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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:

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

Showing 24 citing articles:

Emerging applications of biochar: A review on techno-environmental-economic aspects
Zhu Hui, Qing Long An, Amirah Syafika Mohd Nasir, et al.
Bioresource Technology (2023) Vol. 388, pp. 129745-129745
Closed Access | Times Cited: 42
From immunology to artificial intelligence: revolutionizing latent tuberculosis infection diagnosis with machine learning
Linsheng Li, Ling Yang, Zhuang Li, et al.
Military Medical Research (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 27
Enhanced Deep-Learning Model for Carbon Footprints of Chemicals
Dachuan Zhang, Zhanyun Wang, Christopher Oberschelp, et al.
ACS Sustainable Chemistry & Engineering (2024) Vol. 12, Iss. 7, pp. 2700-2708
Open Access | Times Cited: 8
Toward artificial intelligence and machine learning-enabled frameworks for improved predictions of lifecycle environmental impacts of functional materials and devices
Taofeeq Ibn‐Mohammed, K.B. Mustapha, M. Abdulkareem, et al.
MRS Communications (2023) Vol. 13, Iss. 5, pp. 795-811
Open Access | Times Cited: 17
Procedural life cycle inventory of chemical products at laboratory and pilot scale: a compendium
Daniele Cespi
Green Chemistry (2024) Vol. 26, Iss. 18, pp. 9554-9568
Open Access | Times Cited: 4
Developing Physiologically Compatible Electron Donors for Reductive Dechlorination by Dissimilatory Iron-Reducing Bacteria Using Machine Learning
Yang Yu, Jiuling Li, Defeng Xing, et al.
ACS ES&T Engineering (2025)
Closed Access
Integrating machine learning with life cycle assessment: a comprehensive review and guide for predicting environmental impacts
João Victor Encide Salla, Tiago A. Almeida, Diogo Aparecido Lopes Silva
The International Journal of Life Cycle Assessment (2025)
Closed Access
Prediction and Detection of Localised Corrosion Attack of Stainless Steel in Biogas Production: A Machine Learning Classification Approach
M.J. Jiménez–Come, Francisco Javier González Gallero, Pascual Álvarez Gómez, et al.
Materials (2025) Vol. 18, Iss. 5, pp. 1057-1057
Open Access
Integrated machine learning and density functional theory to reveal the relationship between water contaminants and singlet oxygen via persulfate activation
Zhenjie Li, Jiachun Zhou, Weijie Huang, et al.
Applied Catalysis B Environment and Energy (2025), pp. 125322-125322
Closed Access
Exploring pollutant joint effects in disease through interpretable machine learning
Shuo Wang, Tianzhuo Zhang, Ziheng Li, et al.
Journal of Hazardous Materials (2024) Vol. 467, pp. 133707-133707
Closed Access | Times Cited: 3
Mapping global distributions of clay-size minerals via soil properties and machine learning techniques
Qinpeng Liao, Huangling Gu, Chongchong Qi, et al.
The Science of The Total Environment (2024) Vol. 949, pp. 174776-174776
Closed Access | Times Cited: 3
Concentration division for adsorption coefficient prediction using machine learning with Abraham descriptors: data-splitting approach comparison and critical factors identification
Zhenguo Qi, Shifa Zhong, Xin Huang, et al.
Carbon (2024) Vol. 230, pp. 119573-119573
Closed Access | Times Cited: 3
Decision tree-based approach to extrapolate life cycle inventory data of manufacturing processes
Mohamed Saad, Yingzhong Zhang, Jia Jia, et al.
Journal of Environmental Management (2024) Vol. 360, pp. 121152-121152
Closed Access | Times Cited: 2
Prediction of PFAS bioaccumulation in different plant tissues with machine learning models based on molecular fingerprints
Chenzhuo Song, Qian Gu, Dengke Zhang, et al.
The Science of The Total Environment (2024) Vol. 950, pp. 175091-175091
Closed Access | Times Cited: 2
Digital technologies for life cycle assessment: a review and integrated combination framework
Martin Popowicz, Nicolas J. Katzer, Moritz Kettele, et al.
The International Journal of Life Cycle Assessment (2024)
Open Access | Times Cited: 2
The need to integrate mass- and energy-based metrics with life cycle impacts for sustainable chemicals manufacture
Elysia Lucas, Antonio J. Martín, Sharon Mitchell, et al.
Green Chemistry (2024) Vol. 26, Iss. 17, pp. 9300-9309
Open Access | Times Cited: 2
A spiral infinite-life-cycle assessment model for measuring the environmental impacts of circular economy systems
Jinliang Xie, Xi Tian, Ming Xu, et al.
Environmental Impact Assessment Review (2024) Vol. 108, pp. 107605-107605
Closed Access | Times Cited: 1
Machine Learning-powered Pseudo-target Screening of Emerging Contaminants in Water: A Case Study on Tetracyclines
Ye Sun, WU Bao-li, Habit Dong, et al.
Water Research (2024), pp. 123039-123039
Closed Access | Times Cited: 1
End-to-end machine-learning for high-gravity ammonia stripping: Bridging the gap between scientific research and user-friendly applications
Shaomin Guo, Junwen Zhou, Zifu Li, et al.
Water Research (2023) Vol. 248, pp. 120790-120790
Closed Access | Times Cited: 3
Networking Chemicals Flows: Efficiency–Value–Environment Functionalized Symbiosis Algorithms and Application
Yizheng Lyu, Zhuoer Andrew Feng, Tianshu Ji, et al.
Environmental Science & Technology (2023) Vol. 57, Iss. 46, pp. 18225-18235
Closed Access | Times Cited: 3
Contribution of molecular structures and quantum chemistry technique to root concentration factor: An innovative application of interpretable machine learning
Tengyi Zhu, Yu Zhang, Yi Li, et al.
Journal of Hazardous Materials (2023) Vol. 459, pp. 132320-132320
Closed Access | Times Cited: 2
Experimental insights and modeling innovations: Deciphering Fe(VI) oxidation in imidazole ionic liquids through QSAR and RFR
Bei‐Bei Li, Ruijuan Qu, Ting Wang, et al.
Journal of Hazardous Materials (2024) Vol. 476, pp. 134980-134980
Closed Access
Machine Learning to support prospective Life Cycle Assessment of emerging chemical technologies
Carlos F. Blanco, N. Pauliks, François Donati, et al.
Current Opinion in Green and Sustainable Chemistry (2024) Vol. 50, pp. 100979-100979
Open Access
Prediction and detection of localised corrosion attack of stainless steel in biogas production: Machine Learning Classification Approach
M.J. Jiménez–Come, Francisco Javier González Gallero, Pascual Álvarez Gómez, et al.
Research Square (Research Square) (2023)
Open Access
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