Data from "Vapor-liquid equilibrium of water with the MB-pol many-body potential"

Muniz, Maria Carolina; Gartner III, Thomas E.; Riera, Marc; Knight, Christopher; Yue, Shuwen; Paesani, Francesco; Panagiotopoulos, Athanassios Z.
Issue date: 2021
Cite as:
Muniz, Maria Carolina, Gartner III, Thomas E., Riera, Marc, Knight, Christopher, Yue, Shuwen, Paesani, Francesco, & Panagiotopoulos, Athanassios Z. (2021). Data from "Vapor-liquid equilibrium of water with the MB-pol many-body potential" [Data set]. Princeton University. https://doi.org/10.34770/nfcx-rb66
@electronic{muniz_maria_carolina_2021,
  author      = {Muniz, Maria Carolina and
                Gartner III, Thomas E. and
                Riera, Marc and
                Knight, Christopher and
                Yue, Shuwen and
                Paesani, Francesco and
                Panagiotopoulos, Athanassios Z.},
  title       = {{Data from "Vapor-liquid equilibrium of w
                ater with the MB-pol many-body potential
                "}},
  publisher   = {{Princeton University}},
  year        = 2021,
  url         = {https://doi.org/10.34770/nfcx-rb66}
}
Abstract:

This dataset contains all data (including input files, simulation trajectories as well as other data files and analysis scripts) related to the publication "Vapor-liquid equilibrium of water with the MB-pol many-body potential" by Muniz et al. in preparation (2021). In this work, we assessed the performance of the MB-pol many-body potential with respect to water's vapor-liquid equilibrium properties. Through the use of direct coexistence molecular dynamics, we calculated properties such as coexistence densities, surface tension, vapor pressures and enthalpy of vaporization. We found that MB-pol is able to predict these properties in good agreement with experimental data. The results attest to the chemical accuracy of MB-pol and its large range of application across water's phase diagram.

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Description:

The README file present in the dataset provides a full description of its structure and identification of the files. This dataset is too large to download directly from this item page. You can access and download the data via Globus at this link: https://app.globus.org/file-manager?origin_id=dc43f461-0ca7-4203-848c-33a9fc00a464&origin_path=%2Fnfcx-rb66%2F (See https://docs.globus.org/how-to/get-started/ for instructions on how to use Globus; sign-in is required).

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