Many-body machine learning models for water, acetonitrile, and methanol
Maldonado, Alex M.;
Many-body machine learning models for water, acetonitrile, and methanol
GDML, GAP, and SchNet models trained on 1-, 2-, and 3-body energies and forces of water, acetonitrile, and methanol. Energies and forces were computed at the MP2/def2-TZVP level of theory in ORCA v4.2.0. Data sets, training scripts, and analyses of these potentials are available here. Applications of these models on molecular dynamics simulations are found here.
- University of Pittsburgh United States
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selected citations
Citations provided by BIP!
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
Popularity provided by BIP! 0
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