Data for "First-principles-based Machine Learning Models for Phase Behavior and Transport Properties of CO2"

Nicola Barbosa Muniz, Maria Carolina
Issue date: 10 April 2023
Cite as:
Nicola Barbosa Muniz, Maria Carolina. (2023). Data for "First-principles-based Machine Learning Models for Phase Behavior and Transport Properties of CO2" [Data set]. Princeton University. https://doi.org/10.34770/3sr4-5g77
@electronic{nicola_barbosa_muniz_maria_carolina_2023,
  author      = {Nicola Barbosa Muniz, Maria Carolina},
  title       = {{Data for "First-principles-based Machine
                 Learning Models for Phase Behavior and
                Transport Properties of CO2"}},
  publisher   = {{Princeton University}},
  year        = 2023,
  url         = {https://doi.org/10.34770/3sr4-5g77}
}
Abstract:

This dataset contains example input files, training data sets and potential files related to the publication "First-principles-based Machine Learning Models for Phase Behavior and Transport Properties of CO2." by Mathur et al (2023). In this work, we developed machine learning models for CO2 based on different exchange-correlation DFT functionals. We assessed their performance on liquid densities, vapor-liquid equilibrium and transport properties.

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