Nature Communications (Mar 2017)

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

  • Zachary W. Ulissi,
  • Andrew J. Medford,
  • Thomas Bligaard,
  • Jens K. Nørskov

DOI
https://doi.org/10.1038/ncomms14621
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 7

Abstract

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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.