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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:

Modeling the ammonia absorption capacity of choline chloride-based deep eutectic solvents with artificial neural networks
Wen Sun, Tian Li, Huaqiang Chu, et al.
Journal of Cleaner Production (2022) Vol. 373, pp. 133764-133764
Closed Access | Times Cited: 11

Showing 11 citing articles:

Intelligent modeling of the hydrogen sulfide removal by deep eutectic solvents for the environmental protection
Xuhao Li, Wen Zhou, Jiajun Liu, et al.
Separation and Purification Technology (2023) Vol. 315, pp. 123621-123621
Closed Access | Times Cited: 15
Simultaneous prediction of CO2, CO, and NOx emissions of biodiesel-hydrogen blend combustion in compression ignition engines by supervised machine learning tools
Zhang LiWu, Zhu Guang-hui, Yanpu Chao, et al.
Energy (2023) Vol. 282, pp. 128972-128972
Closed Access | Times Cited: 14
An integrated ML model for the prediction of the melting points, phase diagrams, and eutectic points of the Type III and V deep eutectic solvents
Dian Jin, Haotian He, Li Sun, et al.
Chemical Engineering Science (2025), pp. 121245-121245
Closed Access
One stone, four birds: Deep eutectic solvents serve multiple functions in the development of flexible smart tag for monitoring the freshness of high-protein food
Yuxiao Hu, Jiayan Zhang, Jiaxin Tong, et al.
Chemical Engineering Journal (2025), pp. 161368-161368
Closed Access
Modeling and estimation of water activity for the ionic-liquid-based aqueous ternary systems by smart paradigms
Ehsan Davoudi, Abolhasan Ameri
Journal of the Taiwan Institute of Chemical Engineers (2024) Vol. 157, pp. 105396-105396
Closed Access | Times Cited: 3
A promising artificial intelligence-based tool to simulate the efficient and sustainable hydrogen sulfide elimination using deep eutectic solvents
Hulin Jin, Zhiran Jin, Yong-Guk Kim, et al.
Separation and Purification Technology (2023) Vol. 324, pp. 124472-124472
Closed Access | Times Cited: 8
A systematic approach based on artificial intelligence techniques for simulating the ammonia removal by eighteen deep eutectic solvents
Moxi Wang, Li Feng
Separation and Purification Technology (2023) Vol. 312, pp. 123292-123292
Closed Access | Times Cited: 6
Applying supervised intelligent scenarios to numerical investigate carbon dioxide capture using nanofluids
Li Feng, Kunyu Zhong, Jiajun Liu, et al.
Journal of Cleaner Production (2022) Vol. 381, pp. 135088-135088
Closed Access | Times Cited: 9
Porous acid–base hybrid polymers for enhanced NH3 uptake with assistance from cooperative hydrogen bonds
Xiaoyan Luo, Yibang Liu, Ming‐Xing Li, et al.
RSC Advances (2023) Vol. 13, Iss. 41, pp. 28729-28735
Open Access | Times Cited: 5
Efficient absorption of low pressure NH3 by non-ionic phenol-based deep eutectic solvents with multiple acidic sites
Ziyue Zhou, Yu Cao, Kai Zong, et al.
Journal of Molecular Liquids (2023) Vol. 389, pp. 122874-122874
Closed Access | Times Cited: 3
Machine learning assisted prediction of the nitric oxide (NO) solubility in various deep eutectic solvents
Hulin Jin, Yong-Guk Kim, Zhiran Jin, et al.
Journal of Industrial Information Integration (2024), pp. 100741-100741
Closed Access
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