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博士(工学)(東京大学)
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修士(工学)(東京大学)
Details of the Researcher
Awards 9
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第35回トーキン科学技術賞奨励賞
2025/03 トーキン科学技術振興財団
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第64回原田奨励賞
2024/07 公益財団法人本多記念会
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奨励賞
2024/07 日本金属学会
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工学研究科長賞(研究)
2020/03 東京大学
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応用物理学会講演奨励賞
2019/03 第46回応用物理学会 2019年春季学術講演会
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Best Poster Award
2017/10 CPMD2017
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Best Poster Award
2015/11 2nd International Symposium on Frontiers in Materials Science
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Best Poster Award
2015/09 International Conference on Advanced Materials IUMRS-ICAM 2015,
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優秀口頭発表賞
2014/03 LCA学会
Papers 28
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Bayesian Optimization with Gaussian Processes Assisted by Deep Learning for Material Designs
Shin Kiyohara, Yu Kumagai
The Journal of Physical Chemistry Letters 5244-5251 2025/05/18
Publisher: American Chemical Society (ACS)DOI: 10.1021/acs.jpclett.5c00592
ISSN: 1948-7185
eISSN: 1948-7185
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Oxygen Defect Engineering of Hexagonal Perovskite Oxides to Boost Catalytic Performance for Aerobic Oxidation of Sulfides to Sulfones
Keiju Wachi, Masashi Makizawa, Takeshi Aihara, Shin Kiyohara, Yu Kumagai, Keigo Kamata
ADVANCED FUNCTIONAL MATERIALS 2025/04/03
ISSN: 1616-301X
eISSN: 1616-3028
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Universal Polaronic Behavior in Elemental Doping of MoS2 from First-Principles
Soungmin Bae, Ibuki Miyamoto, Shin Kiyohara, Yu Kumagai
ACS Nano 2024/12/02
Publisher: American Chemical Society (ACS)ISSN: 1936-0851
eISSN: 1936-086X
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First-principles calculations on dislocations in MgO
Shin Kiyohara, Tomohito Tsuru, Yu Kumagai
Science and Technology of Advanced Materials 25 (1) 2024/09/02
Publisher: Informa UK LimitedDOI: 10.1080/14686996.2024.2393567
ISSN: 1468-6996
eISSN: 1878-5514
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Target Material Property‐Dependent Cluster Analysis of Inorganic Compounds
Nobuya Sato, Akira Takahashi, Shin Kiyohara, Kei Terayama, Ryo Tamura, Fumiyasu Oba
Advanced Intelligent Systems 2024/08/05
Publisher: WileyISSN: 2640-4567
eISSN: 2640-4567
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Copper Phosphate Nanostructures as Catalysts for the Direct Methane Oxidation
Aoi Matsuda, Takeshi Aihara, Shin Kiyohara, Yu Kumagai, Michikazu Hara, Keigo Kamata
ACS Applied Nano Materials 7 (9) 10155-10167 2024/05/10
eISSN: 2574-0970
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Band Alignment of Oxides by Learnable Structural-Descriptor-Aided Neural Network and Transfer Learning
Shin Kiyohara, Yoyo Hinuma, Fumiyasu Oba
Journal of the American Chemical Society 146 (14) 9697-9708 2024/03/28
Publisher: American Chemical Society (ACS)DOI: 10.1021/jacs.3c13574
ISSN: 0002-7863
eISSN: 1520-5126
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Nanosized Ti-Based Perovskite Oxides as Acid-Base Bifunctional Catalysts for Cyanosilylation of Carbonyl Compounds
Takeshi Aihara, Wataru Aoki, Shin Kiyohara, Yu Kumagai, Keigo Kamata, Michikazu Hara
ACS APPLIED MATERIALS & INTERFACES 15 (14) 17957-17968 2023/04
ISSN: 1944-8244
eISSN: 1944-8252
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Unique Atomic and Electronic Structures of Oxygen Vacancies in Amorphous SnO2 from First Principles and Informatics
Shin Kiyohara, David Mora-Fonz, Alexander Shluger, Yu Kumagai, Fumiyasu Oba
JOURNAL OF PHYSICAL CHEMISTRY C 2022/11
ISSN: 1932-7447
eISSN: 1932-7455
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Simulated carbon K edge spectral database of organic molecules
Kiyou Shibata, Kakeru Kikumasa, Shin Kiyohara, Teruyasu Mizoguchi
SCIENTIFIC DATA 9 (1) 2022/05
DOI: 10.1038/s41597-022-01303-8
eISSN: 2052-4463
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Automatic determination of the spectrum-structure relationship by tree structure-based unsupervised and supervised learning
Shin Kiyohara, Kakeru Kikumasa, Kiyou Shibata, Teruyasu Mizoguchi
ULTRAMICROSCOPY 233 2022/03
DOI: 10.1016/j.ultramic.2021.113438
ISSN: 0304-3991
eISSN: 1879-2723
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Quantification of the Properties of Organic Molecules Using Core-Loss Spectra as Neural Network Descriptors
Kakeru Kikumasa, Shin Kiyohara, Kiyou Shibata, Teruyasu Mizoguchi
ADVANCED INTELLIGENT SYSTEMS 4 (1) 2022/01
eISSN: 2640-4567
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Radial Distribution Function from X-ray Absorption near Edge Structure with an Artificial Neural Network
Shin Kiyohara, Teruyasu Mizoguchi
JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN 89 (10) 2020/10
ISSN: 0031-9015
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Learning excited states from ground states by using an artificial neural network
Shin Kiyohara, Masashi Tsubaki, Teruyasu Mizoguchi
NPJ COMPUTATIONAL MATERIALS 6 (1) 2020/06
DOI: 10.1038/s41524-020-0336-3
eISSN: 2057-3960
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Prediction of interface and vacancy segregation energies at silver interfaces without determining interface structures
Ryuken Otani, Shin Kiyohara, Kiyou Shibata, Teruyasu Mizoguchi
APPLIED PHYSICS EXPRESS 13 (6) 2020/06
DOI: 10.35848/1882-0786/ab8b6c
ISSN: 1882-0778
eISSN: 1882-0786
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Machine learning approaches for ELNES/XANES
Teruyasu Mizoguchi, Shin Kiyohara
MICROSCOPY 69 (2) 92-109 2020/04
ISSN: 2050-5698
eISSN: 2050-5701
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Machine learning for structure determination and investigating the structure-property relationships of interfaces
Hiromi Oda, Shin Kiyohara, Teruyasu Mizoguchi
JOURNAL OF PHYSICS-MATERIALS 2 (3) 2019/07
eISSN: 2515-7639
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Quantitative estimation of properties from core-loss spectrum via neural network
Shin Kiyohara, Masashi Tsubaki, Kunyen Liao, Teruyasu Mizoguchi
JOURNAL OF PHYSICS-MATERIALS 2 (2) 2019/04
eISSN: 2515-7639
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Data-driven approach for the prediction and interpretation of core-electron loss spectroscopy
Shin Kiyohara, Tomohiro Miyata, Koji Tsuda, Teruyasu Mizoguchi
SCIENTIFIC REPORTS 8 2018/09
DOI: 10.1038/s41598-018-30994-6
ISSN: 2045-2322
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Element-based optimization of waste ceramic materials and glasses recycling
Ichiro Daigo, Shin Kiyohara, Tomoki Okada, Daisaku Okamoto, Yoshikazu Goto
RESOURCES CONSERVATION AND RECYCLING 133 375-384 2018/06
DOI: 10.1016/j.resconrec.2017.11.012
ISSN: 0921-3449
eISSN: 1879-0658
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Searching the stable segregation configuration at the grain boundary by a Monte Carlo tree search
Shin Kiyohara, Teruyasu Mizoguchi
JOURNAL OF CHEMICAL PHYSICS 148 (24) 2018/06
DOI: 10.1063/1.5023139
ISSN: 0021-9606
eISSN: 1089-7690
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Bayesian optimization for efficient determination of metal oxide grain boundary structures
Shun Kikuchi, Hiromi Oda, Shin Kiyohara, Teruyasu Mizoguchi
PHYSICA B-CONDENSED MATTER 532 24-28 2018/03
DOI: 10.1016/j.physb.2017.03.006
ISSN: 0921-4526
eISSN: 1873-2135
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Effective search for stable segregation configurations at grain boundaries with data-mining techniques
Shin Kiyohara, Teruyasu Mizoguchi
PHYSICA B-CONDENSED MATTER 532 9-14 2018/03
DOI: 10.1016/j.physb.2017.05.019
ISSN: 0921-4526
eISSN: 1873-2135
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Atomic-scale nanostructures by advanced electron microscopy and informatics Peer-reviewed
Teruyasu Mizoguchi, Shin Kiyohara, Yuichi Ikuhara, Naoya Shibata
Nanoinformatics 157-178 2018/01/15
DOI: 10.1007/978-981-10-7617-6_8
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Transfer Learning to Accelerate Interface Structure Searches
Hiromi Oda, Shin Kiyohara, Koji Tsuda, Teruyasu Mizoguchi
JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN 86 (12) 2017/12
ISSN: 0031-9015
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Prediction of interface structures and energies via virtual screening
Shin Kiyohara, Hiromi Oda, Tomohiro Miyata, Teruyasu Mizoguchi
SCIENCE ADVANCES 2 (11) 2016/11
ISSN: 2375-2548
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Acceleration of stable interface structure searching using a kriging approach
Shin Kiyohara, Hiromi Oda, Koji Tsuda, Teruyasu Mizoguchi
JAPANESE JOURNAL OF APPLIED PHYSICS 55 (4) 2016/04
ISSN: 0021-4922
eISSN: 1347-4065
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Investigation of Segregation of Silver at Copper Grain Boundaries by First Principles and Empirical Potential Calculations
Shin Kiyohara, Teruyasu Mizoguchi
FRONTIERS IN MATERIALS SCIENCE (FMS2015) 1763 2016
DOI: 10.1063/1.4961349
ISSN: 0094-243X
Misc. 2
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Prediction of ELNES and Quantification of Structural Properties Using Artificial Neural Network
Shin Kiyohara, Masashi Tsubaki, Teruyasu Mizoguchi
Microscopy and Microanalysis 2020
Publisher: Cambridge University PressDOI: 10.1017/S1431927620020449
ISSN: 1435-8115 1431-9276
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Quantitative prediction of properties of organic molecules from ELNES via artificial neural network
Kakeru Kikumasa, Shin Kiyohara, Kiyou Shibata, Teruyasu Mizoguchi
Microscopy and Microanalysis 2020
Publisher: Cambridge University PressDOI: 10.1017/S1431927620015585
ISSN: 1435-8115 1431-9276
Books and Other Publications 1
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Machine learning in chemistry : the impact of artificial intelligence
Cartwright, Hugh M.
Royal Society of Chemistry 2020
ISBN: 9781788017893
Presentations 34
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ディープカーネルラーニングを用いたベイズ最適化による材料探索
清原慎, 熊谷悠
第72回応用物理学会春季学術講演会 2025/03/16
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機械学習を用いた酸化物表面における機能予測 Invited
清原慎
第7回日本表面真空学会若手部会研究会 2025/01/09
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マテリアルズインフォマティクスを用いた格子欠陥の構造・物性予測および解析手法の開発 Invited
清原慎
日本金属学会2024年秋期講演大会 2024/09/18
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MgO中の転位すべりに関する第一原理計算
清原慎, 都留智仁, 熊谷悠
日本セラミック協会2024年年会 2024/03/16
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機械学習を用いたイオン化ポテンシャル・電子親和力の予測
清原 慎, 高橋 亮, 日沼 洋陽, 大場 史康
第70回 応用物理学会春季学術講演会 2023/03
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Analysis of Atomic and Electronic Structures of Neutral Oxygen Vacancies in Amorphous SnO 2 by First Principles Calculation and Machine Learning
2022/08
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Analysis of Unique Atomic and Electronic Structures of Oxygen Vacancies in Amorphous SnO 2 by First-Principles Calculations and Machine Learning
MRM2021 2021/12
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機械学習を用いたELNES/XANES解析法の開発 Invited
清原慎
日本顕微鏡学会 顕微鏡計測インフォマティクス 2021/12
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Prediction of ELNES and quantification of structural properties using artificial neural network
S. Kiyohara, M. Tsubaki, T. Mizoguchi
Microscopy & Microanalysis 2020 2020/07
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機械学習を用いた結晶粒界構造決定とCore-loss分光法への応用 Invited
清原慎
産業科学ナノテクノロジーセンター若手セミナー 2020/02
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Data-Driven Approach for Core-Loss Spectroscopy—Prediction of Spectra and Quantification of Properties
S. Kiyohara, M. Tsubaki, T. Mizoguchi
MRS2019 fall meeting 2019/11
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機械学習を用いたELNES/XANES スペクトル解析手法の開発 Invited
清原慎, 椿真史, 溝口照康
応用物理学会 2019年秋季学術講演会 2019/09
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Machine learning for Core-loss spectrum: Automated interpretation via both supervised and unsupervised learning
S. Kiyohara, T. Mizoguchi
AMTC6 2019/06
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機械学習を用いたELNESの予測と物性定量化
清原慎, 椿真史, 溝口照康
顕微鏡学会 第75回学術講演会 2019/06
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ニューラルネットワークを用いた内殻電子励起スペクトルの予測
清原慎, 椿真史, 溝口照康
日本金属学会2019年春期講演大会 2019/03
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機械学習を用いた内殻電子励起スペクトルからの物性予測
清原慎, 椿真史, 溝口照康
応用物理学会 2019年春季学術講演会 2019/03
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Machine Learning Approach to Discover the Correlation between Core-loss Spectra and Materials Information via Clustering and Decision Trees
S. Kiyohara, T. Mizoguchi
MRS2018 fall meeting 2018/11
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MACHINE LEARNING-AIDED INTERPRETAION AND PREDICTION OF CORE-LOSS SPECTRUM
S. Kiyohara, T. Miyata, T. Mizoguchi
IMRC2018 2018/08
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ACCELARATION OF INTERFACE STRUCTURE SEARCHING VIA BAYSIAN OPTMIZATION AND TRANSFER LEARNING
S. Kiyohara, T. Mizoguchi
IMRC2018 2018/08
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モンテカルロ木探索を用いた粒界偏析挙動の解析
清原慎, 溝口照康
日本セラミック協会 2018年年会春 2018/03
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Data Driven Approach to Reconstruct and Interpret ELNES/XANES Spectra
S. Kiyohara, T. Miyata, T. Mizoguchi
CPMD2017 2017/10
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データ駆動型アプローチに基づく ELNES スペクトルの再現及び解釈
清原慎, 溝口照康
第40回ケモインフォマティクス討論会 2017/10
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Reconstruction and interpretation of ELNES using sparse representation
S. Kiyohara, T. Miyata, T. Mizoguchi
EDGE 2017: Enhanced Data Generated by Electrons 2017/05
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非負値行列因子分解を用いたELNESスペクトルの再現と解釈
清原慎, 溝口照康
日本顕微鏡学会第73回学術講演会 2017/05
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モンテカルロ木探索を用いた粒界における偏析サイトと濃度の決定
清原慎, 溝口照康
日本セラミック協会 2017年年会春 2017/03
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複数の統計手法を用いた不純物の粒界偏析サイトと濃度の最適化
清原慎, 溝口照康
第19回情報論的学習理論ワークショップ IBIS2016 2016/10
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Prediction of interface structure and energy with an aid of information science
S. Kiyohara, T. Mizoguchi
The 2015 International Chemical Congress of Pacific Basin Societies 2015/12
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Application of Non-linear Regression to predict Grain Boundary Structure and Energy
S. Kiyohara, T. Mizoguchi
2nd International Symposium on Frontiers in Materials Science 2015/11
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Effective Search for Grain Boundary Structure with Data Mining
S. Kiyohara, T. Mizoguchi
International Conference on Advanced Materials IUMRS-ICAM 2015 2015/10
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マテリアルズインフォマティクスに基づいた結晶粒界構造およびエネルギーの効率的探索
清原慎, 溝口照康
第35回エレクトロセラミックス研究討論会 2015/10
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Informatics approach to predict grain boundary structure and energy
清原慎, 溝口照康
日本顕微鏡学会第71回学術講演会 2015/05
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情報科学的手法を用いた結晶粒界構造およびエネルギーの予測
清原慎, 溝口照康
日本金属学会2015年春期講演大会 2015/03
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ガラスを中心とした酸化物系セラミックスの循環利用システムの設計
第 9 回日本LCA学会研究発表会 2014/03
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ガラスを中心とした酸化物系セラミックスの循環利用システムの設計
清原慎, 醍醐市朗, 後藤芳一
第 9 回日本LCA学会研究発表会 2014/03
Research Projects 1
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機械学習に基づいた電荷密度予測手法の構築
清原 慎
Offer Organization: 日本学術振興会
System: 科学研究費助成事業
Category: 若手研究
Institution: 東北大学
2023/04/01 - 2025/03/31