596 citations · 598 across the 4 of their papers we have counts for
4 papers
A Spin-dependent Machine Learning Framework for Transition Metal Oxide Battery Cathode Materials
Taiping Hu, Teng Yang, Jianchuan Liu +9
Owing to the trade-off between the accuracy and efficiency, machine-learning-potentials (MLPs) have been widely applied in the battery materials science, enabling atomic-level dyna…
DeePKS Model for Halide Perovskites with the Accuracy of Hybrid Functional
Qi Ou, Ping Tuo, Wenfei Li +3
Accurate prediction for the electronic structure properties of halide perovskites plays a significant role in the design of highly efficient and stable solar cells. While density f…
DeePMD-kit v2: A software package for Deep Potential models
Jinzhe Zeng, Duo Zhang, Denghui Lu +44
DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. T…
Hybrid nano-domain structures of organic-inorganic perovskites from molecule-cage coupling effects
Ping Tuo, Lei Li, Xiaoxu Wang +4
In hybrid perovskites, the organic molecules and inorganic frameworks exhibit distinct static and dynamic characteristics. Their coupling will lead to unprecedented phenomena, whic…