44 citations · 45 across the 5 of their papers we have counts for
6 papers
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…
Exciton-roton mode in moiré fractional Chern insulators
Xiaoyang Shen, Zijian Zhou, Ruiping Guo +4
Moiré fractional Chern insulators (FCIs) are a novel class of quantum matter that realizes fractional quantum Hall (FQH) physics in zero magnetic field and provides a platform for…
Magnetorotons in Moiré Fractional Chern Insulators
Xiaoyang Shen, Chonghao Wang, Xiaodong Hu +5
The discovery of fractional Chern insulators (FCIs) unlocks exciting opportunities to explore emergent physical excitations arising from topological and geometric effects in novel…
Deep Band Crossings Enhanced Nonlinear Optical Effects
Nianlong Zou, He Li, Meng Ye +8
Nonlinear optical (NLO) effects in materials with band crossings have attracted significant research interests due to the divergent band geometric quantities around these crossings…
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…
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…