5 papers
Dynamic Moiré Potentials and Robust Wigner Crystallization in Large-Scale Twisted Transition Metal Dichalcogenides
Yifan Ke, Chuanjing Zeng, Xinming Qin +3
Understanding the dynamical evolution of large-scale moiré systems is crucial for connecting theoretical predictions with experimental observations. Here we develop a machine-lear…
UniMatSim: A High-Throughput Materials Simulation Automation Framework Based on Universal Machine Learning Potentials
Yanjin Xiang, Yihan Nie, Yunzhi Gao +2
Universal machine learning interatomic potentials (UMLIPs) offer accuracy close to first-principles calculations at a fraction of the cost, showing significant potential for large-…
Non-Hermitian Bethe-Salpeter Equation for Open Systems: Emergence of Exceptional Points in Excitonic Spectra from First Principles
Zhenlin Zhang, Wei Hu, Enrico Perfetto +1
In open quantum systems hosting excitons, dissipation mechanisms critically shape the excitonic dynamics, band-structure and topological properties. A microscopic understanding of…
A Universal Deep Learning Force Field for Molecular Dynamic Simulation and Vibrational Spectra Prediction
Shengjiao Ji, Yujin Zhang, Zihan Zou +4
Accurate and efficient simulation of infrared (IR) and Raman spectra is essential for molecular identification and structural analysis. Traditional quantum chemistry methods based…
QMe14S, A Comprehensive and Efficient Spectral Dataset for Small Organic Molecules
Mingzhi Yuan, Zihan Zou, Wei Hu
Developing machine learning protocols for molecular simulations requires comprehensive and efficient datasets. Here we introduce the QMe14S dataset, comprising 186,102 small organi…