52 citations · 135 across the 21 of their papers we have counts for
9 papers · 1 filter
Machine learning Hamiltonian enables scalable and accurate defect calculations: The case of oxygen vacancies in amorphous SiO
Zhenxing Dai, Zhong Yang, Mingjue Ni +4
Point defects critically influence the properties of materials and devices, yet density functional theory (DFT) remains computationally demanding for defect supercell calculations.…
Efficient E(3)-equivariant framework for universal charge density prediction
Xiwen Li, Zaizhou Xin, Hongyu Yu +3
Electronic structure is ubiquitously obtained via density functional theory (DFT), where the charge density plays a central role. This work presents EdenGNN (Equivariant Density Gr…
Strain-induced gyrotropic effects in ferroelectric BaTiS3
Wei Luo, Asier Zabalo, Guodong Ren +5
Gyrotropic effects, including natural optical activity (NOA) and the nonlinear anomalous Hall effect (NAHE), are crucial for advancing optical and transport devices. We explore the…
A Universal Spin-Orbit-Coupled Hamiltonian Model for Accelerated Quantum Material Discovery
Yang Zhong, Rui Wang, Xingao Gong +1
The accurate modeling of spin-orbit coupling (SOC) effects in diverse complex systems remains a significant challenge due to the high computational demands of density functional th…
Linear Scaling Calculation of Atomic Forces and Energies with Machine Learning Local Density Matrix
Zaizhou Xin, Yang Zhong, Xingao Gong +1
Accurately calculating energies and atomic forces with linear-scaling methods is a crucial approach to accelerating and improving molecular dynamics simulations. In this paper, we…
ABACUS: An Electronic Structure Analysis Package for the AI Era
Weiqing Zhou, Daye Zheng, Qianrui Liu +55
ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It…
Identifying Direct Bandgap Silicon Structures with High-throughput Search and Machine Learning Methods
Rui Wang, Hongyu Yu, Yang Zhong +1
Utilizations of silicon-based luminescent devices are restricted by the indirect-gap nature of diamond silicon. In this study, the high-throughput method is employed to expedite di…
Accelerating the electronic-structure calculation of magnetic systems by equivariant neural networks
Yang Zhong, Binhua Zhang, Hongyu Yu +2
Complex spin-spin interactions in magnets can often lead to magnetic superlattices with complex local magnetic arrangements, and many of the magnetic superlattices have been found…
General time-reversal equivariant neural network potential for magnetic materials
Hongyu Yu, Boyu Liu, Yang Zhong +5
This study introduces time-reversal E(3)-equivariant neural network and SpinGNN++ framework for constructing a comprehensive interatomic potential for magnetic systems, encompassin…