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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:

Machine learning models for predicting biochar properties from lignocellulosic biomass torrefaction
Guangcan Su, Peng Jiang
Bioresource Technology (2024) Vol. 399, pp. 130519-130519
Closed Access | Times Cited: 12

Showing 12 citing articles:

Multi-output neural network model for predicting biochar yield and composition
Yifan Wang, Liang Xu, Jianen Li, et al.
The Science of The Total Environment (2024) Vol. 945, pp. 173942-173942
Closed Access | Times Cited: 4
Screening biomass by machine learning to construct Fe/Co loaded carbon for organic pollutants degradation via peroxymonosulfate activation
Baoying Wang, Huanyan Xu, Jingming Lan, et al.
Separation and Purification Technology (2025), pp. 131664-131664
Closed Access
Machine learning-driven predictive frameworks for optimizing chemical strategies in Microcystis aeruginosa mitigation
Zobia Khatoon, Suiliang Huang, Adeel Ahmed Abbasi
Journal of Water Process Engineering (2025) Vol. 71, pp. 107235-107235
Closed Access
Deterministic Models for Performance Analysis of Lignocellulosic Biomass Torrefaction
Abbas Azarpour, Sohrab Zendehboudi, Noori M. Cata Saady
ACS Omega (2025) Vol. 10, Iss. 7, pp. 6470-6501
Open Access
Machine learning modeling of thermally assisted biodrying process for municipal sludge
Kaiqiang Zhang, Ningfung Wang
Waste Management (2024) Vol. 188, pp. 95-106
Closed Access | Times Cited: 3
Critical insights into ensemble learning with decision trees for the prediction of biochar yield and higher heating value from pyrolysis of biomass
Saurav Kandpal, Ankita Tagade, Ashish N. Sawarkar
Bioresource Technology (2024) Vol. 411, pp. 131321-131321
Closed Access | Times Cited: 3
Machine Learning-Based Prediction of the Adsorption Characteristics of Biochar from Waste Wood by Chemical Activation
Jinman Chang, Jai-Young Lee
Materials (2024) Vol. 17, Iss. 21, pp. 5359-5359
Open Access | Times Cited: 2
Accelerated screening of active sites on biochar for catalysis and adsorption via multidimensional fingerprint factor descriptors
Wenjie Gao, Ning Li, Zhanjun Cheng, et al.
Bioresource Technology (2024) Vol. 408, pp. 131156-131156
Closed Access | Times Cited: 1
Using machine learning to predict biochar yield and carbon content: Enhancing efficiency and sustainability in biomass conversion
XU Qing-sheng, Long Du, Rui Deng
BioResources (2024) Vol. 19, Iss. 3, pp. 6545-6558
Open Access | Times Cited: 1
Simulation, prediction and optimization for synthesis and heavy metals adsorption of Schwertmannite by machine learning
Chouyuan Liang, Zhuo Zhang, Yuanyuan Li, et al.
Environmental Research (2024), pp. 120471-120471
Closed Access | Times Cited: 1
Co-pyrolysis of coal-derived sludge and low-rank coal: Thermal behaviour and char yield prediction
Tianli Zhang, Chenxu Zhang, Hai‐Peng Ren, et al.
Fuel Processing Technology (2024) Vol. 267, pp. 108165-108165
Closed Access | Times Cited: 1
Machine-learning-aided biochar production from aquatic biomass
Zhilong Yuan, Ye Wang, Lingfeng Zhu, et al.
Carbon Research (2024) Vol. 3, Iss. 1
Open Access
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