764 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Science and Technology of ChinaCN36 papers
- Xiamen UniversityCN32 papers
- Hefei National Center for Physical Sciences at NanoscaleCN16 papers
- Chinese Academy of SciencesCN15 papers
- Fudan UniversityCN14 papers
- University of Chinese Academy of SciencesCN9 papers
- Collaborative Innovation Center of Advanced MicrostructuresCN8 papers
- Peking UniversityCN8 papers
- National Synchrotron Radiation LaboratoryCN6 papers
- Tan Kah Kee Innovation LaboratoryCN6 papers
- Dalian Institute of Chemical PhysicsCN4 papers
- Henry Royce InstituteGB4 papers
84 papers
Observation of Magnetic-Anisotropy Crossover and High-Temperature Skyrmions in the Dirac Magnet Fe3Ge with a Distorted Kagome Lattice
Yalei Huang, Xiaowei Lv, Bin Li +13
Topological materials that simultaneously host robust high-temperature skyrmions and nontrivial electronic band structures have attracted tremendous interest owing to their distinc…
Voltage-controlled topological spin textures in the monolayer limit
Yangliu Wu, Bo Peng, Zhaozhuo Zeng +10
The physics of phase transitions in low-dimensional systems has long been a subject of significant research interest. Long-range magnetic order in the strict two-dimensional limit,…
TXL Fusion: A Hybrid Machine Learning Framework Integrating Chemical Heuristics and Large Language Models for Topological Materials Discovery
Arif Ullah, Rajibul Islam, Yangming Huang +4
Topological materials, including topological insulators (TIs) and topological semimetals (TSMs), offer promising platforms for quantum, spintronic, and low-dissipation electronic t…
Instanton Theory for Nonadiabatic Tunneling through Near-Barrier Crossings
Ziyan Ye, Eric R. Heller, Dong H. Zhang +2
Many reactions in chemistry and biology involve multiple electronic states, rendering them nonadiabatic in nature. These reactions can be formally described using Fermi's golden ru…
Machine Learning Accelerated Computational Surface-Specific Vibrational Spectroscopy Reveals Oxidation Level of Graphene in Contact with Water
Xianglong Du, Jun Cheng, Fujie Tang
Precise characterization of the graphene/water interface has been hindered by experimental inconsistencies and limited molecular-level access to interfacial structures. In this wor…
Redox chemistry meets semiconductor defect physics
Jian Gu, Jun Huang, Jun Cheng
Understanding how the electronic structure of electrodes influences electrocatalytic reactions has been a longstanding topic in the electrochemistry community, with predominant att…
DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials
Jinzhe Zeng, Duo Zhang, Anyang Peng +44
In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for m…
Reconstructing Pristine Molecular Orbitals from Scanning Tunneling Microscopy Images via Artificial Intelligence Approaches
Yu Zhu, Renjie Xue, Hao Ren +7
Molecular orbital (MO) is one of the most fundamental concepts for molecules, relating to all branches of chemistry, while scanning tunneling microscopy (STM) has been widely recog…
Decoding the Competing Effects of Dynamic Solvation Structures on Nuclear Magnetic Resonance Chemical Shifts of Battery Electrolytes via Machine Learning
Qi You, Yan Sun, Feng Wang +2
Understanding the solvation structure of electrolytes is critical for optimizing the electrochemical performance of rechargeable batteries, as it directly influences properties suc…
Graphendofullerene: a novel molecular two-dimensional ferromagnet
Diego López-Alcalá, Ziqi Hu, José J. Baldoví
Carbon chemistry has attracted a lot of attention by chemists, physicists and material scientists in the last decades. The recent discovery of graphullerene provides a promising pl…
Auto-resolving the atomic structure at van der Waals interfaces using a generative model
Wenqiang Huang, Yuchen Jin, Zhemin Li +12
The high-resolution visualization of atomic structures is significant for understanding the relationship between the microscopic configurations and macroscopic properties of materi…
Revealing the molecular structures of a-Al2O3(0001)-water interface by machine learning based computational vibrational spectroscopy
Xianglong Du, Weizhi Shao, Chenglong Bao +3
Solid-water interfaces are crucial to many physical and chemical processes and are extensively studied using surface-specific sum-frequency generation (SFG) spectroscopy. To establ…
Evidence for Multiferroicity in Single-Layer CuCrSe
Zhenyu Sun, Yueqi Su, Aomiao Zhi +13
Multiferroic materials, which simultaneously exhibit ferroelectricity and magnetism, have attracted substantial attention due to their fascinating physical properties and potential…
Electrically tunable layer-hybridized trions in doped WSe bilayers
Raul Perea-Causin, Samuel Brem, Fabian Buchner +6
Doped van der Waals heterostructures host layer-hybridized trions, i.e. charged excitons with layer-delocalized constituents holding promise for highly controllable optoelectronics…
Unveiling the origin of unconventional moire ferroelectricity
Ruirui Niu, Zhuoxian Li, Xiangyan Han +13
Interfacial ferroelectricity emerges in heterostructures consisting of nonpolar van der Waals (vdW) layers, greatly expanding the scope of two dimensional ferroelectrics. In partic…
Improving XYG3-type Doubly Hybrid Approximation using Self-Interaction Corrected SCAN Density and Orbitals via the PZ-SIC Framework: the xDH@SCAN(SIC) Approach
Sheng Bi, Shirong Wang, Igor Ying Zhang +1
XYG3-type doubly hybrid approximations (xDH) have gained a widespread recognition for their accuracy in describing a diverse range of chemical and physical interactions. However, a…
DPA-2: a large atomic model as a multi-task learner
Duo Zhang, Xinzijian Liu, Xiangyu Zhang +40
The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demo…
MLatom 3: Platform for machine learning-enhanced computational chemistry simulations and workflows
Pavlo O. Dral, Fuchun Ge, Yi-Fan Hou +15
Machine learning (ML) is increasingly becoming a common tool in computational chemistry. At the same time, the rapid development of ML methods requires a flexible software framewor…
Quasicrystalline Nanocrystal Superlattice with Partial Matching Rules
Xingchen Ye, Jun Chen, M. Eric Irrgang +4
Expanding the library of self-assembled superstructures provides insight into the behavior of atomic crystals and supports the development of materials with mesoscale order. Here w…
DeePMD-kit v2: A software package for Deep Potential models
Jinzhe Zeng, Duo Zhang, Denghui Lu +44
DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. T…
pH-dependent water permeability switching and its memory in 1T' MoS membranes
C. Hu, A. Achari, P. Rowe +13
Intelligent transport of molecular species across different barriers is critical for various biological functions and is achieved through the unique properties of biological membra…
Mixing of surface and bulk electronic states at a graphite-hexagonal boron nitride interface
Ciaran Mullan, Sergey Slizovskiy, Jun Yin +12
Van der Waals assembly enables exquisite design of electronic states in two-dimensional (2D) materials, often by superimposing a long-wavelength periodic potential on a crystal lat…
Improving estimation of entropy production rate for run-and-tumble particle systems by high-order thermodynamic uncertainty relation
Ruicheng Bao, Zhonghuai Hou
Entropy production plays an important role in the regulation and stability of active matter systems, and its rate quantifies the nonequilibrium nature of these systems. However, en…
Designing Autonomous Maxwell Demon via Stochastic Resetting
Ruicheng Bao, Zhiyu Cao, Jiming Zheng +1
Autonomous Maxwell demon is a new type of information engine proposed by Mandal and Jarzynski, which can produce work by exploiting an information tape. Here, we show that a stocha…