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Kazumasa Tsutsui

Observed name: Kazumasa TSUTSUI
ORCID: 0000-0002-7620-0768
Observed ORCID: 0000-0002-7620-0768
OpenAlex ID: A5014550180
A methodology of steel microstructure recognition using SEM images by machine learning based on textural analysis
2020 · Kazumasa Tsutsui, Hidenori Terasaki, et al. · Materials Today Communications · 51
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 resistance in high-strength steels
2022 · Kazuma Ito, Yuta Tanaka, et al. · Computational Materials Science · 45
Microstructural diagram for steel based on crystallography with machine learning
2018 · Kazumasa Tsutsui, Hidenori Terasaki, et al. · Computational Materials Science · 41
Analysis of grain-boundary segregation of hydrogen in bcc-Fe polycrystals via a nano-polycrystalline grain-boundary model
2023 · Kazuma Ito, Yuta Tanaka, et al. · Computational Materials Science · 38
Interpretability of Deep Learning Classification for Low-Carbon Steel Microstructures
2020 · Tatsuya Maemura, Hidenori Terasaki, et al. · MATERIALS TRANSACTIONS · 24
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Current Trends on Deep Learning Techniques Applied in Iron and Steel Making Field: A Review
2024 · Kazumasa Tsutsui, Tokinaga Namba, et al. · ISIJ International · 23
A computational experiment on deducing phase diagrams from spatial thermodynamic data using machine learning techniques
2021 · Kazumasa Tsutsui, Koji Moriguchi · Calphad · 23
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
2022 · Kazuma Ito, Yuta Tanaka, et al. · Physical Review Materials · 18
Mixing effects of SEM imaging conditions on convolutional neural network-based low-carbon steel classification
2022 · Kazumasa Tsutsui, Kazushi Matsumoto, et al. · Materials Today Communications · 13
Analysis of grain boundary embrittlement by Cu and Sn in paramagnetic γ−Fe by first-principles computational tensile test
2022 · Kazuma Ito, Takuya Mitsunobu, et al. · Physical Review Materials · 10
Current Trends on Deep Learning Techniques Applied in Iron and Steel Making Field: A Review
2022 · Kazumasa Tsutsui, Tokinaga Namba, et al. · 鐵と鋼 : 日本鐡鋼協會々誌 · 5
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ANNNI model descriptions on structural energetics for a wide variety of metallic polytypes composed of close-packed layers
2021 · Koji Moriguchi, Taku Miyakawa, et al. · MRS Advances · 5
Studying Superfluid Transition of a Dilute Bose Gas by Conserving Approximations
2012 · Kazumasa Tsutsui, Takafumi Kita · Journal of the Physical Society of Japan · 5
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Enhancing Scanning Electron Microscopy Analysis of Low-Carbon Steel: A Generative Adversarial Network-Based Approach for Image Standardization
2025 · Kazumasa Tsutsui, Koutarou Hayashi, et al. · MATERIALS TRANSACTIONS · 4
Quantum Correlations of Ideal Bose and Fermi Gases in the Canonical Ensemble
2016 · Kazumasa Tsutsui, Takafumi Kita · Journal of the Physical Society of Japan · 4
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Effects of Re-ignition and Coke Breeze Reduction on Sinter Microstructure in Sintering Process
2025 · Keisuke Hirano, Kazumasa Tsutsui, et al. · 鐵と鋼 : 日本鐡鋼協會々誌 · 1
(Digital Presentation) Development of an Eam-Type Interatomic Potential Model Reproducing Theoretical Energetics in Polytype Structures
2022 · Shinya Ogane, Riku Sato, et al. · ECS Meeting Abstracts · 1
Micro- and Macroscopic Numerical Analyses on Effect of Repulsive Exclusion Zones on Interstitial Particle Diffusivity in Bcc Lattice Based on Diffusion Path Network Model
2022 · Daichi Akahoshi, Kazuto Kawakami, et al. · ISIJ International
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Theoretical Relation between Polytype Energetics and Effective Atomistic Interaction Based on Interlayer Partial Energy Model
2021 · Shinya Ogane, Riku Sato, et al. · ECS Meeting Abstracts
Machine-learning for Microstructure in the Low-carbon Steel Weld
2019 · Hidenori TERASAKI, Kazumasa TSUTSUI, et al. · JOURNAL OF THE JAPAN WELDING SOCIETY
Works count: 21
Citation count: 319
H-index: 10
I10-index: 10
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