Vasylenko, Andrij (2022) Data for "Element selection for functional materials discovery by integrated machine learning of atomic contributions to properties". [Data Collection]
Data Catalogue DOI: 10.17638/datacat.liverpool.ac.uk/1613
Description
Collection of the datasets for training phase fields ranking and classification for three target properties: superconducting transition temperature, magnetic transition temperature, energy band gap. Predictions for the unexplored phase ternary phase fields and for the phase fields in ICSD that have not been studied with respect to the target properties.
| Keywords: | Superconducting, magnetic, energy band gap phase fields datasets for training and testing. |
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| Divisions: | Faculty of Science and Engineering > School of Physical Sciences > School of Physical Sciences |
| Depositing User: | Andrij Vasylenko |
| Date Deposited: | 31 Jan 2022 18:20 |
| Last Modified: | 31 Jan 2022 18:20 |
| DOI: | 10.17638/datacat.liverpool.ac.uk/1613 |
| URI: | https://datacat.liverpool.ac.uk/id/eprint/1613 |
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Creative Commons: Attribution 4.0 |
