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cond-mat.mtrl-sci2025
Are diffusion models ready for materials discovery in unexplored chemical space?
Sanghyun Kim, Gihyeon Jeon, Seungwoo Hwang +4
While diffusion models are attracting increasing attention for the design of novel materials, their ability to generate low-energy structures in unexplored chemical spaces has not…
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…