Machine learning the metastable phase diagram of covalently bonded carbon
Exploration of metastable phases of a given elemental composition is a data-intensive task. Here the authors integrate first-principles atomistic simulations with machine learning and high-performance computing to allow a rapid exploration of the metastable phases of carbon.
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-06-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-022-30820-8 |