Machine Learning Assisted Optimization of SmFe12-based Alloys

BOLYACHKIN Anton; SUBAGJA Toni; LI Jiangnan; ZHANG Jiasheng; ASHOK KRISHNASWAMY Srinithi; ABE Taichi; TANG Xin; TOZMAN KARANIKOLAS Pelin; KULESH Nikita; SEPEHRI AMIN Hossein; OHKUBO Tadakatsu; HONO Kazuhiro

Poster Machine Learning Assisted Optimization of SmFe12-based Alloys

BOLYACHKIN Anton (International Center for Young Scientists, National Institute for Materials Science) ; SUBAGJA Toni (Research Center for Magnetic and Spintronic Materials/Green Magnetic Materials Group, National Institute for Materials Science) ; LI Jiangnan (Research Center for Magnetic and Spintronic Materials/Magnetic Materials Analysis Group, National Institute for Materials Science) ; ZHANG Jiasheng (Research Center for Magnetic and Spintronic Materials/Green Magnetic Materials Group, National Institute for Materials Science) ; ASHOK KRISHNASWAMY Srinithi (Research Center for Magnetic and Spintronic Materials/Green Magnetic Materials Group, National Institute for Materials Science) ; ABE Taichi (Research Center for Structural Materials/Materials Evaluation Field/Structural Thermodynamics Group, National Institute for Materials Science) ; TANG Xin (Research Center for Magnetic and Spintronic Materials/Green Magnetic Materials Group, National Institute for Materials Science) ; TOZMAN KARANIKOLAS Pelin (Global Networking Division/International Center for Young Scientists, National Institute for Materials Science) ; KULESH Nikita (Research Center for Magnetic and Spintronic Materials/Green Magnetic Materials Group, National Institute for Materials Science) ; SEPEHRI AMIN Hossein (Research Center for Magnetic and Spintronic Materials/Green Magnetic Materials Group, National Institute for Materials Science) ; OHKUBO Tadakatsu (Research Center for Magnetic and Spintronic Materials, National Institute for Materials Science) ; HONO Kazuhiro (National Institute for Materials Science)

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BOLYACHKIN Anton, SUBAGJA Toni, LI Jiangnan, ZHANG Jiasheng, ASHOK KRISHNASWAMY Srinithi, ABE Taichi, TANG Xin, TOZMAN KARANIKOLAS Pelin, KULESH Nikita, SEPEHRI AMIN Hossein, OHKUBO Tadakatsu, HONO Kazuhiro. Machine Learning Assisted Optimization of SmFe12-based Alloys. https://doi.org/10.48505/nims.4857

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In this work, we conducted machine learning on an experimental dataset of SmFe12-based alloys with ThMn12-type crystal structure. The dataset comprised 908 samples collected from articles and our own experiments on the alloys which were obtained either by mechanical alloying or by melt-spinning followed by heat treatment. The descriptor of each sample consisted of the chemical composition and synthesis details. The importance of the features and their correlations were analyzed, then two gradient boosting regressors were trained to predict coercivity and remanence as the main targets. Next, a large feature space of (Sm,Zr)x(Fe,Ti,V)100-x melt spun samples with annealing temperatures ranging from 923 to 1373 K was examined to define a Pareto front of the competing targets. Finally, we proposed a list of the most prospective alloys for an experimental validation, the results of which will be reported, as well as other details of the machine learning on the SmFe12-based isotropic alloys.

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