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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 prediction of biochar yield and carbon contents in biochar based on biomass characteristics and pyrolysis conditions
Xinzhe Zhu, Yinan Li, Xiaonan Wang
Bioresource Technology (2019) Vol. 288, pp. 121527-121527
Closed Access | Times Cited: 334

Showing 1-25 of 334 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: 302
New trends in biochar pyrolysis and modification strategies: feedstock, pyrolysis conditions, sustainability concerns and implications for soil amendment
Liuwei Wang, Yong Sik Ok, Daniel C.W. Tsang, et al.
Soil Use and Management (2020) Vol. 36, Iss. 3, pp. 358-386
Open Access | Times Cited: 298
Application of machine learning methods for the prediction of organic solid waste treatment and recycling processes: A review
Haonan Guo, Shubiao Wu, Yingjie Tian, et al.
Bioresource Technology (2020) Vol. 319, pp. 124114-124114
Closed Access | Times Cited: 292
Machine Learning in Environmental Research: Common Pitfalls and Best Practices
Jun‐Jie Zhu, Meiqi Yang, Zhiyong Jason Ren
Environmental Science & Technology (2023) Vol. 57, Iss. 46, pp. 17671-17689
Closed Access | Times Cited: 250
Fuel properties of hydrochar and pyrochar: Prediction and exploration with machine learning
Jie Li, Lanjia Pan, Manu Suvarna, et al.
Applied Energy (2020) Vol. 269, pp. 115166-115166
Closed Access | Times Cited: 213
Machine learning for the selection of carbon-based materials for tetracycline and sulfamethoxazole adsorption
Xinzhe Zhu, Zhonghao Wan, Daniel C.W. Tsang, et al.
Chemical Engineering Journal (2020) Vol. 406, pp. 126782-126782
Closed Access | Times Cited: 200
Machine learning methods for modelling the gasification and pyrolysis of biomass and waste
Simon Ascher, Ian Watson, Siming You
Renewable and Sustainable Energy Reviews (2021) Vol. 155, pp. 111902-111902
Open Access | Times Cited: 182
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: 178
Predicting algal biochar yield using eXtreme Gradient Boosting (XGB) algorithm of machine learning methods
Abhijeet Pathy, Saswat Meher, P. Balasubramanian
Algal Research (2020) Vol. 50, pp. 102006-102006
Closed Access | Times Cited: 175
Insights into the adsorption of pharmaceuticals and personal care products (PPCPs) on biochar and activated carbon with the aid of machine learning
Xinzhe Zhu, Mingjing He, Yuqing Sun, et al.
Journal of Hazardous Materials (2021) Vol. 423, pp. 127060-127060
Closed Access | Times Cited: 160
Multi-task prediction and optimization of hydrochar properties from high-moisture municipal solid waste: Application of machine learning on waste-to-resource
Jie Li, Xinzhe Zhu, Yinan Li, et al.
Journal of Cleaner Production (2020) Vol. 278, pp. 123928-123928
Open Access | Times Cited: 152
Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and Reactors
Li‐Tao Zhu, Xizhong Chen, Bo Ouyang, et al.
Industrial & Engineering Chemistry Research (2022) Vol. 61, Iss. 28, pp. 9901-9949
Open Access | Times Cited: 151
Applications of machine learning in thermochemical conversion of biomass-A review
Muzammil Khan, Salman Raza Naqvi, Zahid Ullah, et al.
Fuel (2022) Vol. 332, pp. 126055-126055
Closed Access | Times Cited: 144
Life-cycle assessment of pyrolysis processes for sustainable production of biochar from agro-residues
Xiefei Zhu, Claudia Labianca, Mingjing He, et al.
Bioresource Technology (2022) Vol. 360, pp. 127601-127601
Open Access | Times Cited: 142
A comprehensive review of biochar in removal of organic pollutants from wastewater: Characterization, toxicity, activation/functionalization and influencing treatment factors
Hicham Zeghioud, Lydia Fryda, Hayet Djelal, et al.
Journal of Water Process Engineering (2022) Vol. 47, pp. 102801-102801
Open Access | Times Cited: 141
A complete review on biochar: Production, property, multifaceted applications, interaction mechanism and computational approach
K. Jeyasubramanian, B. Thangagiri, A. Sakthivel, et al.
Fuel (2021) Vol. 292, pp. 120243-120243
Closed Access | Times Cited: 137
Machine learning aided supercritical water gasification for H2-rich syngas production with process optimization and catalyst screening
Jie Li, Lanjia Pan, Manu Suvarna, et al.
Chemical Engineering Journal (2021) Vol. 426, pp. 131285-131285
Open Access | Times Cited: 132
Machine learning prediction of pyrolytic gas yield and compositions with feature reduction methods: Effects of pyrolysis conditions and biomass characteristics
Qinghui Tang, Yingquan Chen, Haiping Yang, et al.
Bioresource Technology (2021) Vol. 339, pp. 125581-125581
Closed Access | Times Cited: 132
Machine learning prediction and optimization of bio-oil production from hydrothermal liquefaction of algae
Weijin Zhang, Jie Li, Tonggui Liu, et al.
Bioresource Technology (2021) Vol. 342, pp. 126011-126011
Closed Access | Times Cited: 130
The role of machine learning to boost the bioenergy and biofuels conversion
Zheng‐Xin Wang, Xinggan Peng, Ao Xia, et al.
Bioresource Technology (2021) Vol. 343, pp. 126099-126099
Closed Access | Times Cited: 130
Straw and wood based biochar for CO2 capture: Adsorption performance and governing mechanisms
Lingyu Cao, Xueyang Zhang, Yue Xu, et al.
Separation and Purification Technology (2022) Vol. 287, pp. 120592-120592
Closed Access | Times Cited: 128
Interpretable machine learning for predicting and evaluating hydrogen production via supercritical water gasification of biomass
Sheng Zhao, Jian Li, Chao Chen, et al.
Journal of Cleaner Production (2021) Vol. 316, pp. 128244-128244
Closed Access | Times Cited: 117
Applications of artificial intelligence‐based modeling for bioenergy systems: A review
Mochen Liao, Yuan Yao
GCB Bioenergy (2021) Vol. 13, Iss. 5, pp. 774-802
Open Access | Times Cited: 112
Machine learning prediction of biocrude yields and higher heating values from hydrothermal liquefaction of wet biomass and wastes
Tossapon Katongtung, Thossaporn Onsree, Nakorn Tippayawong
Bioresource Technology (2021) Vol. 344, pp. 126278-126278
Closed Access | Times Cited: 111
Review of biochar production via crop residue pyrolysis: Development and perspectives
Yize Li, Rohit Gupta, Qiaozhi Zhang, et al.
Bioresource Technology (2022) Vol. 369, pp. 128423-128423
Open Access | Times Cited: 109
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