Statistical learning goes beyond the d-band model providing the thermochemistry of adsorbates on transition metals
Assessing catalytic mechanisms using DFT calculations greatly aids catalyst design, but is impractical for large molecules. Here the authors develop a statistical learning-based thermochemical model for estimating adsorption of organics onto metals, retaining DFT accuracy while reducing the number o...
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| Auteurs principaux: | , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2019
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/bcfedd75f53c4af9ad17dc158fdf3102 |
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