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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:

Machine learning: An accelerator for the exploration and application of advanced metal-organic frameworks
Ruolin Du, R. C. Xin, Han Wang, et al.
Chemical Engineering Journal (2024) Vol. 490, pp. 151828-151828
Closed Access | Times Cited: 8

Showing 8 citing articles:

Biomass: The accelerator for moving MOFs to practical applications
Rongfu Peng, R. C. Xin, Dujuan Wu, et al.
Chemical Engineering Journal (2024) Vol. 497, pp. 154908-154908
Closed Access | Times Cited: 9
Generation and π-phase-induced oscillations of multi-soliton molecular complexes in ultrafast fiber lasers based on MOF-253@Au
Zhi‐Zeng Si, Long‐Fei Ren, Dalei Wang, et al.
Chemical Engineering Journal (2025), pp. 159024-159024
Closed Access
Artificial Intelligence in Metal–Organic Frameworks from 2013 to 2024: A Bibliometric Analysis
Jian Cao, Ling Zhou, Fan Gan, et al.
JOM (2025)
Open Access
CO2 Adsorption Using Graphene-Based Materials: A Review
Ridhwan Lawal, Mohammad M. Hossain
Arabian Journal for Science and Engineering (2025)
Closed Access
Application of machine learning in adsorption energy storage using metal organic frameworks: A review
Nokubonga P. Makhanya, Michael Kumi, Charles Mbohwa, et al.
Journal of Energy Storage (2025) Vol. 111, pp. 115363-115363
Closed Access
Chemical-guided screening of top-performing metal–organic frameworks for hydrogen storage: An explainable deep attention convolutional model
Abdulrahman H. Ba-Alawi, Sridhar Palla, A. Seshagiri Rao, et al.
Chemical Engineering Journal (2024), pp. 155626-155626
Closed Access | Times Cited: 2
Machine learning approaches for the prediction of hydrogen uptake in metal-organic-frameworks: A comprehensive review
Aryan Anil Yamde, Vikesh G. Lade, Ankush B. Bindwal, et al.
International Journal of Hydrogen Energy (2024) Vol. 98, pp. 1131-1154
Closed Access | Times Cited: 1
Rapid analysis of salivary glucose content using MOF/MIPs biomimetic microfluidic paper chips
Ningning Li, Ying Zhou, Hao Sun, et al.
Chemical Engineering Journal (2024), pp. 159023-159023
Closed Access
Climate friendly MOFs synthesis for drug delivery systems by integrating AI, intelligent manufacturing, and quantum solutions in industry 6.0 sustainable approach
M. Akhtar, Hammad Majeed, Tehreema Iftikhar, et al.
Toxicology Research (2024) Vol. 14, Iss. 1
Closed Access
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