11 citations · 20 across the 5 of their papers we have counts for
5 papers
Agentic Discovery of Exchange-Correlation Density Functionals
Titouan Duston, Jiashu Liang, Yuanheng Wang +6
The development of accurate exchange-correlation (XC) functionals remains a longstanding challenge in density functional theory (DFT). The vast majority of XC functionals have been…
Accelerated Machine Learning Force Field for Predicting Thermal Conductivity of Organic Liquids
Wei Feng, Siyuan Liu, Hongyi Wang +11
The thermal conductivity of organic liquids is a vital parameter influencing various industrial and environmental applications, including energy conversion, electronics cooling, an…
CrysToGraph: A Comprehensive Predictive Model for Crystal Materials Properties and the Benchmark
Hongyi Wang, Ji Sun, Jinzhe Liang +7
The ionic bonding across the lattice and ordered microscopic structures endow crystals with unique symmetry and determine their macroscopic properties. Unconventional crystals, in…
Enhancing GPU-acceleration in the Python-based Simulations of Chemistry Framework
Xiaojie Wu, Qiming Sun, Zhichen Pu +11
We describe our contribution as industrial stakeholders to the existing open-source GPU4PySCF project (https: //github.com/pyscf/gpu4pyscf), a GPU-accelerated Python quantum chemis…
A predictive machine learning force field framework for liquid electrolyte development
Sheng Gong, Yumin Zhang, Zhenliang Mu +13
Despite the widespread applications of machine learning force fields (MLFF) in solids and small molecules, there is a notable gap in applying MLFF to simulate liquid electrolyte, a…