| Microstructural diagram for steel based on crystallography with machine learning K Tsutsui, H Terasaki, T Maemura, K Hayashi, K Moriguchi, S Morito Computational Materials Science 159, 403-411, 2019 | 35 | 2019 |
| A methodology of steel microstructure recognition using SEM images by machine learning based on textural analysis K Tsutsui, H Terasaki, K Uto, T Maemura, S Hiramatsu, K Hayashi, ... Materials Today Communications 25, 101514, 2020 | 27 | 2020 |
| A computational experiment on deducing phase diagrams from spatial thermodynamic data using machine learning techniques K Tsutsui, K Moriguchi Calphad 74, 102303, 2021 | 14 | 2021 |
| Effect of Mo addition on hydrogen segregation at α-Fe grain boundaries: A first-principles investigation of the mechanism by which Mo addition improves hydrogen embrittlement … K Ito, Y Tanaka, K Tsutsui, T Omura Computational Materials Science 218, 111951, 2023 | 12 | 2023 |
| First-principles computational tensile test of γ-Fe grain boundaries considering the effect of magnetism: Electronic origin of grain boundary embrittlement due to Zn segregation K Ito, Y Tanaka, T Mitsunobu, T Kohtake, K Tsutsui, H Sawada Physical Review Materials 6 (5), 053604, 2022 | 11 | 2022 |
| Interpretability of deep learning classification for low-carbon steel microstructures T Maemura, H Terasaki, K Tsutsui, K Uto, S Hiramatsu, K Hayashi, ... Materials Transactions 61 (8), 1584-1592, 2020 | 11 | 2020 |
| Analysis of grain-boundary segregation of hydrogen in bcc-Fe polycrystals via a nano-polycrystalline grain-boundary model K Ito, Y Tanaka, K Tsutsui, H Sawada Computational Materials Science 225, 112196, 2023 | 10 | 2023 |
| Are quasiparticles and phonons identical in Bose–Einstein condensates? K Tsutsui, Y Kato, T Kita Journal of the Physical Society of Japan 85 (12), 124004, 2016 | 10 | 2016 |
| Studying Superfluid Transition of a Dilute Bose Gas by Conserving Approximations K Tsutsui, T Kita Journal of the Physical Society of Japan 81 (11), 114002, 2012 | 8 | 2012 |
| Analysis of grain boundary embrittlement by Cu and Sn in paramagnetic by first-principles computational tensile test K Ito, T Mitsunobu, Y Ishiguro, Y Kohigashi, K Tsutsui Physical Review Materials 6 (9), 093603, 2022 | 7 | 2022 |
| Lifetime of Single-Particle Excitations in a Dilute Bose–Einstein Condensate at Zero Temperature K Tsutsui, T Kita Journal of the Physical Society of Japan 83 (3), 033001, 2014 | 7 | 2014 |
| Ground-State Energy and Condensate Density of a Dilute Bose Gas Revisited K Tsutsui, T Kita Journal of the Physical Society of Japan 82 (6), 063001, 2013 | 5 | 2013 |
| Quantum correlations of ideal Bose and Fermi gases in the canonical ensemble K Tsutsui, T Kita Journal of the Physical Society of Japan 85 (11), 114603, 2016 | 4 | 2016 |
| Mixing effects of SEM imaging conditions on convolutional neural network-based low-carbon steel classification K Tsutsui, K Matsumoto, M Maeda, T Takatsu, K Moriguchi, K Hayashi, ... Materials Today Communications 32, 104062, 2022 | 3 | 2022 |
| ANNNI model descriptions on structural energetics for a wide variety of metallic polytypes composed of close-packed layers K Moriguchi, T Miyakawa, S Ogane, R Sato, K Tsutsui, Y Tanaka MRS Advances 6, 163-169, 2021 | 2 | 2021 |
| 低炭素鋼溶接部ミクロ組織の機械学習に関する研究 寺崎秀紀， 筒井和政， 森口晃治， 林宏太郎， 森戸茂一 溶接学会誌 88 (7), 536-539, 2019 | 2 | 2019 |
| 鉄鋼分野における深層学習技術の活用の現状 筒井， 和政， 難波， 時永， 木原， 研吾， 平田， 松尾， 翔平， 伊藤， 一真 鉄と鋼 109 (6), 464-489, 2023 | 1 | 2023 |
| HOT-ROLLED STEEL SHEET AND CORRESPONDING PRODUCTION METHOD S Yabu, K Hayashi, K Hayashi, K TSUTSUI | | 2023 |
| Hot-rolled steel sheet M Yoshida, H Shuto, K Tsutsui, K Hayashi US Patent App. 18/021,066, 2023 | | 2023 |
| Hot rolled steel sheet Y Shohei, K Tsutsui, T Kuwayama US Patent App. 18/007,621, 2023 | | 2023 |
