[G] Hard Magnetic Materials

[273] Compositional optimization of SmFe₁₂-based alloys accelerated by machine learning

*Anton Bolyachkin¹, Jiangnan Li¹, Ashok Srinithi^1,2, Jiasheng Zhang¹, Xin Tang¹, Pelin Tozman¹, Hossein Sepehri-Amin¹, Tadakatsu Ohkubo¹, Kazuhiro Hono¹ (1. NIMS、2. Univ. Tsukuba)

Keywords:Permanent magnet、ThMn₁₂、Coercivity、Machine learning

A search for composition of SmFe₁₂-based alloys and their optimal synthesis conditions leading to the highest coercivity was performed using machine learning on experimental dataset.