3 papers
cond-mat.mtrl-sci2026
Agentic programs: an emerging form of scientific software in computational materials science
Yunsung Lim, Haekwan Jeon, Jaesun Kim +2
Computational materials science has traditionally delegated algorithmic tasks to computers while leaving scientific judgments to humans. We argue that recent LLM-based agent harnes…
cond-mat.mtrl-sci2026
Precipitate phase selection and grain boundary morphology in Cu-Ni-Si-Mn alloys: A machine-learning interatomic potential study
Aadil Fayaz Wani, Il-Seok Jeong, Haekwan Jeon +6
Alloys inevitably contain interphase boundaries, whose energetics govern nucleation processes and precipitate morphology. In Cu-Ni-Si alloys, Mn addition markedly changes grain bou…
cond-mat.mtrl-sci2025
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…