Optimization of nickel-based catalysts for hydrogenolysis of light paraffins using machine learning
This study demonstrates the successful application of machine learning for the hydrogenolysis reaction. The prediction of more than a million generated experiments opens the way to identify the potentially best catalyst in the specified range.
Authors
- Nikita O. Azarapin (ORCID: https://orcid.org/0000-0003-1510-9749)
- Kirill Motaev (ORCID: https://orcid.org/0009-0005-3307-0958)
- Мaxim S. Моlokeev (ORCID: https://orcid.org/0000-0002-8297-0945)
- А. Н. Загоруйко (ORCID: https://orcid.org/0000-0001-6217-0302)
- M. Sebaa (ORCID: https://orcid.org/0000-0001-6409-5123)
- Andrey Elyshev (ORCID: https://orcid.org/0000-0001-8277-2626)
- Alexey V. Matigorov (ORCID: https://orcid.org/0000-0002-4073-1284)
- Alina Petrishena
Institutions
- University of Tyumen (RU)
- Boreskov Institute of Catalysis (RU)
Publication Details
- Journal
- Catalysis Science & Technology
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5cy00024f
- Citations
- 2
- Primary Topic
- Catalysis and Hydrodesulfurization Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.43
Funders
- Ministry of Education and Science of the Russian Federation