OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
Application of Machine Learning to Fischer–Tropsch Synthesis for Cobalt Catalysts
Kirill Motaev, Maxim S. Мolokeev, Bulat Sultanov, et al.
Industrial & Engineering Chemistry Research (2023) Vol. 62, Iss. 48, pp. 20658-20666
Closed Access | Times Cited: 7
Kirill Motaev, Maxim S. Мolokeev, Bulat Sultanov, et al.
Industrial & Engineering Chemistry Research (2023) Vol. 62, Iss. 48, pp. 20658-20666
Closed Access | Times Cited: 7
Showing 7 citing articles:
Screening High-Performance Hybrid Halides Scintillators: A Comprehensive Analysis and Prediction Model
Maxim S. Мolokeev, Nicolay N. Golovnev, Andrey Zolotov, et al.
Chemistry of Materials (2025)
Closed Access | Times Cited: 1
Maxim S. Мolokeev, Nicolay N. Golovnev, Andrey Zolotov, et al.
Chemistry of Materials (2025)
Closed Access | Times Cited: 1
Application of machine learning in the study of cobalt-based oxide catalysts for antibiotic degradation: An innovative reverse synthesis strategy
Siyuan Jiang, Wen Xu, Qi Xia, et al.
Journal of Hazardous Materials (2024) Vol. 471, pp. 134309-134309
Closed Access | Times Cited: 6
Siyuan Jiang, Wen Xu, Qi Xia, et al.
Journal of Hazardous Materials (2024) Vol. 471, pp. 134309-134309
Closed Access | Times Cited: 6
Parametric analysis of CO2 hydrogenation via Fischer-Tropsch synthesis: A review based on machine learning for quantitative assessment
Jing Hu, Yixao Wang, Xiyue Zhang, et al.
International Journal of Hydrogen Energy (2024) Vol. 59, pp. 1023-1041
Open Access | Times Cited: 5
Jing Hu, Yixao Wang, Xiyue Zhang, et al.
International Journal of Hydrogen Energy (2024) Vol. 59, pp. 1023-1041
Open Access | Times Cited: 5
Improving Catalysts and Operating Conditions Using Machine Learning in Fischer-Tropsch Synthesis of Jet Fuels (C8-C16)
Parisa Shafiee, Bogdan Dorneanu, Harvey Arellano‐García
Chemical Engineering Journal Advances (2025), pp. 100702-100702
Open Access
Parisa Shafiee, Bogdan Dorneanu, Harvey Arellano‐García
Chemical Engineering Journal Advances (2025), pp. 100702-100702
Open Access
Machine learning and experimental study on the activity decrease of VW/Ti for SCR at ultra-high temperature: the influence mechanism and regulation strategy
Jia Guo, Yongqi Zhao, Junjie Jiang, et al.
Process Safety and Environmental Protection (2025), pp. 107021-107021
Closed Access
Jia Guo, Yongqi Zhao, Junjie Jiang, et al.
Process Safety and Environmental Protection (2025), pp. 107021-107021
Closed Access
Toward accelerated discovery of solid catalysts using extrapolative machine learning approach
Takashi Toyao
Chemistry Letters (2024) Vol. 53, Iss. 8
Open Access | Times Cited: 1
Takashi Toyao
Chemistry Letters (2024) Vol. 53, Iss. 8
Open Access | Times Cited: 1
Application of machine learning for material prediction and design in the environmental remediation
Yunzhe Zheng, Si Sun, Jiali Liu, et al.
Chinese Chemical Letters (2024), pp. 110722-110722
Closed Access | Times Cited: 1
Yunzhe Zheng, Si Sun, Jiali Liu, et al.
Chinese Chemical Letters (2024), pp. 110722-110722
Closed Access | Times Cited: 1
