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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:

Applied Machine Learning for Prediction of CO2 Adsorption on Biomass Waste-Derived Porous Carbons
Xiangzhou Yuan, Manu Suvarna, S.M. Low, et al.
Environmental Science & Technology (2021) Vol. 55, Iss. 17, pp. 11925-11936
Open Access | Times Cited: 239

Showing 1-25 of 239 citing articles:

Prediction of Soil Heavy Metal Immobilization by Biochar Using Machine Learning
Kumuduni Niroshika Palansooriya, Jie Li, Pavani Dulanja Dissanayake, et al.
Environmental Science & Technology (2022) Vol. 56, Iss. 7, pp. 4187-4198
Open Access | Times Cited: 290
Artificial intelligence for waste management in smart cities: a review
Bingbing Fang, Jiacheng Yu, Zhonghao Chen, et al.
Environmental Chemistry Letters (2023) Vol. 21, Iss. 4, pp. 1959-1989
Open Access | Times Cited: 210
Critical impacts of pyrolysis conditions and activation methods on application-oriented production of wood waste-derived biochar
Mingjing He, Zibo Xu, Yuqing Sun, et al.
Bioresource Technology (2021) Vol. 341, pp. 125811-125811
Closed Access | Times Cited: 177
Functional Carbon from Nature: Biomass‐Derived Carbon Materials and the Recent Progress of Their Applications
Hongzhe He, Ruoqun Zhang, Pengcheng Zhang, et al.
Advanced Science (2023) Vol. 10, Iss. 16
Open Access | Times Cited: 168
Impact of Surface Functional Groups and Their Introduction Methods on the Mechanisms of CO2 Adsorption on Porous Carbonaceous Adsorbents
Ben Petrovic, Mikhail Gorbounov, Salman Masoudi Soltani
Carbon Capture Science & Technology (2022) Vol. 3, pp. 100045-100045
Open Access | Times Cited: 116
Recent advancements and challenges in emerging applications of biochar-based catalysts
Xiangzhou Yuan, Yang Cao, Jie Li, et al.
Biotechnology Advances (2023) Vol. 67, pp. 108181-108181
Open Access | Times Cited: 100
A generalized machine learning framework to predict the space-time yield of methanol from thermocatalytic CO2 hydrogenation
Manu Suvarna, Thaylan Pinheiro Araújo, Javier Pérez‐Ramírez
Applied Catalysis B Environment and Energy (2022) Vol. 315, pp. 121530-121530
Open Access | Times Cited: 93
Nitrogen-doped porous carbons from polyacrylonitrile fiber as effective CO2 adsorbents
Changdan Ma, Jiali Bai, Xin Hu, et al.
Journal of Environmental Sciences (2022) Vol. 125, pp. 533-543
Closed Access | Times Cited: 88
Enhancing Biochar-Based Nonradical Persulfate Activation Using Data-Driven Techniques
Rupeng Wang, Shiyu Zhang, Honglin Chen, et al.
Environmental Science & Technology (2023) Vol. 57, Iss. 9, pp. 4050-4059
Closed Access | Times Cited: 87
Sustainability-inspired upcycling of waste polyethylene terephthalate plastic into porous carbon for CO2 capture
Xiangzhou Yuan, Nallapaneni Manoj Kumar, Boris Brigljević, et al.
Green Chemistry (2022) Vol. 24, Iss. 4, pp. 1494-1504
Open Access | Times Cited: 85
Modeling phytoremediation of heavy metal contaminated soils through machine learning
Liang Shi, Jie Li, Kumuduni Niroshika Palansooriya, et al.
Journal of Hazardous Materials (2022) Vol. 441, pp. 129904-129904
Closed Access | Times Cited: 77
Machine learning predicting and engineering the yield, N content, and specific surface area of biochar derived from pyrolysis of biomass
Lijian Leng, Lihong Yang, Xinni Lei, et al.
Biochar (2022) Vol. 4, Iss. 1
Open Access | Times Cited: 75
Machine learning assisted predicting and engineering specific surface area and total pore volume of biochar
Hailong Li, Zejian Ai, Lihong Yang, et al.
Bioresource Technology (2022) Vol. 369, pp. 128417-128417
Closed Access | Times Cited: 75
Understanding and optimizing the gasification of biomass waste with machine learning
Jie Li, Lanyu Li, Yen Wah Tong, et al.
Green Chemical Engineering (2022) Vol. 4, Iss. 1, pp. 123-133
Open Access | Times Cited: 74
Preparation of renewable porous carbons for CO2 capture – A review
Yafei Shen
Fuel Processing Technology (2022) Vol. 236, pp. 107437-107437
Closed Access | Times Cited: 70
AI for Nanomaterials Development in Clean Energy and Carbon Capture, Utilization and Storage (CCUS)
Honghao Chen, Yingzhe Zheng, Jiali Li, et al.
ACS Nano (2023) Vol. 17, Iss. 11, pp. 9763-9792
Closed Access | Times Cited: 45
Prediction of Photochemical Properties of Dissolved Organic Matter Using Machine Learning
Zhiyang Liao, Jinrong Lu, Kunting Xie, et al.
Environmental Science & Technology (2023) Vol. 57, Iss. 46, pp. 17971-17980
Closed Access | Times Cited: 43
Feature engineering for improved machine-learning-aided studying heavy metal adsorption on biochar
Tian Shen, Haoyi Peng, Xingzhong Yuan, et al.
Journal of Hazardous Materials (2024) Vol. 466, pp. 133442-133442
Closed Access | Times Cited: 33
Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities
Eslam G. Al-Sakkari, Ahmed Ragab, Hanane Dagdougui, et al.
The Science of The Total Environment (2024) Vol. 917, pp. 170085-170085
Closed Access | Times Cited: 32
Artificial intelligence-based prediction of hydrogen adsorption in various kerogen types: Implications for underground hydrogen storage and cleaner production
Hung Vo Thanh, Zhenxue Dai, Zhengyang Du, et al.
International Journal of Hydrogen Energy (2024) Vol. 57, pp. 1000-1009
Closed Access | Times Cited: 26
Liquid Phase Exfoliation of 2D Materials and Its Electrochemical Applications in the Data-Driven Future
Panwad Chavalekvirat, Wisit Hirunpinyopas, Krittapong Deshsorn, et al.
Precision Chemistry (2024) Vol. 2, Iss. 7, pp. 300-329
Open Access | Times Cited: 25
Machine-learning-aided prediction and engineering of nitrogen-containing functional groups of biochar derived from biomass pyrolysis
Lijian Leng, Xinni Lei, Naif Abdullah Al‐Dhabi, et al.
Chemical Engineering Journal (2024) Vol. 485, pp. 149862-149862
Closed Access | Times Cited: 24
One-pot synthesis of biomass-derived porous carbons for multipurpose energy applications
Yafei Shen, Yupeng Zhu
Journal of Materials Chemistry A (2024) Vol. 12, Iss. 11, pp. 6211-6242
Closed Access | Times Cited: 20
Machine learning modeling of fluorescence spectral data for prediction of trace organic contaminant removal during UV/H2O2 treatment of wastewater
Yi Yang, Chao Shan, Bingcai Pan
Water Research (2024) Vol. 255, pp. 121484-121484
Closed Access | Times Cited: 19
Active Learning-Based Guided Synthesis of Engineered Biochar for CO2 Capture
Xiangzhou Yuan, Manu Suvarna, Juin Yau Lim, et al.
Environmental Science & Technology (2024) Vol. 58, Iss. 15, pp. 6628-6636
Open Access | Times Cited: 18
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