article Open AccessTop 1% cited
DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics
Computer Physics Communications · 2018 · Vol. 228 · pp. 178–184
Han Wang✉(Numerical Method (China))Linfeng Zhang✉(Princeton University)Jiequn Han(Princeton University)E Weinan(Princeton University)
Machine Learning in Materials ScienceProtein Structure and DynamicsAdvanced Chemical Physics StudiesMolecular dynamicsRepresentation (politics)Computer scienceStatistical physicsDynamics (music)Energy (signal processing)Computational scienceArtificial intelligencePhysicsComputational chemistry
Funding
- U.S. Department of Energy
- National Natural Science Foundation of China
- Office of Naval Research
Citations
1,898
FWCI
24.76
field-weighted impact
References
38
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100%
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References
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Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces
Physical Review Letters · 2007 · 4,776 citations
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Physical Review B · 2013 · 2,551 citations
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Development and Testing of the OPLS All-Atom Force Field on Conformational Energetics and Properties of Organic Liquids
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CHARMM general force field: A force field for drug‐like molecules compatible with the CHARMM all‐atom additive biological force fields
Journal of Computational Chemistry · 2009 · 7,311 citations
Development and testing of a general amber force field
Journal of Computational Chemistry · 2004 · 19,029 citations
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