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cond-mat.mtrl-sci2026
PASS: Perturbation augmented space group structure sampling for transferable Fe-O machine learning interatomic potential
Zixiong Wei, Fei Shuang, Poulumi Dey
Accurate atomistic modelling of iron (Fe) oxidation requires a reliable interatomic potential, which necessitates an extensive and representative first-principles dataset for train…
cond-mat.mtrl-sci2026
Finite Temperature Stacking Fault Stability in Random and Locally Ordered CoCrNi beyond the Harmonic Approximation
Reza Namakian, Fei Shuang, Thomas D Swinburne +3
Previous density functional theory (DFT) calculations for random solid solution (RSS) CoCrNi predict negative intrinsic stacking-fault energy (ISFE) at 0 K, contrary to experimenta…
cond-mat.mtrl-sci2026★ 1 cited
Benchmarking Chemically Scalable Machine-Learning Interatomic Potentials for Large-Scale Simulations of Multicomponent Alloys
Fei Shuang, Penghua Ying, Kai Liu +5
Machine learning interatomic potentials (MLIPs) with broad chemical flexibility are essential for atomistic simulations of compositionally complex alloys, but their deployment in l…