OpenAlex Citation Counts

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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:

Innovative clean hybrid energy system driven by flame-assisted SOFC: Multi-criteria optimization with ANN and genetic algorithm
Tao Hai, Hamad Almujibah, Loghman Mostafa, et al.
International Journal of Hydrogen Energy (2024) Vol. 63, pp. 193-206
Closed Access | Times Cited: 5

Showing 5 citing articles:

Quantitative analysis of energy justice in demand response: Insights from real residential data in Texas, USA
Yuan Gao, Mingzhe Liu, Zehuan Hu, et al.
Renewable Energy (2025), pp. 122477-122477
Open Access

Novel multigeneration system based on a flame-assisted fuel cell for use in residential applications
MohammadBagher Amiri, Mortaza Yari, Faramarz Ranjbar, et al.
International Journal of Hydrogen Energy (2025) Vol. 105, pp. 778-796
Closed Access

Leveraging data-driven strategy for redesigning the tubular fixed bed propane dehydrogenation reactor
Yannan Xia, Liming Zheng, Zuhao Feng, et al.
International Journal of Hydrogen Energy (2025) Vol. 106, pp. 935-947
Closed Access

Understanding Solid Oxide Fuel Cell Hybridization: A Critical Review
Ioannis Nikiforakis, Sotirios Mamalis, Dimitris Assanis
Applied Energy (2024) Vol. 377, pp. 124277-124277
Open Access | Times Cited: 2

Optimizing neural network models for predicting nuclear reactor channel temperature: A study on hyperparameter tuning and performance analysis
Sinem Uzun, Eyyüp Yıldız, Hatice Arslantaş
Nuclear Engineering and Design (2024) Vol. 429, pp. 113636-113636
Closed Access | Times Cited: 1

Prediction of Hydrogen Production from Solid Oxide Electrolytic Cells Based on ANN and SVM Machine Learning Methods
Ke Chen, Youran Li, Jie Chen, et al.
Atmosphere (2024) Vol. 15, Iss. 11, pp. 1344-1344
Open Access

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