44 citations · 44 across the 3 of their papers we have counts for
3 papers
physics.comp-ph2024
Deep learning density functional theory Hamiltonian in real space
Zilong Yuan, Zechen Tang, Honggeng Tao +11
Deep learning electronic structures from ab initio calculations holds great potential to revolutionize computational materials studies. While existing methods proved success in dee…
physics.comp-ph2024★ 44 cited
Universal materials model of deep-learning density functional theory Hamiltonian
Yuxiang Wang, Yang Li, Zechen Tang +14
Realizing large materials models has emerged as a critical endeavor for materials research in the new era of artificial intelligence, but how to achieve this fantastic and challeng…
cond-mat.mtrl-sci2024
Deep-Learning Database of Density Functional Theory Hamiltonians for Twisted Materials
Ting Bao, Runzhang Xu, He Li +5
Moiré-twisted materials have garnered significant research interest due to their distinctive properties and intriguing physics. However, conducting first-principles studies on such…