[SY-D5] Symposium D-5

[SY-D5] Computational exploration of strong permanent magnet compounds

Invited

^○Takashi Miyake^1,2,3 (1.CD-FMat, AIST, Japan, 2.ESICMM, NIMS, Japan, 3.CMI², NIMS, Japan)

Modern strong magnets are rare-earth magnets in which high saturation magnetization and high Curie temperature come from transition-metal 3d electrons, and strong magnetorcystalline anisotropy originates from rare-earth 4f electrons [1]. There are various types of crystal structures and chemical composition, and exploration of a new magnet compound is a hot topic. Among them, RFe₁₂-type compounds with the ThMn₁₂ structure are attracting renewed interest because of their high iron content. Recently synthesized NdFe₁₂N_x film has higher saturation magnetization and anisotropy field than Nd₂Fe₁₄B, although its bulk phase is thermodynamically unstable. I will present a first-principles study on the effect of element substitution on magnetism and structural stability. I will also discuss how machine learning accelerates magnetic-materials discovery. Application to the Curie temperature of RFe₁₂-type compounds shows that Bayesian optimization offers an efficient way to optimize chemical composition of magnet compounds. Kernel ridge regression using orbital-field matrix as a descriptor reproduces the magnetic moment and formation energy of thousands of transition-metal compounds in reasonable accuracy [2], which can be utilized for virtual screening of new magnetic compounds. Bayesian optimization approach to crystal structure prediction is also presented [3].
[1] Takashi Miyake and Hisazumi Akai, J. Phys. Soc. Jpn. 87, 041009 (2018).
[2] T.L. Pham et al., Sci. Tech. Adv. Mater. 18, 756 (2017).
[3] T. Yamashita et al., Phys. Rev. Mater. 2, 013803 (2018).