2025-03-18 中国科学院（CAS）
＜関連情報＞
- https://english.cas.cn/newsroom/research_news/tech/202503/t20250318_905782.shtml
- https://advanced.onlinelibrary.wiley.com/doi/10.1002/adfm.202425588
超高磁化と超低保磁力を両立する鉄基アモルファス合金を人工知能で設計する Designing Fe-Based Amorphous Alloys With both Ultra-High Magnetization and Ultra-Low Coercivity Through Artificial Intelligence
Shiyu Yang, Bowen Zang, Mingliang Xiang, Fayuan Shen, Lijian Song, Meng Gao, Yan Zhang, Juntao Huo, Jun-Qiang Wang
Advanced Functional Materials Published: 27 February 2025
DOI:https://doi.org/10.1002/adfm.202425588
Abstract
Designing soft magnetic alloys with high magnetization and low coercivity is of special interest for application in high-frequency and high-power electric and electronic components. In this work, high-precision machine-learning models based on 536 different Fe-based amorphous alloys are developed. It reveals that the electronegativity difference (δχ) and mixing enthalpy (ΔHmix) of the alloying elements play critical roles in determining the saturated magnetization (Bs) of amorphous alloys. Specifically, smaller δχ can strengthen the biased distribution of spin-up and spin-down electrons as is revealed by ab initio simulations. Based on these findings, a series of advanced amorphous/nanocrystalline alloys with Bs higher than 1.90 T and coercivity (Hc) as low as 1.2 A m−1 are designed, which also have good amorphous forming ability owing to the suitable mixing enthalpy. The designed alloys with high Bs and low Hc hold promising application potentials in electronic components of high power density and low energy loss.
