activity
19982023
most citedOctagraphene as a Versatile Carbon Atomic Sheet for Novel Nanotubes, Unconventional Fullerenes and Hydrogen Storage

116 citations · 1.2k across the 42 of their papers we have counts for

collaborators
Showing 2020Show all

15 papers · 1 filter

cond-mat.mes-hall2020★ 14 cited

Hexagonal Warping Induced Nonlinear Planar Nernst Effect in Nonmagnetic Topological Insulators

Xiao-Qin Yu, Zhen-Gang Zhu, Gang Su

We propose theoretically a new effect, i.e. nonlinear planar Nernst effect (NPNE), in nonmagnetic topological insulator (TI) Bi2Te3 in the presence of an in-plane magnetic field. W…

cond-mat.supr-con2020★ 45 cited

Two-dimensional topological superconductivity candidate in van der Waals layered material

Jing-Yang You, Bo Gu, Gang Su +1

Two-dimensional (2D) topological superconductors are highly desired because they not only offer opportunities for exploring novel exotic quantum physics, but also possesses potenti…

cond-mat.mtrl-sci2020

P-orbital magnetic topological states on square lattice

Jing-Yang You, Bo Gu, Gang Su

Honeycomb or triangular lattices were extensively studied and thought to be proper platforms for realizing quantum anomalous Hall effect (QAHE), where magnetism is usually caused b…

cond-mat.mtrl-sci2020

Kagome quantum anomalous Hall effect with high Chern number and large band gap

Zhen Zhang, Jing-Yang You, Xing-Yu Ma +2

Due to the potential applications in the low-power-consumption spintronic devices, the quantum anomalous Hall effect (QAHE) has attracted tremendous attention in past decades. Howe…

cond-mat.mtrl-sci2020

Microscopic mechanism of high-temperature ferromagnetism in Fe, Mn, and Cr-doped InSb, InAs, and GaSb magnetic semiconductors

Jing-Yang You, Bo Gu, Sadamichi Maekawa +1

In recent experiments, high Curie temperatures Tc above room temperature were reported in ferromagnetic semiconductors Fe-doped GaSb and InSb, while low Tc between 20 K to 90 K wer…

cond-mat.mtrl-sci2020

Voting Data-Driven Regression Learning for Discovery of Functional Materials and Applications to Two-Dimensional Ferroelectric Materials

Xing-Yu Ma, Hou-Yi Lyu, Xue-Juan Dong +4

Regression machine learning is widely applied to predict various materials. However, insufficient materials data usually leads to a poor performance. Here, we develop a new voting…