most cited"One defect, one potential" strategy for accurate machine learning prediction of defect phonons

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cond-mat.mtrl-sci2026

Small-supercell and Small-dataset Training Strategy of Machine Learning Interatomic Potentials for Point Defects

Zhenxing Dai, Mingjue Ni, Xinpeng Li +3

Machine learning interatomic potentials (MLIPs) can treat large-scale material systems with near first-principles accuracy and have been widely used to accelerate point-defect simu…

cond-mat.mtrl-sci2025★ 2 cited

"One defect, one potential" strategy for accurate machine learning prediction of defect phonons

Junjie Zhou, Xinpeng Li, Menglin Huang +1

Atomic vibrations play a critical role in phonon-assisted electron transitions at defects in solids. However, accurate phonon calculations in defect systems are often hindered by t…