3 citations · 7 across the 4 of their papers we have counts for
4 papers
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,…
Deuteration removes quantum dipolar defects from KDP crystals
Bingjia Yang, Pinchen Xie, Roberto Car
The structural, dielectric, and thermodynamic properties of the hydrogen-bonded ferroelectric crystal potassium dihydrogen phosphate (), KDP for short, differ si…
Quantum effects in the H-bond symmetrization and in the thermodynamic properties of high pressure ice
Marco Cherubini, Lorenzo Monacelli, Bingjia Yang +3
We investigate the structural and thermodynamic properties of high-pressure ice by incorporating quantum anharmonicity at a non-perturbative level. Quantum fluctuations reduce the…