85 citations · 181 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
Complex Spin Hamiltonian Represented by Artificial Neural Network
Hongyu Yu, Changsong Xu, Feng Lou +4
The effective spin Hamiltonian method is widely adopted to simulate and understand the behavior of magnetism. However, the magnetic interactions of some systems, such as itinerant…