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RESEARCH PAPER · Science China Technological Sciences · 2024

Highly effective design of high GFA alloys with different metal-based and various components by machine learning

Yichuan Tang, Yifan He, ZhuoQun Fan, Zhongqi Wang, Chengying Tang

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Highly effective design of high GFA alloys with different metal-based and various components by machine learningOriginalOptimizing Glass Formation Ability and Magnetic Flux Density of High-Fe-Content Fe-Based Amorphous Alloys Using Interpretable Machine Learning0Composition design and crystallization behavior of Zr–Cu–Ni–Al bulk metallic glasses3Accurate prediction of magnetocaloric effect in NiMn‐based Heusler alloys by prioritizing phase transitions through explainable machine learning25Machine learning assisted design and preparation of Fe85Si2B8.5P3.5C1 amorphous/nanocrystalline alloy with high B and low H12Design and preparation of novel Fe-Si-B-P-C-Nb amorphous /nanocrystalline alloys guided by machine learning5A Review of Artificial Intelligence‐Driven Innovations in Soft Magnetic Materials Optimization: Current Trends and Future Horizons13Machine learning-driven design of rare metal doped niobium alloys with enhanced strength and ductility6Machine learning prediction of metallic glass forming ability: The pivotal role of relative energy1Machine learning on glass-forming ability of metallic glasses guided by domain knowledge0Data-driven prediction of thin-film metallic glass forming ability via Bayesian classification and experimental verification in the Cu–Zr–Al system0Optimization of A356.2 alloy based on explainable ensemble learning with 40% enhancement in mechanical properties0Design of Nanocrystalline Alloy for Reducing Motor Hysteresis Loss by Machine Learning0Synergistic capping strategy for oxidation-resistant copper nanoparticles enables low-resistivity printed flexible electronics1Yttrium-Enhanced Thermal Stability of Novel Fe-Based BMGs0

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  1. Optimizing Glass Formation Ability and Magnetic Flux Density of High-Fe-Content Fe-Based Amorphous Alloys Using Interpretable Machine Learning

    SSRN Electronic Journal · 2024-01-01

    Yichuan Tang, Yin Zhang, Ruonan Ma, Shaopeng Liu, Silong Li, Kun Wang, Minxia Fang, Kaiyan Cao, Chao Zhou, Chuanhui Cheng, Sen Yang

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  2. Composition design and crystallization behavior of Zr–Cu–Ni–Al bulk metallic glasses

    Intermetallics · 2024-07-06

    Changzhi Li, Shengnan Chen, Zhengqing Cai, Zhilin Shi, Haoran Zhang, Chao Nan Wei, M Ma

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  3. Accurate prediction of magnetocaloric effect in NiMn‐based Heusler alloys by prioritizing phase transitions through explainable machine learning

    Rare Metals · 2024-08-29

    Yichuan Tang, Kaiyan Cao, Ruonan Ma, Jia‐Bin Wang, Yin Zhang, Dongyan Zhang, Chao Zhou, Fanghua Tian, Minxia Fang, Sen Yang

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  4. Machine learning assisted design and preparation of Fe85Si2B8.5P3.5C1 amorphous/nanocrystalline alloy with high B and low H

    Materials & Design · 2024-11-17

    Shengdong Tang, Rui Sun, Yifan He, Guichang Liu, Ruixuan Wang, Yuqin Liu, Chengying Tang

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  5. Design and preparation of novel Fe-Si-B-P-C-Nb amorphous /nanocrystalline alloys guided by machine learning

    Progress in Natural Science Materials International · 2025-01-18

    Yifan He, Rui Sun, Shengdong Tang, Zilong Xu, Long Hou, Chaohao Hu, Chengying Tang, Yuqin Liu

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  6. A Review of Artificial Intelligence‐Driven Innovations in Soft Magnetic Materials Optimization: Current Trends and Future Horizons

    MetalMat · 2025-03-01

    Yichuan Tang, Shaopeng Liu, Silong Li, Ruonan Ma, Yue Li, Kun Wang, Minxia Fang, Chao Zhou, Sen Yang, Yin Zhang

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  7. Machine learning-driven design of rare metal doped niobium alloys with enhanced strength and ductility

    Journal of Materials Research and Technology · 2025-04-06

    Zhenqiang Xiong, ZhaoKun Song, Jianwei Li, Heran Wang, Xiaoxin Zhang, Bin Liang, Dong Wang

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  8. Machine learning prediction of metallic glass forming ability: The pivotal role of relative energy

    Journal of Non-Crystalline Solids · 2025-04-21

    Xiaohan Cheng, Ping Huang, Wang Fei

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  9. Machine learning on glass-forming ability of metallic glasses guided by domain knowledge

    Transactions of Nonferrous Metals Society of China · 2025-11-01

    Hong BO, Xu-dong CHEN, Li-bin LIU, Xiao-gang FANG, Jian-liang HU, Li-min WANG

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  10. Data-driven prediction of thin-film metallic glass forming ability via Bayesian classification and experimental verification in the Cu–Zr–Al system

    RSC Advances · 2026-01-01

    Xuliang Luo, Tero Mäkinen, Wenyi Huo, Silvia Bonfanti, Zhehao Chen, Kenichiro Mizohata, Kostas Sarakinos, Mikko J. Alava

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  11. Optimization of A356.2 alloy based on explainable ensemble learning with 40% enhancement in mechanical properties

    SSRN Electronic Journal · 2026-01-01

    Yin Zhang, Ruonan Ma, Yichuan Tang, Shaopeng Liu, yue li, Yifan He, Silong Li, Chang Huang, Minxia Fang, Sen Yang

    Read original paper ↗ ·

  12. Design of Nanocrystalline Alloy for Reducing Motor Hysteresis Loss by Machine Learning

    IEEE Transactions on Magnetics · 2026-02-10

    Tengcui Gao, Zilong Xu, Zhongwei Jiang, Zhuoqun Fan, Jiaqing Liu, Chengying Tang

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  13. Synergistic capping strategy for oxidation-resistant copper nanoparticles enables low-resistivity printed flexible electronics

    Applied Surface Science · 2026-06-30

    Haiqing Qiao, Jing Li, Xuhe Gong, Enhuai Yin, Ran Li, Kaikai Song, Xiaobo Chen

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  14. Yttrium-Enhanced Thermal Stability of Novel Fe-Based BMGs

    Metallurgical and Materials Transactions A · 2026-08-08

    Parisa Rezaei-Shahreza, Saeed Hasani, Amir Seifoddini, Marcin NABIALEK

    Read original paper ↗ ·
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