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 in clarifying complex relationships: Biochar preparation procedures and capacitance characteristics
Yuxuan Sun, Peihao Sun, Jixiu Jia, et al.
Chemical Engineering Journal (2024) Vol. 485, pp. 149975-149975
Closed Access | Times Cited: 13

Showing 13 citing articles:

Research progress on activated persulfate by biochar: Soil and water environment remediation, mechanism exploration and simulation calculation
Ziming Xin, Jianhao Tong, Jing Wang, et al.
Chemical Engineering Journal (2024) Vol. 493, pp. 152718-152718
Closed Access | Times Cited: 13

Data-based modeling for prediction of supercapacitor capacity: Integrated machine learning and metaheuristic algorithms
Hamed Azimi, Ebrahim Ghorbani‐Kalhor, Seyed Reza Nabavi, et al.
Journal of the Taiwan Institute of Chemical Engineers (2025) Vol. 170, pp. 105996-105996
Closed Access

Bio-carbon composite for supercapacitor electrodes: Harnessing hydrochar frameworks and bio-tar polymerization
Jixiu Jia, Yuxuan Sun, Lili Huo, et al.
Fuel Processing Technology (2025) Vol. 269, pp. 108178-108178
Closed Access

New insights into the performance of biomass carbon-based supercapacitors based on interpretable machine learning approach
Pengfei Liu, Ge Yu, Huanhuan Li, et al.
Journal of Energy Storage (2025) Vol. 118, pp. 116300-116300
Closed Access

Modeling and analysis of droplet generation in microchannels using interpretable machine learning methods
Mengqi Liu, Haoyang Hu, Yongjin Cui, et al.
Chemical Engineering Journal (2025), pp. 161972-161972
Closed Access

Machine Learning Accelerated Discovery of Covalent Organic Frameworks for Environmental and Energy Applications
Hao Wang, Yuquan Li, Xiaoyang Xuan, et al.
Environmental Science & Technology (2025)
Closed Access

Critical insights into ensemble learning with decision trees for the prediction of biochar yield and higher heating value from pyrolysis of biomass
Saurav Kandpal, Ankita Tagade, Ashish N. Sawarkar
Bioresource Technology (2024) Vol. 411, pp. 131321-131321
Closed Access | Times Cited: 3

Opportunities and Threats for Supercapacitor Technology Based on Biochar—A Review
Radosław Kwarciany, Marcin Fiedur, Bogdan Saletnik
Energies (2024) Vol. 17, Iss. 18, pp. 4617-4617
Open Access | Times Cited: 2

Machine learning-assisted prediction, screen, and interpretation of porous carbon materials for high-performance supercapacitors
Hongwei Liu, Zhenming Cui, Zhennan Qiao, et al.
Journal of Materials Informatics (2024) Vol. 4, Iss. 4
Open Access | Times Cited: 2

Coal-based Si self-doped disordered porous carbon for supercapacitor electrodes
Yi Xiao, Duo Dong, Jiawei Wang, et al.
Chemical Engineering Journal (2024), pp. 157084-157084
Closed Access | Times Cited: 2

Studying the Thermodynamic Phase Stability of Organic–Inorganic Hybrid Perovskites Using Machine Learning
Juan Wang, Xinzhong Wang, Shun Feng, et al.
Molecules (2024) Vol. 29, Iss. 13, pp. 2974-2974
Open Access | Times Cited: 1

Robust prediction for characteristics of digestion products in an industrial-scale biogas project via typical non-time series and time-series machine learning algorithms
Ruixia Shen, Peihao Sun, Jie Liu, et al.
Chemical Engineering Journal (2024) Vol. 498, pp. 155582-155582
Closed Access | Times Cited: 1

Sustainably transforming biomass into advanced carbon materials for solid-state supercapacitors: A review
Ruoxun Fan, Beichen Xue, Pengfei Tian, et al.
Chemical Communications (2024)
Closed Access

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