2 citations · 4 across the 3 of their papers we have counts for
3 papers
physics.chem-ph2025★ 2 cited
Assessment of First-Principles Methods in Modeling the Melting Properties of Water
Yifan Li, Bingjia Yang, Chunyi Zhang +5
First-principles simulations have played a crucial role in deepening our understanding of the thermodynamic properties of water, and machine learning potentials (MLPs) trained on t…
physics.chem-ph2025★ 2 cited
Ab Initio Melting Properties of Water and Ice from Machine Learning Potentials
Yifan Li, Bingjia Yang, Chunyi Zhang +5
Liquid water exhibits several important anomalous properties in the vicinity of the melting temperature () of ice Ih, including a higher density than ice and a dens…
physics.chem-ph2025
A Machine Learning Model for the Chemistry of a Solvated Electron
Ruiqi Gao, Pinchen Xie, Roberto Car
In molecular simulations, machine-learning force fields can achieve ab initio accuracy at a lower cost but remain limited in the explicit modeling of electrons. In this work, we de…