Proceedings of the 1st International Symposium on African Sustainable Energy Solutions (AfrSusEnS 2024)

<Previous Article In Volume
Next Article In Volume>

Application of Machine Learning in Analysis of the Effects of Co/SiO2 Catalyst Surface Area on CO Conversion during Fischer Tropsch Synthesis

Authors
N. Jim1, *, J. Gorimbo2, L. L. Jewell1, *, Y. Yao2, X. Liu2, L. L. Mguni2
1Department of Chemical and Materials Engineering, University of South Africa, c/o Pioneer Avenue and Christian De Wet, 1710, FL, Private bag X6, South Africa
2Institute of Catalysis and Energy Solutions, University of South Africa, c/o Pioneer Avenue and Christian De Wet, 1710, FL, Private bag X6, South Africa
*Corresponding author.
*Corresponding author. Email: jewelll@unisa.ac.za
Corresponding Authors
N. Jim, L. L. Jewell
Available Online 22 July 2025.
DOI
10.2991/978-94-6463-797-7_3How to use a DOI?
Keywords
Surface area; Catalyst; Machine learning
Abstract

Cobalt is one of the most common catalysts used in the Fischer-Tropsch (FT) process and the primary catalyst investigated in this study. Machine learning (ML) was used to analyze the variables that affect the FT process. This study investigates how surface area impacts CO adsorption and hydrocarbon product diffusion under dynamic reaction conditions such as temperature or pressure. 410 data points were collected from publications involving Co catalysts where 36 key input parameters related to the feed gas, catalyst properties, pretreatment, and reaction conditions were investigated to predict the CO conversion during the FT process. Random Forest algorithm was used for both feature importance analysis and regression tasks. An optimum surface area in the range of 430 - 450m2/g resulted in the highest CO conversion. The observed trends and prediction models can help design more selective catalysts for CO conversion via FT process and provide a guide in identifying the key descriptors in the Co catalyst design and operating conditions to enhance the CO conversion.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 1st International Symposium on African Sustainable Energy Solutions (AfrSusEnS 2024)
Series
Advances in Engineering Research
Publication Date
22 July 2025
ISBN
978-94-6463-797-7
ISSN
2352-5401
DOI
10.2991/978-94-6463-797-7_3How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - N. Jim
AU  - J. Gorimbo
AU  - L. L. Jewell
AU  - Y. Yao
AU  - X. Liu
AU  - L. L. Mguni
PY  - 2025
DA  - 2025/07/22
TI  - Application of Machine Learning in Analysis of the Effects of Co/SiO₂ Catalyst Surface Area on CO Conversion during Fischer Tropsch Synthesis
BT  - Proceedings of the 1st International Symposium on African Sustainable Energy Solutions (AfrSusEnS 2024)
PB  - Atlantis Press
SP  - 12
EP  - 19
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-797-7_3
DO  - 10.2991/978-94-6463-797-7_3
ID  - Jim2025
ER  -