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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:

“pySiRC”: Machine Learning Combined with Molecular Fingerprints to Predict the Reaction Rate Constant of the Radical-Based Oxidation Processes of Aqueous Organic Contaminants
Flávio O. Sanches-Neto, Jefferson R. Dias-Silva, Luiz Henrique Keng Queiroz Júnior, et al.
Environmental Science & Technology (2021) Vol. 55, Iss. 18, pp. 12437-12448
Closed Access | Times Cited: 74

Showing 1-25 of 74 citing articles:

Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and Reactors
Li‐Tao Zhu, Xizhong Chen, Bo Ouyang, et al.
Industrial & Engineering Chemistry Research (2022) Vol. 61, Iss. 28, pp. 9901-9949
Open Access | Times Cited: 145
Count-Based Morgan Fingerprint: A More Efficient and Interpretable Molecular Representation in Developing Machine Learning-Based Predictive Regression Models for Water Contaminants’ Activities and Properties
Shifa Zhong, Xiaohong Guan
Environmental Science & Technology (2023) Vol. 57, Iss. 46, pp. 18193-18202
Closed Access | Times Cited: 55
Advancements in heterogeneous activation of persulfates: Exploring mechanisms, challenges in organic wastewater treatment, and innovative solutions
Fei Chen, Xin-Tong Huang, Chang-Wei Bai, et al.
Chemical Engineering Journal (2024) Vol. 481, pp. 148789-148789
Closed Access | Times Cited: 32
Efficient removal of micropollutants from low-conductance surface water using an electrochemical Janus ceramic membrane filtration system
Zhouyan Li, Xuesong Li, Yang Li, et al.
Water Research (2022) Vol. 220, pp. 118627-118627
Closed Access | Times Cited: 43
Comparison of sulfate radical with other reactive species
Xiaodi Duan, Xiaoxiao Niu, Jiong Gao, et al.
Current Opinion in Chemical Engineering (2022) Vol. 38, pp. 100867-100867
Closed Access | Times Cited: 41
Machine Learning Models for Inverse Design of the Electrochemical Oxidation Process for Water Purification
Ye Sun, Zhiyuan Zhao, Hailong Tong, et al.
Environmental Science & Technology (2023) Vol. 57, Iss. 46, pp. 17990-18000
Closed Access | Times Cited: 33
Multi-dimensional micro-nano scale manganese oxide catalysts induced chemical-based advanced oxidation processes (AOPs) in environmental applications: A critical review
Lin Lin, Junsen Wang, Zhifang Zhao, et al.
Chemical Engineering Journal (2023) Vol. 474, pp. 145600-145600
Closed Access | Times Cited: 31
Low-cost machine learning prediction of excited state properties of iridium-centered phosphors
Gianmarco Terrones, Chenru Duan, Aditya Nandy, et al.
Chemical Science (2023) Vol. 14, Iss. 6, pp. 1419-1433
Open Access | Times Cited: 24
A machine learning method to predict rate constants for various reactions in combustion kinetic models
Ning Li, Sanket Girhe, Mingzhi Zhang, et al.
Combustion and Flame (2024) Vol. 263, pp. 113375-113375
Closed Access | Times Cited: 9
A novel interpretable machine learning model approach for the prediction of TiO2 photocatalytic degradation of air contaminants
Rodrigo Teixeira Schossler, Samuel Ojo, Zhuoying Jiang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 8
Current Status of Emerging Contaminant Models and Their Applications Concerning the Aquatic Environment: A Review
Zhuang Liu, Yonghai Gan, Jun Luo, et al.
Water (2025) Vol. 17, Iss. 1, pp. 85-85
Open Access | Times Cited: 1
Interpretable Machine Learning Models Delivering a New Perspective for the Reaction Mechanism between Organic Pollutants and Oxidative Radicals
Yiqiu Wu, Zhixiang Wang, Guangfei Yu, et al.
Environmental Science & Technology (2025)
Closed Access | Times Cited: 1
Practical Machine Learning Model Selection and Interpretation for Organophosphorus Flame Retardancy in Epoxy Resin
Jiajun Li, Bin Zou, Amirbek Bekeshev, et al.
Polymer Degradation and Stability (2025) Vol. 234, pp. 111209-111209
Closed Access | Times Cited: 1
Investigation of the Binding Fraction of PFAS in Human Plasma and Underlying Mechanisms Based on Machine Learning and Molecular Dynamics Simulation
Huiming Cao, Peng Jian-hua, Zhen Zhou, et al.
Environmental Science & Technology (2022) Vol. 57, Iss. 46, pp. 17762-17773
Closed Access | Times Cited: 30
Machine learning-assisted data filtering and QSAR models for prediction of chemical acute toxicity on rat and mouse
Tao Bo, Yaohui Lin, Jinglong Han, et al.
Journal of Hazardous Materials (2023) Vol. 452, pp. 131344-131344
Closed Access | Times Cited: 19
Machine learning for predicting halogen radical reactivity toward aqueous organic chemicals
Youheng Liang, Xiaoliu Huangfu, Ruixing Huang, et al.
Journal of Hazardous Materials (2024) Vol. 472, pp. 134501-134501
Closed Access | Times Cited: 6
Improved Machine Learning Models by Data Processing for Predicting Life-Cycle Environmental Impacts of Chemicals
Ye Sun, Xiuheng Wang, Nanqi Ren, et al.
Environmental Science & Technology (2022) Vol. 57, Iss. 8, pp. 3434-3444
Closed Access | Times Cited: 24
Machine Learning Modeling of Environmentally Relevant Chemical Reactions for Organic Compounds
Kai Zhang, Huichun Zhang
ACS ES&T Water (2022) Vol. 4, Iss. 3, pp. 773-783
Closed Access | Times Cited: 23
Developing machine learning approaches to identify candidate persistent, mobile and toxic (PMT) and very persistent and very mobile (vPvM) substances based on molecular structure
Han Min, Biao Jin, Jun Liang, et al.
Water Research (2023) Vol. 244, pp. 120470-120470
Closed Access | Times Cited: 13
Enhancing compound confidence in suspect and non-target screening through machine learning-based retention time prediction
Dehao Song, Ting Tang, Rui Wang, et al.
Environmental Pollution (2024) Vol. 347, pp. 123763-123763
Closed Access | Times Cited: 5
Molecular fingerprint-aided prediction of organic solute rejection in reverse osmosis and nanofiltration
Sangsuk Lee, Michael R. Shirts, Anthony P. Straub
Journal of Membrane Science (2024) Vol. 705, pp. 122927-122927
Closed Access | Times Cited: 5
Machine learning-guided strategies for reaction conditions design and optimization
Lung-Yi Chen, Yi‐Pei Li
Beilstein Journal of Organic Chemistry (2024) Vol. 20, pp. 2476-2492
Open Access | Times Cited: 5
Evaluating and elucidating the reactivity of OH radicals with atmospheric organic pollutants: Reaction kinetics and mechanisms by machine learning
Flávio O. Sanches-Neto, Jefferson R. Dias-Silva, Vitor Mendes de Oliveira, et al.
Atmospheric Environment (2022) Vol. 275, pp. 119019-119019
Closed Access | Times Cited: 20
Theoretical insights into the oxidation of quinmerac herbicide initiated by HO• radical in aqueous media: Mechanism, kinetics, and ecotoxicity
Thị Chinh Ngo, Sonia Taamalli, Zainab Srour, et al.
Journal of environmental chemical engineering (2023) Vol. 11, Iss. 3, pp. 109941-109941
Open Access | Times Cited: 11
Application of machine learning and deep learning methods for hydrated electron rate constant prediction
Shanshan Zheng, Wanqian Guo, Chao Li, et al.
Environmental Research (2023) Vol. 231, pp. 115996-115996
Closed Access | Times Cited: 11
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