42 citations · 64 across the 16 of their papers we have counts for
16 papers
Latent Genetic Algorithm for Crystal Structure Prediction
Kaixin Zheng, Wanjian Yin, Hongyu Yu +1
Predicting crystal structures requires navigating rugged energy landscapes in which favorable local motifs must be inherited across candidates with incompatible cells, densities, a…
A Fully Ab-Initio Spin-Lattice Dynamics Framework for Magnetic Materials
Xianxi Zhang, Hongyu Yu, Liangliang Hong +1
Coupled spin-lattice dynamics (SLD) underlie a wide range of magnetic phenomena, yet a unified first-principles framework that propagates both degrees of freedom without empirical…
Tangent-Plane Evidential Uncertainty in Active Learning for Magnetic Interatomic Potentials
Yang Cheng, Hongyu Yu, Hongjun Xiang
Magnetic interatomic potentials need to account for coupled lattice and spin degrees of freedom, yet constructing reliable training sets remains costly because noncollinear first-p…
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…
Defect-Charge-Driven 90° Switching in HfO2
Muting Xie, Hongyu Yu, Zhihao Dai +3
Hafnium dioxide (HfO2) is a CMOS-compatible ferroelectric showing both 180° and 90° switching, yet the microscopic nature of the 90° pathway remains unresolved. We show that the 90…
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…
Moiré-Induced Magnetoelectricity in Twisted Bilayer NiI2
Haiyan Zhu, Hongyu Yu, Weiqin Zhu +3
Twisted magnetic van der Waals (vdW) materials offer a promising route for multiferroic engineering, yet modeling large-scale moiré superlattices remains challenging. Leveraging a…
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…
Efficient construction of effective Hamiltonians with a hybrid machine learning method
Yang Cheng, Binhua Zhang, Xueyang Li +3
The effective Hamiltonian method is a powerful tool for simulating large-scale systems across a wide range of temperatures. However, previous methods for constructing effective Ham…
Efficient prediction of potential energy surface and physical properties with Kolmogorov-Arnold Networks
Rui Wang, Hongyu Yu, Yang Zhong +1
The application of machine learning methodologies for predicting properties within materials science has garnered significant attention. Among recent advancements, Kolmogorov-Arnol…
Role of Domain Walls on Imprint and Fatigue in HfO2-Based Ferroelectrics
Muting Xie, Hongyu Yu, Binhua Zhang +2
HfO2-based ferroelectric materials are promising for the next generation of memory devices, attracting significant attention. However, their potential applications are significantl…
Deterministic and Efficient Switching of Sliding Ferroelectrics
Shihan Deng, Hongyu Yu, Junyi Ji +2
Recent studies highlight the scientific importance and broad application prospects of two-dimensional (2D) sliding ferroelectrics, which prevalently exhibit vertical polarization w…
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…
Switchable Ferroelectricity in Subnano Silicon Thin Films
Hongyu Yu, Shihan deng, Muting Xie +5
Recent advancements underscore the critical need to develop ferroelectric materials compatible with silicon. We systematically explore possible ferroelectric silicon quantum films…
Universal Machine Learning Kohn-Sham Hamiltonian for Materials
Yang Zhong, Hongyu Yu, Jihui Yang +3
While density functional theory (DFT) serves as a prevalent computational approach in electronic structure calculations, its computational demands and scalability limitations persi…
Transferable Machine Learning Approach for Predicting Electronic Structures of Charged Defects
Yuxing Ma, Yang Zhong, Yu Hongyu +2
The study of the electronic properties of charged defects is crucial for our understanding of various electrical properties of materials. However, the high computational cost of de…