26 citations
- Westlake UniversityCN2 papers
- Beijing University of Posts and TelecommunicationsCN1 paper
- Guizhou University of Finance and EconomicsCN1 paper
- Kaili UniversityCN1 paper
- Nanjing UniversityCN1 paper
- Shaanxi Normal UniversityCN1 paper
- University of Arkansas at FayettevilleUS1 paper
- Xi'an Jiaotong UniversityCN1 paper
- Xi’an UniversityCN1 paper
- Xi’an University of Posts and TelecommunicationsCN1 paper
- Xi'an University of TechnologyCN1 paper
- Xidian UniversityCN1 paper
7 papers
Sliding Ferroelectricity Induced and Switched Altermagnetism in GaSe-VPSe3-GaSe Sandwiched Heterostructure with Strong Magnetoelectric Effect
Pengqiang Dong, Hanbo Sun, Chao Wu +1
Magnetoelectric coupling is vital for exploring fundamental science and driving the development of high-density memory and energy-efficient spintronic devices. Altermagnets, which…
Global well-posedness of the Navier--Stokes equations and the Keller--Segel system in variable Fourier--Besov spaces
Gastón Vergara-Hermosilla, Jihong Zhao
In this paper, we study the Cauchy problem of the classical incompressible Navier--Stokes equations and the parabolic-elliptic Keller--Segel system in the framework of the Fourier-…
Global well-posedness of the fractional dissipative system in the framework of variable Fourier--Besov spaces
Gastón Vergara-Hermosilla, Jihong Zhao
In this paper, we are concerned with the well-posed issues of the fractional dissipative system in the framework of the Fourier--Besov spaces with variable regularity and integrabi…
Electric-field-induced formation and annihilation of skyrmions in two-dimensional magnet
Jingman Pang, Hongjia Wang, Yufei Tang +2
Electric manipulation of skyrmions in 2D magnetic materials has garnered significant attention due to the potential in energy-efficient spintronic devices. In this work, using firs…
Inferring synchronizability of networked heterogenous oscillators with machine learning
Liang Wang, Huawei Fan, Yafeng Wang +4
In the study of network synchronization, an outstanding question of both theoretical and practical significance is how to allocate a given set of heterogenous oscillators on a comp…
Accelerating inverse crystal structure prediction by machine learning: a case study of carbon allotropes
Wen Tong, Qun Wei, Haiyan Yan +2
Based on structure prediction method, the machine learning method is used instead of the density function theory (DFT) method to predict the material properties, thereby accelerati…