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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 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: 114

Showing 1-25 of 114 citing articles:

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: 130
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: 128
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: 116
Machine-learning-aided thermochemical treatment of biomass: a review
Hailong Li, Jiefeng Chen, Weijin Zhang, et al.
Biofuel Research Journal (2023) Vol. 10, Iss. 1, pp. 1786-1809
Open Access | Times Cited: 83
Machine learning for hydrothermal treatment of biomass: A review
Weijin Zhang, Qingyue Chen, Jiefeng Chen, et al.
Bioresource Technology (2022) Vol. 370, pp. 128547-128547
Closed Access | Times Cited: 80
A review of biomass pyrolysis gas: Forming mechanisms, influencing parameters, and product application upgrades
Yongnan Zhang, Yunyi Liang, Suiyi Li, et al.
Fuel (2023) Vol. 347, pp. 128461-128461
Closed Access | Times Cited: 80
Recent advances on industrial solid waste catalysts for improving the quality of bio-oil from biomass catalytic cracking: A review
Bingbing Qiu, Chen-Hao Yang, Qianni Shao, et al.
Fuel (2022) Vol. 315, pp. 123218-123218
Closed Access | Times Cited: 78
Machine learning to predict biochar and bio-oil yields from co-pyrolysis of biomass and plastics
Aessa Alabdrabalnabi, Ribhu Gautam, S. Mani Sarathy
Fuel (2022) Vol. 328, pp. 125303-125303
Closed Access | Times Cited: 72
Advances in machine learning technology for sustainable biofuel production systems in lignocellulosic biorefineries
Vishal Sharma, Mei‐Ling Tsai, Chiu‐Wen Chen, et al.
The Science of The Total Environment (2023) Vol. 886, pp. 163972-163972
Closed Access | Times Cited: 41
Recent advances and future prospects of thermochemical biofuel conversion processes with machine learning
Pil Rip Jeon, Jong-Ho Moon, Nafiu Olanrewaju Ogunsola, et al.
Chemical Engineering Journal (2023) Vol. 471, pp. 144503-144503
Open Access | Times Cited: 38
Utilizing support vector regression modeling to predict pyro product yields from microwave-assisted catalytic co-pyrolysis of biomass and waste plastics
Ramesh Potnuri, Chinta Sankar Rao, Dadi Venkata Surya, et al.
Energy Conversion and Management (2023) Vol. 292, pp. 117387-117387
Closed Access | Times Cited: 35
Emerging Photoreforming Process to Hydrogen Production: A Future Energy
Sandip Prabhakar Shelake, Dattatray Namdev Sutar, B. Moses Abraham, et al.
Advanced Functional Materials (2024) Vol. 34, Iss. 40
Closed Access | Times Cited: 17
Co-Pyrolysis of biomass and plastic waste: Process prediction and optimization based on Artificial Intelligence and response optimizer surrogate model
Yousaf Ayub, Jingzheng Ren
Process Safety and Environmental Protection (2024) Vol. 186, pp. 612-624
Closed Access | Times Cited: 12
Predicting co-pyrolysis of coal and biomass using machine learning approaches
Hao Wei, Kun Luo, Jiangkuan Xing, et al.
Fuel (2021) Vol. 310, pp. 122248-122248
Closed Access | Times Cited: 67
A comprehensive artificial neural network model for gasification process prediction
Simon Ascher, William Sloan, Ian Watson, et al.
Applied Energy (2022) Vol. 320, pp. 119289-119289
Open Access | Times Cited: 57
Machine learning prediction of pyrolytic products of lignocellulosic biomass based on physicochemical characteristics and pyrolysis conditions
Zixun Dong, Xiaopeng Bai, Daochun Xu, et al.
Bioresource Technology (2022) Vol. 367, pp. 128182-128182
Closed Access | Times Cited: 55
Machine learning prediction of the yield and oxygen content of bio-oil via biomass characteristics and pyrolysis conditions
Ke Yang, Kai Wu, Huiyan Zhang
Energy (2022) Vol. 254, pp. 124320-124320
Closed Access | Times Cited: 54
Machine learning and circular bioeconomy: Building new resource efficiency from diverse waste streams
To‐Hung Tsui, Mark C.M. van Loosdrecht, Yanjun Dai, et al.
Bioresource Technology (2022) Vol. 369, pp. 128445-128445
Open Access | Times Cited: 50
Artificial intelligence enabled efficient power generation and emissions reduction underpinning net-zero goal from the coal-based power plants
Waqar Muhammad Ashraf, Ghulam Moeen Uddin, Hassan Afroze Ahmad, et al.
Energy Conversion and Management (2022) Vol. 268, pp. 116025-116025
Open Access | Times Cited: 42
Comparison of machine learning methods for predicting the methane production from anaerobic digestion of lignocellulosic biomass
Zheng‐Xin Wang, Xinggan Peng, Ao Xia, et al.
Energy (2022) Vol. 263, pp. 125883-125883
Closed Access | Times Cited: 41
Exposing and understanding synergistic effects in co-pyrolysis of biomass and plastic waste via machine learning
Prapaporn Prasertpong, Thossaporn Onsree, Nattawut Khuenkaeo, et al.
Bioresource Technology (2022) Vol. 369, pp. 128419-128419
Closed Access | Times Cited: 41
A machine learning model to predict the pyrolytic kinetics of different types of feedstocks
Shule Wang, Ziyi Shi, Yanghao Jin, et al.
Energy Conversion and Management (2022) Vol. 260, pp. 115613-115613
Open Access | Times Cited: 40
Influence of Biomass Composition and Microwave Pyrolysis Conditions on Biochar Yield and its Properties: a Machine Learning Approach
Mari Selvam S., P. Balasubramanian
BioEnergy Research (2022) Vol. 16, Iss. 1, pp. 138-150
Closed Access | Times Cited: 38
Improving kitchen waste composting maturity by optimizing the processing parameters based on machine learning model
Shang Ding, Wuji Huang, Weijian Xu, et al.
Bioresource Technology (2022) Vol. 360, pp. 127606-127606
Closed Access | Times Cited: 37
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
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