11 citations · 23 across the 8 of their papers we have counts for
8 papers
NEPMaker: Active learning of neuroevolution machine learning potential for large cells
Junjie Wang, Shuning Pan, Haoting Zhang +4
Machine learning potentials (MLPs) achieve near first-principles accuracy but often fail for atomic environments outside the training distribution. Active learning can mitigate thi…
GPUTB-2:An efficient E(3) network method for learning high-precision orthogonal Hamiltonian
Yunlong Wang, Zhixin Liang, Chi Ding +5
Although equivariant neural networks have become a cornerstone for learning electronic Hamiltonians, the intrinsic non-orthogonality of linear combinations of atomic orbitals (LCAO…
GPUTB: Efficient Machine Learning Tight-Binding Method for Large-Scale Electronic Properties Calculations
Yunlong Wang, Zhixin Liang, Chi Ding +5
The high computational cost of ab-initio methods limits their application in predicting electronic properties at the device scale. Therefore, an efficient method is needed to map t…
Enhancement of superconducting transition temperature and exotic stoichiometries in Lu-S system under high pressure
Juefei Wu, Bangshuai Zhu, Chi Ding +5
Binary metal sulfides are potential material family for exploring high Tc superconductors under high pressure. In this work, we study the crystal structures, electronic structures…
Superconducting Ternary Hydridies in Ca-U-H under High Pressure
Juefei Wu, Bangshuai Zhu, Chi Ding +4
The research on hydrogen-rich ternary compounds attract tremendous attention for it paves new route to room-temperature superconductivity at lower pressures. Here, we study the cry…
Excitonic Insulator to Superconductor Phase Transition in Ultra-Compressed Helium
Cong Liu, Ion Errea, Chris Pickard +8
Helium, the second most abundant element in the universe, exhibits an extremely large electronic band gap of about eV at low pressures ( GPa). While the metallization…
Prediction of surface reconstructions using MAGUS
Yu Han, Junjie Wang, Chi Ding +4
In this paper, we present a new module to predict the potential surface reconstruction configurations of given surface structures in the framework of our machine learning and graph…
Novel superhard structures of high-pressure C-N compounds
Yunlong Wang, Chi Ding, Jianan Yuan +1
Through machine learning force field accelerated structure search combined with first-principles calculations, we have studied the structures of new C-N compounds with different st…