chen, Xiongjun Liu, Deye Lin, Yuan Wu, Yibo Zhang, Hui Wang, Suihe Jiang, Hongxiang Li, Xianzhen Wang, Zhaoping Lu
Format: Article
Language:English
Published: Nature Publishing Group 2020-12-01
Series:npj Computational Materials
Online Access:https://doi.org/10.1038/s41524-020-00460-x

Internet

https://doi.org/10.1038/s41524-020-00460-x

Similar Items