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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:

Assessing the potential of machine learning methods to study the removal of pharmaceuticals from wastewater using biochar or activated carbon
Jude A. Okolie, Shauna Savage, Chukwuma C. Ogbaga, et al.
Total Environment Research Themes (2022) Vol. 1-2, pp. 100001-100001
Open Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

Adsorptive removal of paracetamol from aqueous media: A review of adsorbent materials, adsorption mechanisms, advancements, and future perspectives
Md. Aminul Islam, Mazen K. Nazal, Muhammad Sajid, et al.
Journal of Molecular Liquids (2024) Vol. 396, pp. 123976-123976
Closed Access | Times Cited: 26
Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
Van Giao Nguyen, Prabhakar Sharma, Ümit Ağbulut, et al.
Biofuels Bioproducts and Biorefining (2024) Vol. 18, Iss. 2, pp. 567-593
Closed Access | Times Cited: 22
Machine learning applications in nanomaterials: Recent advances and future perspectives
Liang Yang, Hong Wang, Deying Leng, et al.
Chemical Engineering Journal (2024), pp. 156687-156687
Closed Access | Times Cited: 21
Machine learning applications for biochar studies: A mini-review
Wei Wang, Jo‐Shu Chang, Duu‐Jong Lee
Bioresource Technology (2024) Vol. 394, pp. 130291-130291
Closed Access | Times Cited: 15
Recent development in the sustainable remediation of antibiotics: A review
Kushneet Kaur Sodhi, C. K. Singh
Total Environment Research Themes (2022) Vol. 3-4, pp. 100008-100008
Open Access | Times Cited: 39
Machine learning applications in biomass pyrolysis: From biorefinery to end-of-life product management
David Akorede Akinpelu, Adekoya Oluwaseun Abiodun, Peter Olusakin Oladoye, et al.
Digital Chemical Engineering (2023) Vol. 8, pp. 100103-100103
Open Access | Times Cited: 36
CdS nanocrystallites sensitized ZnO nanosheets for visible light induced sonophotocatalytic/photocatalytic degradation of tetracycline: From experimental results to a generalized model based on machine learning methods
Amin Esmaeili, Shideh Pourranjabar Hasan Kiadeh, Azadeh Ebrahimian Pirbazari, et al.
Chemosphere (2023) Vol. 332, pp. 138852-138852
Closed Access | Times Cited: 29
Ensemble meta machine learning for predicting the adsorption of anionic and cationic dyes from aqueous solutions using Polymer/graphene/clay/MgFeAl-LTH nanocomposite
Galal M. BinMakhashen, Salem A. Bahadi, Hamdi A. Al-Jamimi, et al.
Chemosphere (2023) Vol. 349, pp. 140861-140861
Closed Access | Times Cited: 28
Old wine and new bottles: Insights into traditional attapulgite adsorbents with functionalized modification strategies applied in efficient phosphate immobilization
Shuai Liu, Fuqiang Fan, Xiaofei Liu, et al.
Journal of Cleaner Production (2023) Vol. 395, pp. 136451-136451
Closed Access | Times Cited: 26
A systematic review on applications of biochar and activated carbon derived from biomass as adsorbents for sustainable remediation of antibiotics from pharmaceutical wastewater
Zakariyya Uba Zango, Abdurrahman Garba, Abdurrashid Haruna, et al.
Journal of Water Process Engineering (2024) Vol. 67, pp. 106186-106186
Closed Access | Times Cited: 13
Advanced Oxidation Processes and Adsorption Technologies for the Removal of Organic Azo Compounds: UV, H2O2, and GAC
M. Ferre, M. J. Moya-Llamas, E. Domínguez, et al.
Water (2025) Vol. 17, Iss. 2, pp. 212-212
Open Access | Times Cited: 1
MachIne learning for nutrient recovery in the smart city circular economy – A review
Allan Soo, Li Wang, Chen Wang, et al.
Process Safety and Environmental Protection (2023) Vol. 173, pp. 529-557
Closed Access | Times Cited: 21
Process modelling integrated with interpretable machine learning for predicting hydrogen and char yield during chemical looping gasification
Arnold E. Sison, Sydney A. Etchieson, Fatih Güleç, et al.
Journal of Cleaner Production (2023) Vol. 414, pp. 137579-137579
Open Access | Times Cited: 18
Research on environmental aspects of retention/release of pollutants in soils and sorbents. What should be next?
Avelino Núñez‐Delgado
Environmental Research (2024) Vol. 251, pp. 118593-118593
Open Access | Times Cited: 7
Machine learning screening tools for the prediction of extraction yields of pharmaceutical compounds from wastewaters
Ana Casas, Diego Rodríguez-Llorente, Guillermo Rodríguez-Llorente, et al.
Journal of Water Process Engineering (2024) Vol. 62, pp. 105379-105379
Open Access | Times Cited: 6
Sustainable wastewater purification with crab shell-derived biochar: Advanced machine learning modeling & experimental analysis
Amina Bibi, Hammad Khan, Sajjad Hussain, et al.
Bioresource Technology (2023) Vol. 390, pp. 129900-129900
Closed Access | Times Cited: 15
Machine Learning Model for the Evaluation of Biomethane Potential Based on the Biochemical Composition of Biomass
Adekunle Akanni Adeleke, Jude A. Okolie, Chukwuma C. Ogbaga, et al.
BioEnergy Research (2023) Vol. 17, Iss. 1, pp. 731-743
Closed Access | Times Cited: 13
Deep Study on Fouling Modelling of Ultrafiltration Membranes Used for OMW Treatment: Comparison Between Semi-empirical Models, Response Surface, and Artificial Neural Networks
Magdalena Cifuentes-Cabezas, José Luis Bohórquez-Zurita, Sandra Gil-Herrero, et al.
Food and Bioprocess Technology (2023) Vol. 16, Iss. 10, pp. 2126-2146
Open Access | Times Cited: 12
Advancing Algal Biofuel Production through Data-Driven Insights: A Comprehensive Review of Machine Learning Applications
Omole Olakunle, Chukwuma C. Ogbaga, Jude A. Okolie, et al.
Computers & Chemical Engineering (2025), pp. 109049-109049
Closed Access
Precise prognostics of biochar yield from various biomass sources by Bayesian approach with supervised machine learning and ensemble methods
Van Giao Nguyen, Prabhakar Sharma, Ümit Ağbulut, et al.
International Journal of Green Energy (2023) Vol. 21, Iss. 9, pp. 2180-2204
Closed Access | Times Cited: 10
Aqueous Adsorption of Pharmaceutical Pollutants on Biochar: a Review on Physicochemical Characteristics, Classical Sorption Models, and Advancements in Machine Learning Techniques
Sarika Ravindra Kulkarni, Amrita Nighojkar, Balasubramanian Kandasubramanian
Water Air & Soil Pollution (2023) Vol. 234, Iss. 11
Closed Access | Times Cited: 8
Simultaneous Removal of Seven Pharmaceutical Compounds from a Water Mixture Using Modified Chitosan Adsorbent Materials
Myrsini Papageorgiou, Konstantinos N. Maroulas, Εleni Εvgenidou, et al.
Macromol—A Journal of Macromolecular Research (2024) Vol. 4, Iss. 2, pp. 304-319
Open Access | Times Cited: 2
Assessment of Published Papers on the Use of Machine Learning in Diagnosis and Treatment of Mastitis
Maria V. Bourganou, Yiannis Kiouvrekis, Dimitrios Chatzopoulos, et al.
Information (2024) Vol. 15, Iss. 8, pp. 428-428
Open Access | Times Cited: 2
Predicting biochar adsorption capacity for methylene blue removal using machine learning
P. K. Rajput, Shubham Yadav, Chong Liu, et al.
Journal of Water Process Engineering (2024) Vol. 69, pp. 106749-106749
Closed Access | Times Cited: 2
Predicting the Adsorption Efficiency Using Machine Learning Framework on a Carbon-Activated Nanomaterial
Kalapala Prasad, V. Ravikumar, Ravishankar Kumar, et al.
Adsorption Science & Technology (2023) Vol. 2023
Open Access | Times Cited: 6
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