3 citations · 7 across the 17 of their papers we have counts for
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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…
SevenNet-Polar for MultiTask Prediction of Energy, Forces, Stress, and Born Effective Charges: Development and Application to ZrO, LiPO, and Perovskites
Anh Khoa Augustin Lu, Shungo Arai, Yutack Park +3
Accurate prediction of the Born effective charge (BEC) tensor is crucial for modeling materials under electric fields but remains computationally expensive. To bridge this gap, we…
A Robust Agentic Framework for Expert-Level Automation of Atomistic Simulations
Yutack Park, Yeonwoo Chung, Jinmu You +3
Traditionally, atomistic simulation has been constrained by the computational scaling limits of ab initio methods and the parameterization overhead of empirical force fields. The r…
A Lightweight Universal Machine-Learning Interatomic Potential via Knowledge Distillation for Scalable Atomistic Simulations
Sangmin Oh, Jinmu You, Jaesun Kim +4
We introduce a lightweight universal machine-learning interatomic potential (uMLIP), SevenNet-Nano, based on the graph neural network architecture SevenNet and enabled by a knowled…
Atomic-Scale Mechanisms of SiO Plasma-Enhanced Chemical Vapor Deposition Revealed by Molecular Dynamics with a Machine-Learning Interatomic Potential
Jaehoon Kim, Minseok Moon, Hyunsung Cho +5
Plasma-enhanced chemical vapor deposition (PECVD) of silicon dioxide (SiO) is widely used for low-temperature fabrication of dielectric thin films, yet its atomic-scale growth…
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…