363 citations · 898 across the 14 of their papers we have counts for
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dpti: An Automated Thermodynamic Integration Workflow for Phase Diagram Calculations with Machine Learning Interatomic Potentials
Fengbo Yuan, Xin Zhong, Donghao Zheng +4
Thermodynamic integration (TI) is a widely used approach for computing free energies and phase diagrams. However, TI calculations driven by machine learning interatomic potentials…
Hybrid Auxiliary Field Quantum Monte Carlo for Molecular Systems
Yixiao Chen, Linfeng Zhang, Weinan E +1
We propose a quantum Monte Carlo approach to solve the ground state many-body Schrodinger equation for the electronic ground state. The method combines optimization from variationa…
Machine learning assisted coarse-grained molecular dynamics modeling of meso-scale interfacial fluids
Pei Ge, Linfeng Zhang, Huan Lei
A hallmark of meso-scale interfacial fluids is the multi-faceted, scale-dependent interfacial energy, which often manifests different characteristics across the molecular and conti…
Warm dense matter simulation via electron temperature dependent deep potential molecular dynamics
Yuzhi Zhang, Chang Gao, Linfeng Zhang +2
Simulating warm dense matter that undergoes a wide range of temperatures and densities is challenging. Predictive theoretical models, such as quantum-mechanics-based first-principl…
Deep learning inter-atomic potential model for accurate irradiation damage simulations
Hao Wang, Xun Guo, Linfeng Zhang +2
We propose a hybrid scheme that interpolates smoothly the Ziegler-Biersack-Littmark (ZBL) screened nuclear repulsion potential with a newly developed deep learning potential energy…