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http://arks.princeton.edu/ark:/88435/dsp01dj52w794k| Title: | Data for "First-principles-based Machine Learning Models for Phase Behavior and Transport Properties of CO2" |
| Contributors: | Mathur, Reha Yue, Shuwen Car, Roberto Panagiotopoulos, Athanassios Nicola Barbosa Muniz, Maria Carolina |
| Keywords: | machine-learning potentials carbon dioxide |
| Issue Date: | 10-Apr-2023 |
| Publisher: | Princeton University |
| 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. |
| URI: | https://doi.org/10.34770/3sr4-5g77 http://arks.princeton.edu/ark:/88435/dsp01dj52w794k |
| Referenced By: | R. Mathur, M. C. Muniz, S. Yue, R. Car and A. Z. Panagiotopoulos. First-principles-based Machine Learning Models for Phase Behavior and Transport Properties of CO2. Submitted to Journal of Physical Chemistry B. (2023) Link to the article will be added upon publication. |
| Appears in Collections: | Research Data Sets |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| DPMDCO2readme.txt | 5.2 kB | Text | View/Download | |
| DPMD-CO2-dataspace.tar.gz | 115.66 MB | Unknown | View/Download |
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