most citedAn efficient forgetting-aware fine-tuning framework for pretrained universal machine-learning interatomic potentials

1 citations · 1 across the 3 of their papers we have counts for

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3 papers

cond-mat.mtrl-sci2025

Discovery of oxide Li-conducting electrolytes in uncharted chemical space via topology-constrained crystal structure prediction

Seungwoo Hwang, Jiho Lee, Seungwu Han +2

Oxide Li-conducting solid-state electrolytes (SSEs) offer excellent chemical and thermal stability but typically exhibit lower ionic conductivity than sulfides and chlorides. This…

cond-mat.mtrl-sci2025★ 1 cited

An efficient forgetting-aware fine-tuning framework for pretrained universal machine-learning interatomic potentials

Jisu Kim, Jiho Lee, Sangmin Oh +5

Pretrained universal machine-learning interatomic potentials (MLIPs) have revolutionized computational materials science by enabling rapid atomistic simulations as efficient altern…

cond-mat.mtrl-sci2023

Disorder-dependent Li diffusion in investigated by machine learning potential

Jiho Lee, Suyeon Ju, Seungwoo Hwang +4

Solid-state electrolytes with argyrodite structures, such as , have attracted considerable attention due to their superior safety compared to liquid electrolyt…