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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:

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

Showing 1-25 of 33 citing articles:

A complete review on the oxygen-containing functional groups of biochar: Formation mechanisms, detection methods, engineering, and applications
Jiefeng Chen, Junhui Zhou, Weitao Zheng, et al.
The Science of The Total Environment (2024) Vol. 946, pp. 174081-174081
Closed Access | Times Cited: 31
Machine learning-driven prediction of phosphorus removal performance of metal-modified biochar and optimization of preparation processes considering water quality management objectives
Weilin Fu, Menghan Feng, Changbin Guo, et al.
Bioresource Technology (2024) Vol. 403, pp. 130861-130861
Closed Access | Times Cited: 17
Engineering biochar from biomass pyrolysis for effective adsorption of heavy metal: An innovative machine learning approach
Lijian Leng, Huihui Zheng, Tian Shen, et al.
Separation and Purification Technology (2025), pp. 131592-131592
Closed Access | Times Cited: 2
Enhanced imidacloprid adsorption using boron-modified biochar: Insights into molecular mechanisms and environmental stability
Zhengming Yang, Zhuochao Wang, Khantaphong Charoenkal, et al.
Chemical Engineering Journal (2025), pp. 159729-159729
Closed Access | Times Cited: 2
Machine learning prediction of biochar physicochemical properties based on biomass characteristics and pyrolysis conditions
Yuanbo Song, Zipeng Huang, Mengyu Jin, et al.
Journal of Analytical and Applied Pyrolysis (2024) Vol. 181, pp. 106596-106596
Closed Access | Times Cited: 13
Machine learning prediction of dye adsorption by hydrochar: Parameter optimization and experimental validation
Chong Liu, P. Balasubramanian, Fayong Li, et al.
Journal of Hazardous Materials (2024) Vol. 480, pp. 135853-135853
Closed Access | Times Cited: 11
Tourmaline/ZnAL-LDH nanocomposite based photocatalytic system for efficient degradation of mixed pollutant wastewater
Jiangfu Zheng, Changzheng Fan, Xiaoming Li, et al.
Separation and Purification Technology (2024) Vol. 345, pp. 127306-127306
Closed Access | Times Cited: 8
Machine learning-based exploration of biochar for environmental management and remediation
Burcu Oral, Ahmet Coşgun, M. Erdem Günay, et al.
Journal of Environmental Management (2024) Vol. 360, pp. 121162-121162
Closed Access | Times Cited: 8
Amorphous-dominated MgO hollow spheres enhanced fluoride adsorption: Mechanism analysis and machine learning prediction
Lin Fan, Dexi Wang, Honglei Yu, et al.
The Journal of Chemical Physics (2025) Vol. 162, Iss. 1
Closed Access | Times Cited: 1
Simultaneous Mitigation of Cadmium Contamination and Greenhouse Gas Emissions in Paddy Soil by Iron-Modified Biochar
Xin Wang, Tong Zou, Jiapan Lian, et al.
Journal of Hazardous Materials (2025) Vol. 488, pp. 137430-137430
Closed Access | Times Cited: 1
MgO-embedded S-doped porous biochar composites for efficient removal Cd(II) and Pb(II) in water: DFT studies and mechanistic insights
Phạm Văn Hảo, Haichao Fu, Shuanglong Ma, et al.
Separation and Purification Technology (2025), pp. 132079-132079
Closed Access | Times Cited: 1
Machine learning-driven prediction of phosphorus adsorption capacity of biochar: Insights for adsorbent design and process optimization
Huafei Lyu, Ziming Xu, Jian Zhong, et al.
Journal of Environmental Management (2024) Vol. 369, pp. 122405-122405
Closed Access | Times Cited: 6
Two-step machine learning-aided two-stage hydrothermal liquefaction of biomass for bio-oil upgrading to lower nitrogen content: Experimental verification and parameter optimization
Tonggui Liu, Donghai Xu, Ming-xin Xu, et al.
Journal of Cleaner Production (2024), pp. 143808-143808
Closed Access | Times Cited: 5
Machine learning accelerated catalysts design for CO reduction: An interpretability and transferability analysis
Yuhang Wang, Yaqin Zhang, Ninggui Ma, et al.
Journal of Material Science and Technology (2024) Vol. 213, pp. 14-23
Closed Access | Times Cited: 4
Application of Machine Learning to Predict the Fluoride Removal Capability of MgO
Lin Fan, Dexi Wang, Honglei Yu, et al.
Journal of environmental chemical engineering (2025) Vol. 13, Iss. 1, pp. 115317-115317
Closed Access
Machine learning-aided biochar design for the adsorptive removal of emerging inorganic pollutants in water
Habib Ullah, Sangar Khan, Xiaoying Zhu, et al.
Separation and Purification Technology (2025), pp. 131421-131421
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
Aluminum ion catalyzed proton transfer: Mechanism on promoting highly stable passivation of Cr by soil organic matter
Gaoyuan Gu, Jianing Zhang, Yan Zhou, et al.
The Science of The Total Environment (2025) Vol. 966, pp. 178760-178760
Closed Access
Machine learning-aided model for predicting oily sludge pyrolysis under various feedstock and operating conditions
Cheng Lu, Dixuan Li, Beidou Xi, et al.
Journal of Hazardous Materials (2025), pp. 137654-137654
Open Access
Addressing Data Handling Shortcomings in Machine Learning Studies on Biochar for Heavy Metal Remediation
Destika Cahyana, Hak Sun Jang
Journal of Hazardous Materials (2025) Vol. 491, pp. 137887-137887
Closed Access
Machine learning predicts selectivity of green synthesized iron nanoparticles toward typical contaminants: critical factors in synthesis conditions, material properties, and reaction process
Yiwen Xiao, Zhenjun Zhang, Jiajiang Lin, et al.
Environmental Research (2025) Vol. 277, pp. 121605-121605
Closed Access
A critical review on green synthesis and modification techniques of biochar: Comparison of efficacies towards adsorption capacities
Prasenjit Choudhury, Mriganka Sekhar Manna, Soma Nag
Biomass and Bioenergy (2025) Vol. 198, pp. 107859-107859
Closed Access
Leveraging big data to elucidate the impact of heavy metal nanoparticles on anammox processes in wastewater treatment
Yanbin Hong, Zhenguo Chen, Zehua Huang, et al.
Journal of Environmental Management (2025) Vol. 382, pp. 125243-125243
Closed Access
Evaluation of machine learning models for accurate prediction of heavy metals in coal mining region soils in Bangladesh
Ram Proshad, Krishno Chandra, Maksudul Islam, et al.
Environmental Geochemistry and Health (2025) Vol. 47, Iss. 5
Closed Access
Machine learning prediction of biochar properties derived from food waste
Ekaterina Kravchenko, Tatiana Minkina, D. A. Privizentseva, et al.
Journal of environmental chemical engineering (2025), pp. 116791-116791
Closed Access
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