Machine learning and evolutionary prediction of superhard B-C-N compounds
Abstract We build random forests models to predict elastic properties and mechanical hardness of a compound, using only its chemical formula as input. The model training uses over 10,000 target compounds and 60 features based on stoichiometric attributes, elemental properties, orbital occupations, a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-07-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-021-00585-7 |