239 citations · 564 across the 15 of their papers we have counts for
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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…
Equivariant Neural Network Force Fields for Magnetic Materials
Zilong Yuan, Zhiming Xu, He Li +6
Neural network force fields have significantly advanced ab initio atomistic simulations across diverse fields. However, their application in the realm of magnetic materials is stil…
Efficient hybrid density functional calculation by deep learning
Zechen Tang, He Li, Peize Lin +7
Hybrid density functional calculation is indispensable to accurate description of electronic structure, whereas the formidable computational cost restricts its broad application. H…
Deep-Learning Density Functional Theory Hamiltonian for Efficient ab initio Electronic-Structure Calculation
He Li, Zun Wang, Nianlong Zou +5
The marriage of density functional theory (DFT) and deep learning methods has the potential to revolutionize modern computational materials science. Here we develop a deep neural n…