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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.

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Showing 26-50 of 53 citing articles:

Molecular graph-based deep learning method for predicting multiple physical properties of alternative fuel components
Jinpeng Liu, Siyuan Gong, Hongwei Li, et al.
Fuel (2021) Vol. 313, pp. 122712-122712
Closed Access | Times Cited: 12
Prediction of Sooting Index of Fuel Compounds for Spark-Ignition Engine Applications Based on a Machine Learning Approach
Zhuo Chen, Florian vom Lehn, Heinz Pitsch, et al.
Journal of Thermal Science (2023) Vol. 32, Iss. 2, pp. 521-530
Closed Access | Times Cited: 4
On the Development of Descriptor-Based Machine Learning Models for Thermodynamic Properties: Part 1—From Data Collection to Model Construction: Understanding of the Methods and Their Effects
Cindy Trinh, Youssef Tbatou, Silvia Lasala, et al.
Processes (2023) Vol. 11, Iss. 12, pp. 3325-3325
Open Access | Times Cited: 4
Machine Learning for Ionization Potentials and Photoionization Cross Sections of Volatile Organic Compounds
Matthew Stewart, Scot T. Martin
ACS Earth and Space Chemistry (2023) Vol. 7, Iss. 4, pp. 863-875
Open Access | Times Cited: 3
Predicting sulfanilamide solubility in mixed solvents: A comparative analysis of computational models
Prashanth Asadi, Kalyani Kodide, Jyothi Thati, et al.
Fluid Phase Equilibria (2023) Vol. 577, pp. 113966-113966
Closed Access | Times Cited: 3
Low-viscosity oligoether esters (OEEs) as high-efficiency lubricating oils: Insight on their structure–lubricity relationship
Hanwen Wang, Ying Wang, Ping Wen, et al.
Friction (2023) Vol. 12, Iss. 6, pp. 1133-1153
Open Access | Times Cited: 3
A novel AI-based combustion diagnostic technology for the identification of chemical source information via flame images: Fuel type and reaction condition
Mingfei Chen, Z. Zou, Kaile Zhou, et al.
Combustion and Flame (2023) Vol. 260, pp. 113208-113208
Closed Access | Times Cited: 2
Design Green Chemicals by Predicting Vaporization Properties Using Explainable Graph Attention Networks
Yeonjoon Kim, Jae‐Young Cho, Hojin Jung, et al.
Green Chemistry (2024) Vol. 26, Iss. 19, pp. 10247-10264
Open Access
Explainable machine learning assisted design of tailor-made fuels using conjoint fingerprints
Yong Chen, Zhiyuan Lu, Zhifeng Yao, et al.
Energy Conversion and Management (2024) Vol. 322, pp. 119118-119118
Closed Access
Machine Learning for Predicting and Optimizing Physicochemical Properties of Deep Eutectic Solvents: Review and Perspectives
Francisco Javier López-Flores, César Ramírez‐Márquez, J. Betzabe González‐Campos, et al.
Industrial & Engineering Chemistry Research (2024)
Closed Access
Liquid synthetic fuels design guided by chemical structure: A machine learning perspective
Rodolfo S. M. Freitas, Cheng Chen, Xi Jiang
(2024)
Open Access
The Estimation of Latent Heat and Vapor Pressure of Ethanol–Gasoline Blends Using Machine Learning and Thermodynamic Relations
Manan Bansal, Rajneesh Kashyap, Kaushik Saha
Springer proceedings in energy (2024), pp. 391-407
Closed Access
Advancing Sustainable Aviation Fuel Design: Machine Learning for High Energy Density Liquid Polycyclic Hydrocarbons
Dilip Rijal, V. V. Vasilyev, Feng Wang
(2024)
Closed Access
Property prediction of fuel mixtures using pooled graph neural networks
Roel J. Leenhouts, Tara Larsson, Sebastian Verhelst, et al.
Fuel (2024) Vol. 381, pp. 133218-133218
Closed Access
Pushing the boundaries for fuel discovery with a multiview features fusion approach
Dehai Zhang, Di Zhao, Jiashu Liang, et al.
Energy Science & Engineering (2024) Vol. 12, Iss. 11, pp. 4860-4875
Open Access
State-of-the-art review on various applications of machine learning techniques in materials science and engineering
Bing Yu, Lai‐Chang Zhang, Xiaoxia Ye, et al.
Chemical Engineering Science (2024), pp. 121147-121147
Closed Access
General estimation method for lower flammability limits of organic compounds: The simpler the better
Mathilda Maury, Didier Mathieu, Johan Jacquemin
Fuel (2023) Vol. 342, pp. 127753-127753
Closed Access | Times Cited: 1
Experimental and modeling study of the oxidation of fenchone, a high-energy density fuel-additive
L. Boualem, Zeynep Serinyel, André Nicolle, et al.
Fuel (2023) Vol. 353, pp. 129183-129183
Open Access | Times Cited: 1
A modified group contribution method for estimating thermodynamic parameters of methanol-to-olefins over a SAPO-34 catalyst
Junyi Yu, Hua Li, Mao Ye, et al.
Physical Chemistry Chemical Physics (2023) Vol. 25, Iss. 32, pp. 21631-21639
Closed Access | Times Cited: 1
Predicting pKa of the carboxylic acid group in water solutions of amino acids based on molecular structures using machine learning QSPR methods
Ali Fazeli, Mojtaba Karimzadeh
Materials Today Communications (2023) Vol. 37, pp. 107554-107554
Closed Access | Times Cited: 1
Designing high-performance fuels through graph neural networks for predicting cetane number of multicomponent surrogate mixtures
Yeonjoon Kim, Sabari Kumar, Jaeyoung Cho, et al.
SAE technical papers on CD-ROM/SAE technical paper series (2023)
Closed Access | Times Cited: 1
State of the Art and of Outlook of Data Science and Machine Learning in Organic Chemistry
Ricardo Stefani
(2023)
Open Access
State of the Art and of Outlook of Data Science and Machine Learning in Organic Chemistry
Ricardo Stefani
(2023)
Open Access
Design Green Chemicals by Predicting Vaporization Properties Using Explainable Graph Attention Networks
Yeonjoon Kim, Jaeyoung Cho, Hojin Jung, et al.
(2023)
Open Access
Predicting Pka of the Carboxylic Acid Group in Water Solutions of Amino Acids Based on Molecular Structures Using Machine Learning Qspr Methods
Ali Fazeli, Mojtaba Karimzadeh
(2023)
Closed Access

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