Rchr
J-GLOBAL ID:200901086880067400
Update date: Dec. 04, 2020
Tamura Tomoyuki
タムラ トモユキ | Tamura Tomoyuki
Affiliation and department:
Job title:
Associate Professor
Research theme for competitive and other funds (2):
- 2018 - 現在 添加剤による層構造制御を軸としたLi伝導性酸化物材料のデータ駆動型機能創出
- 2014 - 2018 全構造・全元素・全吸収端内殻励起スペクトル計算法の確立による物質計測の新展開
Papers (16):
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Tomoyuki Tamura, Masayuki Karasuyama. Prediction of formation energies of large-scale disordered systems via active-learning based executions of ab initio local-energy calculations: a case study on a Fe random grain boundary model with millions of atoms. Physical Review Materials. 2020. 4. 113602-1-113602-13
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Hidetoshi Miyazaki, Tomoyuki Tamura, Masashi Mikami, Kosuke Watanabe, Ide Naoki, Osman Murat Ozkendir, Yoichi Nishino. Machine-Learning-based Prediction of Lattice Thermal Conductivity for Half-Heusler Compounds using Atomic Information. arXiv.org. 2020
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Shinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama. Multi-objective Bayesian Optimization using Pareto-frontier Entropy. Proceedings of The 37th International Conference on Machine Learning (ICML 2020). 2020
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Masayuki Karasuyama, Hiroki Kasugai, Tomoyuki Tamura, Kazuki Shitara. Computational design of stable and highly ion-conductive materials using multi-objective bayesian optimization: Case studies on diffusion of oxygen and lithium. Computational Materials Science. 2020. 184. 109927
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Tomoyuki Tamura, Masayuki Karasuyama. Active-learning-based efficient prediction of ab initio atomic energy: a case study on a Fe random grain boundary model with millions of atoms. arXiv.org. 2019
more...
MISC (1):
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Introducing Information Science into Grain Boundary Property Research. 2020. 55. 9. 656-661
Lectures and oral presentations (66):
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粒界物性研究に向けた計算科学と情報科学の融合
(第30回格子欠陥フォーラム 2020)
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ニューラル・ネットワーク力場を用いたSiOの相分離過程のMDシミュレーション
(第30回日本MRS年次大会 2020)
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機械学習に基づいた第一原理XANESスペクトルの予測
(第30回日本MRS年次大会 2020)
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Li-Si-O材料の構造欠陥の第一原理XANESシミュレーション
(第30回日本MRS年次大会 2020)
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粒界物性研究に向けた情報科学の導入
(第30回日本MRS年次大会 2020)
more...
Education (1):
- - 2004 The University of Tokyo
Professional career (1):
Work history (6):
Committee career (6):
Association Membership(s) (2):
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