48 citations · 300 across the 20 of their papers we have counts for
22 papers
The Roadmap of Inorganic Computational Materials Databases: Capabilities, Credibility, Coverage, and the Open Frontier
Miao Liu, Jianghao Jin, Tenglong Lu +4
Computational materials databases have become central infrastructure for data-driven discovery of inorganic materials, yet their growth remains strikingly uneven across property fa…
Vestigial chirality from fluctuating loop currents on the kagome lattice
Yin Shi, Xuande Bu, Sheng Meng
Multicomponent order can melt in stages, leaving a composite order after its primary constituents become short ranged. We study this possibility for commensurate three- loop-cur…
Accelerating dynamic simulations of photoexcited materials and their evolution by electron-informed machine learning
Yunzhe Jia, Fankai Xie, Yunfei Bai +3
Nonadiabatic coupled electron-nuclear dynamics upon electronic excitation underpin the microscopic mechanism and rational modulation of diverse photoinduced functional phenomena in…
Aligning Heterogeneous DFT Datasets: A Graph Neural Network Approach to Cross-Functional Formation Energies
Yidong Huang, Tenglong Lu, Hanwen Kang +3
Heterogeneous density functional theory (DFT) calculations, particularly plane-wave implementations, introduce systematic formation energy errors ranging from tens to hundreds of m…
Graph Neural Network Force Fields (GPTFF-mol) for Organic Molecules from Optimization Trajectories (OpenGEM26)
Yifan Huang, Fankai Xie, Jiangnan Zheng +3
Density functional theory (DFT) serves as a reliable tool for atomistic molecular simulations, while machine learning potentials have become powerful complements to balance accurac…
Collective phase modes in twisted -wave superconducting bilayers
Yin Shi, Mengxian Zhao, Fei Yang +2
Twisted cuprate bilayers have been predicted to host high-temperature chiral superconductivity, originating from higher-order Josephson coupling processes. In such two-dime…
Quench of chiral superconductivity by quantum phase fluctuations in twisted cuprate bilayers
Yin Shi, Mengxian Zhao, Fei Yang +2
Following theoretical proposals of chiral superconductivity in twisted cuprate bilayers, experimental signatures of time-reversal symmetry breaking (TRSB) remain highly con…
Are Machine Learning Interatomic Potentials Truly Practical? A Benchmark of 23 Mainstream Models
Hanwen Kang, Tenglong Lu, Sheng Meng +1
Most MLIP benchmarks reward static accuracy while ignoring inference efficiency and hardware scalability -- driving model bloat with unclear real-world value. We benchmark 23 mains…
Tracking unconventional superconductivity in the presence of strongly correlated Fermi arcs
Xianliang Zhou, Fei Yang, Miao Liu +2
One of the primary reasons that superconductivity in underdoped cuprates is enigmatic is that it emerges from an incoherent Fermi-arc state, so the applicability of the Bardeen-Coo…
FastTrack: a fast method to evaluate mass transport in solid leveraging universal machine learning interatomic potential
Hanwen Kang, Tenglong Lu, Zhanbin Qi +3
We introduce a rapid, accurate framework for computing atomic migration barriers in crystals by combining universal machine learning force fields (MLFFs) with 3D potential energy s…
GPTFF: A high-accuracy out-of-the-box universal AI force field for arbitrary inorganic materials
Fankai Xie, Tenglong Lu, Sheng Meng +1
This study introduces a novel AI force field, namely graph-based pre-trained transformer force field (GPTFF), which can simulate arbitrary inorganic systems with good precision and…
Recent Breakthrough in AI-Driven Materials Science: Tech Giants Introduce Groundbreaking Models
Miao Liu, Sheng Meng
A close look of Google's GNoME inorganic materials dataset [Nature 624, 80 (2023)], and 11 things you would like to know.
MatChat: A Large Language Model and Application Service Platform for Materials Science
Ziyi Chen, Fankai Xie, Meng Wan +5
The prediction of chemical synthesis pathways plays a pivotal role in materials science research. Challenges, such as the complexity of synthesis pathways and the lack of comprehen…
Weberite NaMM'F (M,M'=Redox-Active Metal) as Promising Fluoride-Based Sodium-Ion Battery Cathodes
Tenglong Lu, Sheng Meng, Miao Liu
Sodium-ion batteries are a viable alternative to lithium-ion technology due to the plentiful sodium resources. However, certain commercialization challenges, such as low specific e…
Energy landscape and phase competition of CsV3Sb5-, CsV6Sb6-, and TbMn6Sn6-type Kagome materials
Guanghui Cai, Yutao Jiang, Hui Zhou +5
Finding viable Kagome lattices is vital for materializing novel phenomena in quantum materials. In this work, we performed element substitutions on CsV3Sb5 with space group P6/mmm,…
Electron-phonon interactions in LuH, LuH, and LuN
Tenglong Lu, Sheng Meng, Miao Liu
This paper presents the calculation results of electron-phonon interactions within the LuH, LuH, and LuN systems under 0 GPa and 10 GPa via density functional theory at the…
Percolation-induced resistivity drop in cold-pressed LuH2
Ningning Wang, Jun Hou, Ziyi Liu +9
The stoichiometric bulk LuH2 is a paramagnetic metal with high electrical conductivity comparable to simple metals. Here we show that the resistivity of cold-pressed (CP) LuH2 samp…
Lu-H-N phase diagram from first-principles calculations
Fankai Xie, Tenglong Lu, Ze Yu +4
Using a comprehensive structure search and high-throughput first-principles calculations of 1483 compounds, this study presents the phase diagram of Lu-H-N. The formation energy la…
Predicting structure-dependent Hubbard U parameters for assessing hybrid functional-level exchange via machine learning
Zhendong Cao, Guanghui Cai, Fankai Xie +7
DFT+U is a widely used treatment in the density functional theory (DFT) to deal with correlated materials that contain open-shell elements, whereby the quantitative and sometimes e…
Superconductive materials with MgB2-like structures from data-driven screening
Ze Yu, Tao Bo, Bo Liu +7
Finding viable superconducting materials is of interest to the physics community as the superconductors are the playground to manifest many appealing quantum phenomena. This work e…
Screening promising CsV3Sb5-like kagome materials from systematic first-principles evaluation
Yutao Jiang, Ze Yu, Yuxin Wang +4
CsV3Sb5 kagome lattice holds the promise for manifesting electron correlation, topology and superconducting. However, by far only three CsV3Sb5-like kagome materials have been expe…
A universal model for the formation energy prediction of inorganic compounds
Yingzong Liang, Mingwei Chen, Yanan Wang +5
Harnessing the recent advance in data science and materials science, it is feasible today to build predictive models for materials properties. In this study, we employ the data of…