Bayesian learning of chemisorption for bridging the complexity of electronic descriptors
Developing a generalizable model to describe adsorption processes at metal surfaces can be extremely challenging due to complex phenomena involved. Here the authors introduce a Bayesian learning approach based on ab initio data and the d-band model to capture the essential physics of adsorbate–subst...
| Asıl Yazarlar: | , , |
|---|---|
| Materyal Türü: | Makale |
| Dil: | English |
| Baskı/Yayın Bilgisi: |
Nature Portfolio
2020-11-01
|
| Seri Bilgileri: | Nature Communications |
| Online Erişim: | https://doi.org/10.1038/s41467-020-19524-z |