17 citations · 42 across the 9 of their papers we have counts for
9 papers
Understanding the Density Maximum of Water with Machine Learned Potentials
Yizhi Song, Renxi Liu, Chunyi Zhang +5
After melting, at ambient pressure, the density of water continues to increase with temperature until it reaches a maximum around 4 °C. For nearly a century, this phenomenon has be…
Investigating CO Adsorption on Cu(111) and Rh(111) Surfaces Using Machine Learning Exchange-Correlation Functionals
Xinyuan Liang, Renxi Liu, Mohan Chen
The "CO adsorption puzzle", a persistent failure of utilizing generalized gradient approximations (GGA) in density functional theory to replicate CO's experimental preference for t…
A Deep Learning Framework for the Electronic Structure of Water: Towards a Universal Model
Xinyuan Liang, Renxi Liu, Mohan Chen
Accurately modeling the electronic structure of water across scales, from individual molecules to bulk liquid, remains a grand challenge. Traditional computational methods face a c…
ABACUS: An Electronic Structure Analysis Package for the AI Era
Weiqing Zhou, Daye Zheng, Qianrui Liu +55
ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It…
Exploring the energy landscape of aluminas through machine learning interatomic potential
Lei Zhang, Wenhao Luo, Renxi Liu +3
Aluminum oxide (alumina, AlO) exists in various structures and has broad industrial applications. While the crystal structure of -AlO is well-established, those…
Implementation of the SCAN Exchange-Correlation Functional with Numerical Atomic Orbitals
Renxi Liu, Daye Zheng, Xinyuan Liang +3
Kohn-Sham density functional theory (DFT) is nowadays widely used for electronic structure theory simulations, and the accuracy and efficiency of DFT rely on approximations of the…
Characterization of the Hydrogen-Bond Network in High-Pressure Water by Deep Potential Molecular Dynamics
Renxi Liu, Mohan Chen
The hydrogen-bond (H-bond) network of high-pressure water is investigated by neural-network-based molecular dynamics (MD) simulations with the first-principles accuracy. The static…
DeePKS+ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials
Wenfei Li, Qi Ou, Yixiao Chen +9
Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanica…
Structural and Dynamic Properties of Solvated Hydroxide and Hydronium Ions in Water from Ab Initio Modeling
Renxi Liu, Chunyi Zhang, Xinyuan Liang +3
Predicting the asymmetric structure and dynamics of solvated hydroxide and hydronium in water has been a challenging task from ab initio molecular dynamics (AIMD). The difficulty m…