2 citations · 6 across the 8 of their papers we have counts for
5 papers · 1 filter
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…
fix pimd/langevin: An Efficient Implementation of Path Integral Molecular Dynamics in LAMMPS
Yifan Li, Axel Gomez, Kehan Cai +10
Path integral molecular dynamics (PIMD), which maps a quantum particle onto a fictitious classical system of ring polymers and propagates the "beads" of this extended classical sys…
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…
Training Dataset Matters for Machine Learning Interatomic Potentials: Water Simulation as an Example
Yifan Li, Bingjia Yang, Chunyi Zhang +5
Accurate predictions of machine learning interatomic potentials (MLIPs) rely on training datasets covering relevant thermodynamic conditions and phases. Using water as an example,…
Electrical double layer and capacitance of TiO2 electrolyte interfaces from first principles simulations
Chunyi Zhang, Marcos Calegari Andrade, Zachary K. Goldsmith +6
The electrical double layer (EDL) at aqueous solution-metal oxide interfaces critically affects many fundamental processes in electrochemistry, geology and biology, yet understandi…