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20242026
most citedScalable Parallel Algorithm for Graph Neural Network Interatomic Potentials in Molecular Dynamics Simulations

222 citations · 226 across the 6 of their papers we have counts for

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cond-mat.mtrl-sci2025★ 3 cited

Optimizing Cross-Domain Transfer for Universal Machine Learning Interatomic Potentials

Jaesun Kim, Jinmu You, Yutack Park +11

Accurate yet transferable machine-learning interatomic potentials (MLIPs) are essential for accelerating materials and chemical discovery. However, most universal MLIPs overfit to…

cond-mat.mtrl-sci2025

Unveiling defect motifs in amorphous GeSe using machine learning interatomic potentials

Minseok Moon, Seungwoo Hwang, Jaesun Kim +3

Ovonic threshold switching (OTS) selectors play a critical role in non-volatile memory devices because of their nonlinear electrical behavior and polarity-dependent threshold volta…