38 citations · 72 across the 3 of their papers we have counts for
3 papers
cond-mat.supr-con2023★ 7 cited
Energy landscape and phase competition of CsV3Sb5-, CsV6Sb6-, and TbMn6Sn6-type Kagome materials
Guanghui Cai, Yutao Jiang, Hui Zhou +5
Finding viable Kagome lattices is vital for materializing novel phenomena in quantum materials. In this work, we performed element substitutions on CsV3Sb5 with space group P6/mmm,…
physics.comp-ph2023★ 27 cited
Predicting structure-dependent Hubbard U parameters for assessing hybrid functional-level exchange via machine learning
Zhendong Cao, Guanghui Cai, Fankai Xie +7
DFT+U is a widely used treatment in the density functional theory (DFT) to deal with correlated materials that contain open-shell elements, whereby the quantitative and sometimes e…
cond-mat.mtrl-sci2021★ 38 cited
A universal model for the formation energy prediction of inorganic compounds
Yingzong Liang, Mingwei Chen, Yanan Wang +5
Harnessing the recent advance in data science and materials science, it is feasible today to build predictive models for materials properties. In this study, we employ the data of…