Machine Learning-based Analysis and Prediction of Hard Magnetic Performance for Melt-spun NdFeB Magnets
WEN Jintai1, HU Huaigu2, AN Jiangshan1, HAN Ting1, LI Xinyu1, HU Jifan1,3,*
1 School of Materials Science and Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China 2 College of Mechanical and Electrical Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China 3 School of Physics, Shandong University, Jinan 250100, China
Abstract: The permanent magnetic performance of NdFeB magnets strongly depends on the alloy composition and process parameters. Machine lear-ning is based on mathematical and information science methods, using existing rapidly quenched NdFeB magnet data to predict the magnetic properties of NdFeB magnets. In this work, the eXtreme Gradient Boosting (XGBoost) algorithm was used to analyze the permanent magnet performance of rapidly quenched NdFeB magnets. The results show that the machine learning model developed from ensemble learning XGBoost algorithm has a higher prediction accuracy and better stability for the permanent magnet performance of rapidly quenched NdFeB magnets than other algorithms. Then the machine model based on XGBoost algorithm proposed here is utilized to optimize and predict new melt-spun NdFeB mate-rials with high permanent magnetic performance.
温晋太, 胡怀谷, 安江山, 韩婷, 李欣俞, 胡季帆. 基于机器学习的快淬NdFeB磁体永磁性能分析与预测[J]. 材料导报, 2025, 39(8): 24030158-7.
WEN Jintai, HU Huaigu, AN Jiangshan, HAN Ting, LI Xinyu, HU Jifan. Machine Learning-based Analysis and Prediction of Hard Magnetic Performance for Melt-spun NdFeB Magnets. Materials Reports, 2025, 39(8): 24030158-7.
1 Sagawa M, Fujimura S, Togawa N, et al. Journal of Applied Physics, 1984, 55(6), 2083. 2 Croat J J, Herbst J F, Lee R W, et al. Journal of Applied Physics, 1984, 55(6), 2078. 3 Brown D, Ma B M, Chen Z. Journal of Magnetism and Magnetic Materials, 2002, 248(3), 432. 4 Davies B E, Mottram R S, Harris I R. Materials Chemistry and Physics, 2001, 67(1-3), 272. 5 Ma B M, Herchenroeder J W, Smith B, et al. Journal of Magnetism and Magnetic Materials, 2002, 239(1-3), 418. 6 Honshima M, Ohashi K. Journal of Materials Engineering and Performance, 1994, 3, 218. 7 Deng R L, Liang D N, Huang G K, et al. China Equipment Engineering, 2021(12), 242 (in Chinese). 邓汝彬, 梁德宁, 黄国康, 等. 中国设备工程, 2021(12), 242. 8 Zhang Y, Xu X. Computational Materials Science, 2020, 179, 109583. 9 Zhang Y, Xu X. Physica C: Superconductivity and Its Applications, 2020, 573, 1353633. 10 Zhang Y, Xu X. Journal of Magnetism and Magnetic Materials, 2020, 512, 166998. 11 Agrawal A, Deshpande P D, Cecen A, et al. Integrating Materials and Manufacturing Innovation, 2014, 3, 90. 12 Karak S K, Chatterjee S, Bandopadhyay S. Powder Technology, 2015, 274, 217. 13 Pilania G, Mannodi-Kanakkithodi A, Uberuaga B P, et al. Scientific Reports, 2016, 6(1), 19375. 14 Jinnouchi R, Asahi R. The Journal of Physical Chemistry Letters, 2017, 8(17), 4279. 15 Zhou T, Jhamb S, Liang X, et al. Chemical Engineering Science, 2018, 183, 95. 16 Aghaji M Z, Fernandez M, Boyd P G, et al. European Journal of Inorganic Chemistry, 2016, 2016(27), 4505. 17 Sharma V, Wang C, Lorenzini R G, et al. Nature Communications, 2014, 5(1), 4845. 18 Madaan N, Shiju N R, Rothenberg G. Catalysis Science & Technology, 2016, 6(1), 125. 19 Gómez-Bombarelli R, Aguilera-Iparraguirre J, Hirzel T D, et al. Nature Materials, 2016, 15(10), 1120. 20 Stanev V, Oses C, Kusne A G, et al. npj Computational Materials, 2018, 4(1), 29. 21 Olivares-Amaya R, Amador-Bedolla C, Hachmann J, et al. Energy & Environmental Science, 2011, 4(12), 4849. 22 Hou T Y, Sun Y H, Sun S P, et al. Materials Reports, 2022, 36(6), 165(in Chinese). 侯腾跃, 孙炎辉, 孙舒鹏, 等. 材料导报, 2022, 36(6), 165. 23 Stern S, Hexner D, Rocks J W, et al. Physical Review X, 2021, 11(2), 021045. 24 Wickramasinghe C S, Amarasinghe K, Marino D L, et al. IEEE Access, 2021, 9, 131824. 25 Sutton R S, Barto A G. Reinforcement learning: an introduction, MIT Press, USA, 2018. 26 Mobarak M H, Mimona M A, Islam M A, et al. Applied Surface Science Advances, 2023, 18, 100523. 27 Chu L H, Zha W S, Liu J Y, et al. Chinese Rare Earths, 2009, 30(2), 39(in Chinese). 储林华, 查五生, 刘锦云, 等. 稀土, 2009, 30(2), 39. 28 Lian L X, Liu Y, Song D. Journal of Functional Materials, 2005, 36(8), 1178. 29 Vapnik V. New York, 1995, 10, 978. 30 Cheng W D. Journal of Magnetic Materialsr Devices, 2015, 46(3), 17(in Chinese). 程文德. 磁性材料及器件, 2015, 46(3), 17. 31 Zhou S H, Zha W S, Wang X Z. Chinese Rare Earths, 2012, 33(1), 61(in Chinese). 周胜海, 查五生, 王向中. 稀土, 2012, 33(1), 61. 32 Zhang Y, Xu X. Journal of Superconductivity and Novel Magnetism, 2021, 34(11), 2711. 33 Qiao Z, Dong S Z, Li Q, et al. Journal of Alloys and Compounds, 2023, 963. 34 Hearst M A, Dumais S T, Osuna E, et al. IEEE Intelligent Systems and Their Applications, 1998, 13(4), 18. 35 Trevor E. Canadian Journal of Mathematics, 1963, 15, 584. 36 Friedman H J. The Annals of Statistics, 2001, 29(5), 1189. 37 Chen T, Guestrin C. In: Proceedings of the 22nd Acm Sigkdd International Conference on Knowledge Discovery and Data Mining. San Francisco, USA, 2016, pp. 785. 38 Lai B, Li Y F, Wang H J, et al. Journal of Rare Earths, 2014, 32(6), 514. 39 Tian Z, Li S, Peng K, et al. Materials Science and Engineering: A, 2004, 380(1-2), 143. 40 Sun W, Li S, Quan M. Journal of Magnetism and Magnetic Materials, 1997, 176(2-3), 307. 41 Chang W C, Wu S H, Ma B M, et al. Journal of Magnetism and Magnetic Materials, 1997, 167(1-2), 65. 42 Harland C L, Davies H A. Journal of Alloys and Compounds, 1998, 281(1), 37. 43 Caglar S, Kilicaslan M F, Atasoy A, et al. Journal of Materials Science: Materials in Electronics, 2021, 32, 2338. 44 Gholamipour R, Beitollahi A, Marghusian V K, et al. Metallurgical and Materials Transactions A, 2006, 37, 1581. 45 Zhou W, Chang C, Inoue A, et al. Journal of Applied Physics, 2015, 117(12), 123905. 46 Liu A Z, Rahman I Z, Rahman M A, et al. Journal of Materials Processing Technology, 1996, 56(1-4), 571. 47 Cheng Z H, Kronmüller H, Shen B G. Applied Physics Letters, 1998, 73, 1586. 48 Chang W C, Hsing D M. Journal of Applied Physics, 1996, 79(8), 4843. 49 Marashi S P H, Abedi A, Kaviani S, et al. Journal of Physics D: Applied Physics, 2009, 42(11), 115410. 50 Malakouti S M, Menhaj M B, Suratgar A A. Cleaner Engineering and Technology, 2023, 15, 100664. 51 Xi B W, Xiong G, Kozin K A, et al. Results in Control and Optimization, 2023, 13, 100320. 52 Zhang X, Liu C A. Journal of Econometrics, 2023, 235(1), 280. 53 Chen H, Lundberg S, Lee S I. Explainable AI in Healthcare and Medicine: Building a Culture of Transparency and Accountability, 2021, pp. 261. 54 Shapley L. A value for n-person games. contributions to the theory of games Ⅱ (1953)307-317, Princeton University Press, USA, 1997, pp.69.
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2025, Vol. 39 
