178 citations · 204 across the 10 of their papers we have counts for
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Recent Advances in Unconventional Ferroelectrics and Multiferroics
Hongyu Yu, Junyi Ji, Wei Luo +2
Emerging ferroic materials may pave a new way to next-generation nanoelectronic and spintronic devices due to their interesting physical properties. Here, we systematically review…
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…
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…
Capturing long-range interaction with reciprocal space neural network
Hongyu Yu, Liangliang Hong, Shiyou Chen +2
Machine Learning (ML) interatomic models and potentials have been widely employed in simulations of materials. Long-range interactions often dominate in some ionic systems whose dy…
Edge-based Tensor prediction via graph neural networks
Yang Zhong, Hongyu Yu, Xingao Gong +1
Message-passing neural networks (MPNN) have shown extremely high efficiency and accuracy in predicting the physical properties of molecules and crystals, and are expected to become…