To address surface reaction network complexity using scaling relations machine learning and DFT calculations

Autor: Zachary W. Ulissi, Andrew J. Medford, Thomas Bligaard, Jens K. Nørskov
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: Nature Communications, Vol 8, Iss 1, Pp 1-7 (2017)
Druh dokumentu: article
ISSN: 2041-1723
DOI: 10.1038/ncomms14621
Popis: Finding catalyst mechanisms remains a challenge due to the complexity of hydrocarbon chemistry. Here, the authors shows that scaling relations and machine-learning methods can focus full-accuracy methods on the small subset of rate-limiting reactions allowing larger reaction networks to be treated.
Databáze: Directory of Open Access Journals