Machine learning potentials for metal-organic frameworks using an incremental learning approach
Abstract Computational modeling of physical processes in metal-organic frameworks (MOFs) is highly challenging due to the presence of spatial heterogeneities and complex operating conditions which affect their behavior. Density functional theory (DFT) may describe interatomic interactions at the qua...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-02-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-023-00969-x |