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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.

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Showing 1-25 of 36 citing articles:

Prediction and optimization model of sustainable concrete properties using machine learning, deep learning and swarm intelligence: A review
Shiqi Wang, Peng Xia, Keyu Chen, et al.
Journal of Building Engineering (2023) Vol. 80, pp. 108065-108065
Closed Access | Times Cited: 49
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: 14
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: 13
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: 34
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: 31
Biochar production and its environmental applications: Recent developments and machine learning insights
Kolli Venkata Supraja, Himanshu Kachroo, Gayatri Viswanathan, et al.
Bioresource Technology (2023) Vol. 387, pp. 129634-129634
Closed Access | Times Cited: 20
Machine learning–assisted prediction of engineered carbon systems’ capacity to treat textile dyeing wastewater via adsorption technology
Om Kulkarni, Priya Dongare, Bhavana Shanmughan, et al.
Environmental Monitoring and Assessment (2025) Vol. 197, Iss. 2
Closed Access
Application of machine learning for environmentally friendly advancement: exploring biomass-derived materials in wastewater treatment and agricultural sector − a review
Banza Jean Claude, Linda L. Sibali
Journal of Environmental Science and Health Part A (2025), pp. 1-16
Open Access
Recent studies on the comprehensive application of biochar in multiple environmental fields
Yunsong Liu, Zonglin Weng, Bin Han, et al.
Journal of Cleaner Production (2023) Vol. 421, pp. 138495-138495
Closed Access | Times Cited: 17
Social welfare and equality equilibrium based carbon tax subsidy incentive approach for biomass-coal co-firing towards carbon emissions
Shiyu Yan, Chengwei Lv, Liming Yao
Energy (2024) Vol. 291, pp. 130282-130282
Closed Access | Times Cited: 4
Multi-performance optimization of low-carbon geopolymer considering mechanical, cost, and CO2 emission based on experiment and interpretable learning
Shiqi Wang, Keyu Chen, Jinlong Liu, et al.
Construction and Building Materials (2024) Vol. 425, pp. 136013-136013
Closed Access | Times Cited: 4
Chemocatalytic production of sorbitol from cellulose via sustainable chemistry – a tutorial review
Yingqiao Zhou, Richard L. Smith, Xinhua Qi
Green Chemistry (2023) Vol. 26, Iss. 1, pp. 202-243
Closed Access | Times Cited: 12
Optimization-driven modelling of hydrochar derived from fruit waste for adsorption performance evaluation using response surface methodology and machine learning
Fathimath Afrah Solih, Archina Buthiyappan, Khairunnisa Hasikin‬, et al.
Journal of Industrial and Engineering Chemistry (2024)
Closed Access | Times Cited: 3
Toward sustainable crop residue management: A deep ensemble learning approach
Syeda Nyma Ferdous, Xin Li, Kamalakanta Sahoo, et al.
Bioresource Technology Reports (2023) Vol. 22, pp. 101421-101421
Open Access | Times Cited: 8
Improving prediction of N2O emissions during composting using model-agnostic meta-learning
Shuai Shi, Jiaxin Bao, Zhiheng Guo, et al.
The Science of The Total Environment (2024) Vol. 922, pp. 171357-171357
Closed Access | Times Cited: 2
Long Short-Term Memory and Bidirectional Long Short-Term Memory Modeling and Prediction of Hexavalent and Total Chromium Removal Capacity Kinetics of Cupressus lusitanica Bark
Juan C. Cruz-Victoria, Alma Rosa Netzahuatl-Muñoz, Eliseo Cristiani‐Urbina
Sustainability (2024) Vol. 16, Iss. 7, pp. 2874-2874
Open Access | Times Cited: 2
Model Forecasting of Hydrogen Yield and Lower Heating Value in Waste Mahua Wood Gasification with Machine Learning
Prabhu Paramasivam, Mansoor Alruqi, H. A. Hanafi, et al.
International Journal of Energy Research (2024) Vol. 2024, Iss. 1
Open Access | Times Cited: 2
Sustainability assessment of the agriculture sector using best worst method: Case study of Baltic states
Justas Štreimikis, Ahmad Bathaei, Dalia Štreimikienė
Sustainable Development (2024) Vol. 32, Iss. 5, pp. 5611-5626
Closed Access | Times Cited: 1
Machine Learning for Environmental Sustainability
Syeda Nyma Ferdous
(2024)
Open Access | Times Cited: 1
Unlocking renewable energy potential: Harnessing machine learning and intelligent algorithms
Thanh Tuan Le, Prabhu Paramasivam, Elvis Adril, et al.
International Journal of Renewable Energy Development (2024) Vol. 13, Iss. 4, pp. 783-813
Open Access | Times Cited: 1
Machine learning applications in forest and biomass supply chain management: a review
Jinghan Zhao, Jingxin Wang, Nathaniel Anderson
International Journal of Forest Engineering (2024) Vol. 35, Iss. 3, pp. 371-380
Closed Access | Times Cited: 1
Harnessing Biomass Energy: Advancements through Machine Learning and AI Applications for Sustainability and Efficiency
B. Deepanraj, Prabhakar Sharma, Bhaskor Jyoti Bora, et al.
Process Safety and Environmental Protection (2024) Vol. 191, pp. 193-205
Closed Access | Times Cited: 1
Development of a Residual Biomass Supply Chain Simulation Model Using AnyLogistix: A Methodical Approach
Bernardine Chigozie Chidozie, Ana Luísa Ramos, José Vasconcelos Ferreira, et al.
Logistics (2024) Vol. 8, Iss. 4, pp. 107-107
Open Access | Times Cited: 1
A systematic review of current AI techniques used in the context of the SDGs
Lucas Greif, Fabian Röckel, Andreas Kimmig, et al.
International Journal of Environmental Research (2024) Vol. 19, Iss. 1
Open Access | Times Cited: 1
Hydrothermal bio-oil yield and higher heating value of high moisture and lipid biomass: Machine Learning modeling and feature response behavior analysis
Xiangjie Liu, Xin Zhang, Khantaphong Charoenkal, et al.
Journal of the Energy Institute (2024), pp. 101859-101859
Closed Access | Times Cited: 1
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