From the 1 of 93 linked papers with an AI index.
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DeePMD-kit v2: A software package for Deep Potential models
Jinzhe Zeng, Duo Zhang, Denghui Lu +44
DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. T…
A deep potential model with long-range electrostatic interactions
Linfeng Zhang, Han Wang, Maria Carolina Muniz +3
Machine learning models for the potential energy of multi-atomic systems, such as the deep potential (DP) model, make possible molecular simulations with the accuracy of quantum me…
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,…
Raman Spectrum and Polarizability of Liquid Water from Deep Neural Networks
Grace M. Sommers, Marcos F. Calegari Andrade, Linfeng Zhang +2
We introduce a scheme based on machine learning and deep neural networks to model the environmental dependence of the electronic polarizability in insulating materials. Application…
Isotope Effects in Liquid Water via Deep Potential Molecular Dynamics
Hsin-Yu Ko, Linfeng Zhang, Biswajit Santra +4
A comprehensive microscopic understanding of ambient liquid water is a major challenge for simulations as it simultaneously requires an accurate quantum mechanical de…
Searching for crystal-ice domains in amorphous ices
Fausto Martelli, Nicolas Giovambattista, Salvatore Torquato +1
We employ classical molecular dynamics simulations to investigate the molecular-level structure of water during the isothermal compression of hexagonal ice (I) and low-density a…