5 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 b…
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…
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…
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…