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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| Main Authors: | , , , |
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| Format: | article |
| Language: | EN |
| Published: |
Nature Portfolio
2017
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| Subjects: | |
| Online Access: | https://doaj.org/article/f70daa3691ba4e61869251a1b60cfe88 |
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| Summary: | 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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