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cond-mat.mtrl-sci2026
Physics-informed Machine Learning Prediction of Hubbard Interaction Parameters
Jiyeon Kim, Indukuru Ramesh Reddy, Bongjae Kim +1
Accurate determination of Hubbard interaction parameters is essential for beyond-DFT approaches such as DFT+, DFT+DMFT, and DFT++ in correlated materials. In practice, how…
cond-mat.mtrl-sci2024★ 11 cited
Machine Learning Prediction Models for Solid Electrolytes based on Lattice Dynamics Properties
Jiyeon Kim, Donggeon Lee, Dongwoo Lee +3
Recently, machine-learning approaches have accelerated computational materials design and the search for advanced solid electrolytes. However, the predictors are currently limited…