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

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.

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Autores principales: Zachary W. Ulissi, Andrew J. Medford, Thomas Bligaard, Jens K. Nørskov
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2017
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Acceso en línea:https://doaj.org/article/f70daa3691ba4e61869251a1b60cfe88
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