Shigenobu Ogata

Kyoto University — Japan

Materials Science · Physical Sciences

48h-index9.9kcitations407works6.82yr avg
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Research Topics

Microstructure and mechanical properties(113), Metal and Thin Film Mechanics(59), Metallic Glasses and Amorphous Alloys(37), Magnesium Alloys: Properties and Applications(34), Aluminum Alloys Composites Properties(34)

Publications407 total

Dislocation-ledge coupling drives non-conservative migration of semicoherent precipitate interfaces
ArXiv.org·2026Open Access
Negative Strain-Rate Sensitivity in Metallic Glasses Driven by Rejuvenation-Relaxation Competition: Kinetic Monte Carlo Simulations and a Minimal Effective Model
ArXiv.org·2026Open Access
Negative Strain-Rate Sensitivity in Metallic Glasses Driven by Rejuvenation-Relaxation Competition: Kinetic Monte Carlo Simulations and a Minimal Effective Model
arXiv (Cornell University)·2026Open Access
Dislocation-ledge coupling drives non-conservative migration of semicoherent precipitate interfaces
arXiv (Cornell University)·2026Open Access
Unravelling the interplay between hydrogen and grain boundary of α-Fe under different concentration and strain rate via neural network interatomic potential
Computational Materials Science·2026
Quantitative composition‑annealing temperature map of stacking‑fault energy in CoCrNi medium‑entropy alloys unveiled by first‑principles neural‑network potentials
Scripta Materialia·2026
Formation of a one-dimensional dislocation loop array in wurtzite zinc oxide at ambient temperature
Journal of Material Science and Technology·2026Open Access
Negative Strain–Rate Sensitivity in Metallic Glasses Driven by Rejuvenation–Relaxation Competition: Kinetic Monte Carlo Simulations and a Minimal Effective Model
SSRN Electronic Journal·2026Open Access
Formation of Small Prismatic Dislocation Loops via Double Cross-slip of Screw Dislocations in Iron: Dynamic Loop-type Identification Using <i>in situ</i> Transmission Electron Microscopy
Tetsu-to-Hagane·2026Open Access
An Overview of Machine Learning Potentials for Structural Materials
Journal of the Japan Institute of Metals and Materials·2025Open Access
Dual Role of Nb in Defect-Mediated Strength and Ductility of γ-TiAl Alloys
arXiv (Cornell University)·2025Open Access
An empirical formulation of accelerated molecular dynamics for simulating and predicting microstructure evolution in materials
Computer Physics Communications·2025
Achieving Empirical Potential Efficiency with DFT Accuracy: A Neuroevolution Potential for the $α$-Fe--C--H System
arXiv (Cornell University)·2025Open Access
A Neural Network Interatomic Potential for the Ternary α-Fe-C-H System: Toward Million-Atom Simulations of Hydrogen Embrittlement in Steel
JOM·2025· 1 citedOpen Access
Statistical structural mechanism for shear localization in amorphous materials
Acta Materialia·2025· 2 cited
Kinked basal dislocation loops for anomalous annealing hardening in irradiated zirconium
Acta Materialia·2025
Insights into a new overclustering technique using machine learning for a self-selecting bin-restricted colour sorting setup for light red meranti (Rubroshorea spp.)
European Journal of Wood and Wood Products·2025Open Access
‘Tracheid effect’ light scattering response of common commercial species of Malaysia using red laser (650 nm) for grain angle detection, and machine learning based performance prediction
Wood Science and Technology·2025· 1 citedOpen Access
Extraordinary hardening-by-annealing in bulk ultrafine grained magnesium with ultra-low yttrium addition
Acta Materialia·2025· 5 cited
Unveiling kink band formation mechanism in MAX phases
Communications Materials·2025· 2 citedOpen Access
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Frequent Co-authors

Ju Li(15), Jun-Ping Du(10), Hajime Kimizuka(10), Yoji Shibutani(7), Masato Wakeda(6), Shuhei Shinzato(6), Naoto Hirosaki(5), Akio Ishii(5), Sidney Yip(4), Cenk Kocer(4), W. T. Geng(4), Yun-Jiang Wang(4), Futoshi Shimizu(3), Ruixiao Zheng(3), Si Gao(3), Nobuhiro Tsuji(3), Liang Wan(3), Nobuyuki Ishikawa(3), E. Ma(3), Wei‐Zhong Han(3)