44 citations · 44 across the 6 of their papers we have counts for
4 papers · 1 filter
AI-accelerated metallized -bonding screening for superconductor discovery
Zechen Tang, Wen-Han Dong, Baochun Wu +11
The computational discovery of phonon-mediated superconductors is hindered by the prohibitive cost of density functional perturbation theory (DFPT). Here, guided by the metallized…
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…
Improving density matrix electronic structure method by deep learning
Zechen Tang, Nianlong Zou, He Li +10
The combination of deep learning and ab initio materials calculations is emerging as a trending frontier of materials science research, with deep-learning density functional theory…
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…