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Takuji Oda

Seoul National University - Department of Nuclear Engineering

SCHOLARLY PAPERS

5

DOWNLOADS

389

TOTAL CITATIONS

1

Scholarly Papers (5)

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1.

Accurate Description of Hydrogen Diffusivity in bcc Metals Using Machine-Learning Moment Tensor Potentials and Path-Integral Methods

Number of pages: 68 Posted: 25 Oct 2022
Hyukjoon Kwon, Motoyuki Shiga, Hajime Kimizuka and Takuji Oda
Seoul National University - Department of Nuclear Engineering, Japan Atomic Energy Agency - Center for Computational Science and e-Systems, Nagoya University - Department of Materials Design Innovation Engineering and Seoul National University - Department of Nuclear Engineering
Downloads 160 (467,092)

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Hydrogen diffusion; Molecular dynamics (MD); Density Functional Theory

2.

Sticking, Reflection, and Abstraction Behavior of Hydrogen Irradiated on (110) Tungsten Surfaces at 0.1-100 eV by Molecular Dynamics Simulations Using a Machine Learning Potential

Number of pages: 24 Posted: 29 Jan 2025
Sojeong Yang, Seungyun Kim and Takuji Oda
Seoul National University - Department of Nuclear Engineering, Seoul National University and Seoul National University - Department of Nuclear Engineering
Downloads 109 (645,052)

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Machine learning interatomic potential, hydrogen irradiation, tungsten surface, sticking coefficient, abstraction

3.

Improved Reliability and Availability of Transport Properties for All Hydrogen Isotopologues by Gaussian Process Regression Using Data From Experiments and Path-integral Simulations

International Journal of Hydrogen Energy, volume 73, 2024 [10.1016/j.ijhydene.2024.06.054]
Number of pages: 13 Posted: 22 Mar 2024
Sojeong Yang, Jae-Uk Lee, Min Ho Chang, Hyun-Goo Kang and Takuji Oda
Seoul National University - Department of Nuclear Engineering, Korea Institute of Fusion Energy, Korea Institute of Fusion Energy, Korea Institute of Fusion Energy and Seoul National University - Department of Nuclear Engineering
Downloads 45 (1,121,190)
Citation 1

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Gaussian process regression (GPR); path-integral molecular dynamics (PIMD); liquid hydrogen; hydrogen isotopologues; viscosity; diffusion coefficient

4.

Efficient Generation of Radiation Damage Structures by Machine Learning of Molecular Dynamics Simulations: Method Development and Performance Tests with Bcc-W

Number of pages: 15 Posted: 03 Feb 2025
JongHyeon Park and Takuji Oda
Seoul National University and Seoul National University - Department of Nuclear Engineering
Downloads 42 (1,157,785)

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Radiation defect, Molecular dynamics, Binary collision approximation, Primary knock-on atom, Gaussian Process Regression, Convolutional Neural Network

5.

High-throughput generation of radiation damage structures in bcc-W using machine learning statistical and image recognition models trained on molecular dynamics

Number of pages: 28 Posted: 20 Jan 2026
JongHyeon Park and Takuji Oda
Seoul National University and Seoul National University - Department of Nuclear Engineering
Downloads 33 (1,290,922)

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Radiation defect, Tungsten, Molecular dynamics, Binary collision approximation, Primary knock-on atom, Gaussian Process Regression, Convolutional Neural Network