Ab Initio Thermodynamic Sampling of Millions of Configurations in Many-Component Oxides Accelerated by Machine Learning

Shusuke Kasamatsu

Presentation information

Oral Session

A. Fundamentals » [A-5] Advanced Algorithms and Tools for Materials Informatics

[A5-O101] Oral 101

Mon. Dec 11, 2023 1:30 PM - 4:00 PM Session 2 (Room C-2)

Chair: Hiori Kino (NIMS), Milica Todorović (University of Turku), Tetsuya Fukushima (AIST)

2:10 PM - 2:30 PM

[A5-O101-03 (Symposium Invited)] Ab Initio Thermodynamic Sampling of Millions of Configurations in Many-Component Oxides Accelerated by Machine Learning

*Shusuke Kasamatsu¹, Tatsumi Aoyama², Yuichi Motoyama², Kazuyoshi Yoshimi², Akihide Kuwabara³, Takafumi Ogawa³, Junji Hyodo⁴, Yoshihiro Yamazaki⁴ (1. Yamagata Univ. (Japan), 2. Univ. of Tokyo (Japan), 3. Japan Fine Ceramics Center (Japan), 4. Kyushu Univ. (Japan))

Keywords:first principles, thermodynamics, active learning, complex oxides

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