12 citations · 23 across the 8 of their papers we have counts for
8 papers
Polar vibrational excitations and glass-like response in relaxor PMN
Kehan Cai, Pinchen Xie, Yifan Li +1
Relaxor ferroelectrics retain crystalline order while exhibiting glass-like dielectric and thermal responses. Using atomistic models trained on first-principles data, we investigat…
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,…
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…
Intrinsic structure of relaxor ferroelectrics from first principles
Xinyu Xu, Kehan Cai, Yubai Shi +2
We develop FIRE-Swap, a first-principles framework for sampling intrinsic compositional structures in complex perovskites with machine-learning interatomic potentials (MLIPs). Usin…
Predicting open quantum dynamics with data-informed quantum-classical dynamics
Pinchen Xie, Ke Wang, Anupam Mitra +4
We introduce a data-informed quantum-classical dynamics (DIQCD) approach for predicting the evolution of an open quantum system. The equation of motion in DIQCD is a Lindblad equat…
Thermal disorder and phonon softening in the ferroelectric phase transition of lead titanate
Pinchen Xie, Yixiao Chen, Weinan E +1
We report a molecular dynamics study of ab initio quality of the ferroelectric phase transition in crystalline PbTiO3. We model anharmonicity accurately in terms of potential energ…
Coarse-graining conformational dynamics with multi-dimensional generalized Langevin equation: how, when, and why
Pinchen Xie, Yunrui Qiu, Weinan E
A data-driven ab initio generalized Langevin equation (AIGLE) approach is developed to learn and simulate high-dimensional, heterogeneous, coarse-grained conformational dynamics. C…