83 citations · 83 across the 1 of their papers we have counts for
6 papers
Modeling liquid water by climbing up Jacob's ladder in density functional theory facilitated by using deep neural network potentials
Chunyi Zhang, Fujie Tang, Mohan Chen +5
Within the framework of Kohn-Sham density functional theory (DFT), the ability to provide good predictions of water properties by employing a strongly constrained and appropriately…
The Phase Diagram of a Deep Potential Water Model
Linfeng Zhang, Han Wang, Roberto Car +1
Using the Deep Potential methodology, we construct a model that reproduces accurately the potential energy surface of the SCAN approximation of density functional theory for water,…
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…
Adaptive coupling of a deep neural network potential to a classical force field
Linfeng Zhang, Han Wang, Weinan E
An adaptive modeling method (AMM) that couples a deep neural network potential and a classical force field is introduced to address the accuracy-efficiency dilemma faced by the mol…
DeePCG: constructing coarse-grained models via deep neural networks
Linfeng Zhang, Jiequn Han, Han Wang +2
We introduce a general framework for constructing coarse-grained potential models without ad hoc approximations such as limiting the potential to two- and/or three-body contributio…