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.
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2017-03-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/ncomms14621 |