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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:

Predicting THM Formation and Revealing Its Contributors in Drinking Water Treatment Using Machine Learning
Rabbi Sikder, Tianyu Zhang, Tao Ye
ACS ES&T Water (2023) Vol. 4, Iss. 3, pp. 899-912
Closed Access | Times Cited: 19

Showing 19 citing articles:

The Irreversible Transformation of the Molecular Structure of Humic Acid during pH Change and Its Effects on the Formation of Disinfection By-Products
Yun Xiao, Yufei Li, Hankun Yang, et al.
Journal of Hazardous Materials (2025) Vol. 488, pp. 137504-137504
Closed Access | Times Cited: 1
Application of artificial intelligence in (waste)water disinfection: Emphasizing the regulation of disinfection by-products formation and residues prediction
Yizhe Ding, Qiya Sun, Yuqian Lin, et al.
Water Research (2024) Vol. 253, pp. 121267-121267
Closed Access | Times Cited: 13
Complex impact of metals on the fate of disinfection by-products in drinking water pipelines: A systematic review
Xinming Guo, Xiaoyue Ji, Zihan Liu, et al.
Water Research (2024) Vol. 261, pp. 121991-121991
Closed Access | Times Cited: 10
Machine Learning-Assisted Raman Spectroscopy and SERS for Bacterial Pathogen Detection: Clinical, Food Safety, and Environmental Applications
Md Hasan-Ur Rahman, Rabbi Sikder, Manoj Tripathi, et al.
Chemosensors (2024) Vol. 12, Iss. 7, pp. 140-140
Open Access | Times Cited: 8
Machine learning framework for predicting cytotoxicity and identifying toxicity drivers of disinfection byproducts
Rabbi Sikder, Huichun Zhang, Peng Gao, et al.
Journal of Hazardous Materials (2024) Vol. 469, pp. 133989-133989
Closed Access | Times Cited: 6
Exploring the potential of machine learning to understand the occurrence and health risks of haloacetic acids in a drinking water distribution system
Ying Yu, Md. Mahjib Hossain, Rabbi Sikder, et al.
The Science of The Total Environment (2024) Vol. 951, pp. 175573-175573
Closed Access | Times Cited: 6
Transforming PFAS management: A critical review of machine learning applications for enhanced monitoring and treatment
Md Hasan-Ur Rahman, Rabbi Sikder, Tanvir Ahamed Tonmoy, et al.
Journal of Water Process Engineering (2025) Vol. 70, pp. 106941-106941
Closed Access
Machine Learning to Assess and Support Safe Drinking Water Supply: A Systematic Review
Feng Feng, Yuanxun Zhang, Zhenru Chen, et al.
Journal of environmental chemical engineering (2024), pp. 114481-114481
Closed Access | Times Cited: 3
Automated Crack Detection in 2D Hexagonal Boron Nitride Coatings Using Machine Learning
Md Hasan-Ur Rahman, Bichar Dip Shrestha Gurung, Bharat K. Jasthi, et al.
Coatings (2024) Vol. 14, Iss. 6, pp. 726-726
Open Access | Times Cited: 2
Applications of Machine Learning in Drinking Water Quality Management: A Critical Review on Water Distribution System
Zhaopeng Li, Wencheng Ma, Dan Zhong, et al.
Journal of Cleaner Production (2024) Vol. 481, pp. 144171-144171
Closed Access | Times Cited: 2
Photo driven homogeneous advanced oxidation coupled to adsorption process for an effective arsenic removal from drinking water
Anna Melnikova, Antonio Faggiano, M. Visconti, et al.
Journal of Environmental Management (2023) Vol. 349, pp. 119568-119568
Open Access | Times Cited: 3
Health impacts of poor water quality on an endangered shorebird breeding programme in Aotearoa New Zealand
Brett D. Gartrell, Stuart Hunter, Rose Collen, et al.
New Zealand Veterinary Journal (2023) Vol. 72, Iss. 2, pp. 103-111
Open Access | Times Cited: 2
Applications of Artificial Intelligence, Machine Learning, and Data Analytics in Water Environments
Huichun Zhang, Carla A. Ng
ACS ES&T Water (2024) Vol. 4, Iss. 3, pp. 761-763
Open Access
New insights into the reaction mechanisms and kinetics of aromatic compounds degraded by ClO· and BrO· to produce disinfection by-products
Yuhui Ma, Mingxue Li, Yanru Huo, et al.
Journal of environmental chemical engineering (2024) Vol. 12, Iss. 5, pp. 113770-113770
Closed Access
Advancements in electrocoagulation for oily wastewater treatment: Mechanisms, efficiency, and applications
Hansa Muvel, Manoj Kumar Jindal, P.K. Tewari, et al.
Journal of Water Process Engineering (2024) Vol. 68, pp. 106291-106291
Closed Access
Enhanced iodinated disinfection byproducts formation in iodide/iodate-containing water undergoing UV-chloramine sequential disinfection: machine learning-aided identification of reaction mechanisms
Zhen-Ning Luo, Huan He, Tian‐Yang Zhang, et al.
Water Research (2024) Vol. 272, pp. 122975-122975
Closed Access
Leveraging weak electrical stimulation and artificial intelligence for sustainable microbial dehalogenation in groundwater remediation
Miao Lv, Qianjing Yao, Zemin Qin, et al.
Elsevier eBooks (2024), pp. 475-490
Closed Access
Statistical modeling for iodinated trihalomethanes: Preformed chloramination versus prechlorination followed by ammonia addition
Gamze Ersan, Mahmut S. Erşan, Tanju Karanfil
Chemosphere (2024) Vol. 363, pp. 142876-142876
Closed Access
PREDICTIVE MODEL OF DISINFECTION BYPRODUCTS FROM NATURAL ORGANIC MATTERS USING HIGH-RESOLUTION MASS SPECTROMETRY AND MACHINE LEARNING
Kenji Yoshida, Jibao Liu, Eunsang Kwon, et al.
Japanese Journal of JSCE (2024) Vol. 80, Iss. 25, pp. n/a-n/a
Closed Access
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