Data analysis of CO2 hydrogenation catalysts for hydrocarbon production. (July 2022)
- Record Type:
- Journal Article
- Title:
- Data analysis of CO2 hydrogenation catalysts for hydrocarbon production. (July 2022)
- Main Title:
- Data analysis of CO2 hydrogenation catalysts for hydrocarbon production
- Authors:
- Fedorov, Aleksandr
Linke, David - Abstract:
- Abstract: Literature data of CO2 hydrogenation catalysts for hydrocarbon production via Fischer-Tropsch synthesis (FTS) were extracted from literature, collected into a SQLite database, and analyzed using data science and machine learning techniques. A challenge was to include performance data obtained by different groups which vary in the applied reaction conditions but vary also in the set of performance indicators that are reported. The thermodynamic ratio was used for analyzing reverse water gas shift reaction as the first stage of CO2 hydrogenation. A tailored Anderson-Schulz-Flory distribution modified by two additional parameters was suggested based on the data and applied for describing hydrocarbon production. The data analysis indicated the existence of direct CO2 conversion to hydrocarbons via the FT mechanism for some catalysts. It was shown that the chain growth probability as the key parameter of catalyst selectivity slightly depends on reaction condition (temperature, pressure, H2 :CO2 ratio) and is mainly defined by catalyst composition, method of catalyst preparation, nature of active sites and pretreatment conditions. With respect to the catalyst composition, it was found that doping catalysts by alkali metals like K or Na is the most effective measure to improve catalyst performance leading to increased chain growth probability, increased olefins content and a decrease of undesired CH4 formation.
- Is Part Of:
- Journal of CO₂ utilization. Volume 61(2022)
- Journal:
- Journal of CO₂ utilization
- Issue:
- Volume 61(2022)
- Issue Display:
- Volume 61, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 61
- Issue:
- 2022
- Issue Sort Value:
- 2022-0061-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-07
- Subjects:
- CO2 hydrogenation catalysts -- Data analysis -- Machine learning -- Anderson-Schulz-Flory distribution
Carbon dioxide -- Periodicals
Carbon dioxide -- Environmental aspects -- Periodicals
Carbon dioxide mitigation -- Periodicals
Carbon dioxide
Carbon dioxide -- Environmental aspects
Carbon dioxide mitigation
Periodicals
628.53205 - Journal URLs:
- http://www.sciencedirect.com/science/journal/22129820 ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.jcou.2022.102034 ↗
- Languages:
- English
- ISSNs:
- 2212-9820
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 21798.xml