most citedHighly efficient and transferable interatomic potentials for α-iron and α-iron/hydrogen binary systems using deep neural networks

2 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

cond-mat.mtrl-sci2026

Dual Role of Mobile Interstitials in Defect Kinetics: From Retardation to Acceleration

Shihao Zhang, Shihao Zhu, Junping Du +3

Mobile interstitial atoms redistribute while defects migrate, complicating prediction of defect kinetics and leading to contradictory reports of acceleration and retardation. We fo…

physics.comp-ph2026

Machine-learned atomistic simulations reveal the basis of hydrogen-induced crack-plane transition in alpha-Fe

Jiaqin Xu, Zhiqiang Zhao, Kazuma Ito +4

Hydrogen-related fracture in body-centered cubic Fe and ferritic steels often appears as transgranular quasi-cleavage rather than purely intergranular failure, especially at low to…

cond-mat.mtrl-sci2023★ 2 cited

Highly efficient and transferable interatomic potentials for α-iron and α-iron/hydrogen binary systems using deep neural networks

Shihao Zhang, Fanshun Meng, Rong Fu +1

Artificial neural network potentials (NNPs) have emerged as effective tools for understanding atomic interactions at the atomic scale in various phenomena. Recently, we developed h…