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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:

Predicting physical properties of oxygenated gasoline and diesel range fuels using machine learning
Hussain A. AlNazr, Nabeel Ahmad, Usama Ahmed, et al.
Alexandria Engineering Journal (2023) Vol. 76, pp. 193-219
Open Access | Times Cited: 15

Showing 15 citing articles:

Prediction of combustion, performance, and emission parameters of ethanol powered spark ignition engine using ensemble Least Squares boosting machine learning algorithms
D. Jesu Godwin, Edwin Geo Varuvel, Leenus Jesu Martin
Journal of Cleaner Production (2023) Vol. 421, pp. 138401-138401
Closed Access | Times Cited: 31
Chemical SuperLearner (ChemSL) - An automated machine learning framework for building physical and chemical properties model
Balaji Mohan, Junseok Chang
Chemical Engineering Science (2024) Vol. 294, pp. 120111-120111
Closed Access | Times Cited: 5
A Case Study on Integrating an AI System into the Fuel Blending Process in a Chemical Refinery
Abdul Gani Abdul Jameel
ChemEngineering (2025) Vol. 9, Iss. 1, pp. 4-4
Open Access
Advancing Sustainable Aviation Fuel Design: Machine Learning for High-Energy-Density Liquid Polycyclic Hydrocarbons
Dilip Rijal, Vladislav Vasilyev, Feng Wang
Energy & Fuels (2025)
Closed Access
Comprehensive accurate prediction of critical jet fuel properties with multiple machine learning models
Yitong Shao, Mengxian Yu, Mengchao Zhao, et al.
Chemical Engineering Science (2024), pp. 121018-121018
Closed Access | Times Cited: 3
Artificial intelligence for novel fuel design
S. Mani Sarathy, Basem A. Eraqi
Proceedings of the Combustion Institute (2024) Vol. 40, Iss. 1-4, pp. 105630-105630
Closed Access | Times Cited: 2
Advancing CO2 Solubility Prediction in Brine Solutions with Explainable Artificial Intelligence for Sustainable Subsurface Storage
Amin Shokrollahi, Afshin Tatar, Abbas Zeinijahromi
Sustainability (2024) Vol. 16, Iss. 17, pp. 7273-7273
Open Access | Times Cited: 2
Molecular Profile, Fuel Properties, Engine Performance and Emission Characteristics of Gasoline-Like Fuel Produced Via Cracking of Used Engine Oil Using Na-Fe3O4/HZSM-5 Catalyst
Yaquba M. Sahabi, Abdullahi Muhammad Sokoto, Misbahu Ladan Mohammed, et al.
Caliphate Journal of Science and Technology (2024) Vol. 6, Iss. 1, pp. 93-102
Open Access | Times Cited: 1
Machine learning of weighted superposition attraction algorithm for optimization diesel engine performance and emission fueled with butanol-diesel biofuel
Ibham Veza, Aslan Deniz Karaoğlan, Şener Akpınar, et al.
Ain Shams Engineering Journal (2024), pp. 103126-103126
Open Access | Times Cited: 1
Fuel type recognition of ester isomer additives in flames by optical diagnostics coupled with machine learning method
J.-W. He, MengFei Chen, Bingkun Wu, et al.
Science China Technological Sciences (2024) Vol. 67, Iss. 11, pp. 3431-3442
Closed Access | Times Cited: 1
Synthesis of 1-Hexanol/Hexyl hexanoate Mixtures from Grape Pomace: Insights on Diesel Engine Performances at High Bio-Blendstock Loadings
Stefano Frigo, Anna Maria Raspolli Galletti, Sara Fulignati, et al.
Energies (2023) Vol. 16, Iss. 19, pp. 6789-6789
Open Access | Times Cited: 2
A machine learning approach for optimizing the water-energy-food-ecosystem nexus: a resilience perspective for sustainability
Francisco Javier López-Flores, Xaté Geraldine Sánchez-Zarco, Eusiel Rubio‐Castro, et al.
Environment Development and Sustainability (2023)
Closed Access | Times Cited: 2
Physics driven interpretable deep learning-based insights into boiling crisis of smooth and roughened surfaces
Uzair Sajjad, Sadaf Mehdi, Imtiyaz Hussain, et al.
Alexandria Engineering Journal (2024) Vol. 116, pp. 112-128
Closed Access
Artificial Neural Network-Based Modeling of Performance Spark Ignition Engine Fuelled with Bioethanol and Gasoline
Susi Marianingsih, Farhanna Mar’i, Hendry Y. Nanlohy
Journal of Mechanical Engineering Science and Technology (JMEST) (2023) Vol. 7, Iss. 2, pp. 190-190
Open Access | Times Cited: 1
Investigation of the Effect of Al2O3 - TiO2 Nano Particles on Engine Noise Using Machine Learning Method
Mehmet Selman GÖKMEN, Hasan Aydoğan
(2023), pp. 37-42
Closed Access
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