no code implementations • 26 Apr 2022 • Hiori Kino, Hieu-Chi Dam, Takashi Miyake, Riichiro Mizoguchi
The proposed method was applied to materials informatics to demonstrate the systematic representation of expert knowledge and its usefullness.
no code implementations • 4 Feb 2021 • Guangzong Xing, Takahiro Ishikawa, Yoshio Miura, Takashi Miyake, Terumasa Tadano
We report the effects of lattice dynamics on thermodynamic stability of binary $R_{1-x}$Fe$_x$ $(0<x<1)$ compounds ($R$: rare-earth elements, Y, Ce, Nd, Sm, and Dy) at finite temperature predicted by first-principles calculation based on density functional theory (DFT).
Materials Science Computational Physics
no code implementations • 3 Feb 2021 • Takahiro Ishikawa, Taro Fukazawa, Guangzong Xing, Terumasa Tadano, Takashi Miyake
Modern high-performance permanent magnets are made from alloys of rare earth and transition metal elements, and large magnetization is achieved in the alloys with high concentration of transition metals.
Materials Science
no code implementations • 20 Aug 2020 • Duong-Nguyen Nguyen, Tien-Lam Pham, Viet-Cuong Nguyen, Hiori Kino, Takashi Miyake, Hieu-Chi Dam
We propose a data-driven method to extract dissimilarity between materials, with respect to a given target physical property.
no code implementations • 23 Mar 2019 • Tran-Thai Dang, Tien-Lam Pham, Hiori Kino, Takashi Miyake, Hieu-Chi Dam
In this study, we establish a basis for selecting similarity measures when applying machine learning techniques to solve materials science problems.