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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:

Prognostic modeling of polydisperse SiO2/Aqueous glycerol nanofluids' thermophysical profile using an explainable artificial intelligence (XAI) approach
K.V. Sharma, P. H. V. Sesha Talpa Sai, Prabhakar Sharma, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106967-106967
Closed Access | Times Cited: 18

Showing 18 citing articles:

Optimization of thermophysical properties of nanofluids using a hybrid procedure based on machine learning, multi-objective optimization, and multi-criteria decision-making
Tao Zhang, Anahita Manafi Khajeh Pasha, S. Mohammad Sajadi, et al.
Chemical Engineering Journal (2024) Vol. 485, pp. 150059-150059
Closed Access | Times Cited: 22
Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
Van Giao Nguyen, Prabhakar Sharma, Ümit Ağbulut, et al.
International Journal of Green Energy (2024) Vol. 21, Iss. 12, pp. 2771-2798
Closed Access | Times Cited: 8
Machine learning analysis of thermophysical and thermohydraulic properties in ethylene glycol- and glycerol-based SiO2 nanofluids
Suleiman Akilu, K.V. Sharma, Aklilu Tesfamichael Baheta, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5
Explainable Advanced Modelling of CO2-Dissolved Brine Density: Applications for Geological CO2 Storage in Aquifers
Amin Shokrollahi, Afshin Tatar, Sepideh Atrbarmohammadi, et al.
Inventions (2025) Vol. 10, Iss. 1, pp. 15-15
Open Access
Forecasting and Feature Analysis of Ship Fuel Consumption by Explainable Machine Learning Approaches
Nguyen Dang Khoa Pham, Gia Huy Dinh, Canh Nguyen, et al.
Polish Maritime Research (2025) Vol. 32, Iss. 1, pp. 81-94
Open Access
Prediction of the viscosity of iron-CuO/water-ethylene glycol non-Newtonian hybrid nanofluids using different machine learning algorithms
Mohammed Shorbaz Graish, Ali B.M. Ali, Murtadha M. Al-Zahiwat, et al.
Case Studies in Chemical and Environmental Engineering (2025), pp. 101180-101180
Open Access
Prediction of the thermal behavior of multi-walled carbon nanotubes-CuO-CeO2 (20-40-40)/water hybrid nanofluid using different types of regressors and evolutionary algorithms for designing the best artificial neural network modeling
Reza Rostamzadeh‐Renani, Mohammadreza Baghoolizadeh, S. Mohammad Sajadi, et al.
Alexandria Engineering Journal (2023) Vol. 84, pp. 184-203
Open Access | Times Cited: 13
Transfer learned deep feature based crack detection using support vector machine: a comparative study
K. S. Bhalaji Kharthik, Edeh Michael Onyema, Saurav Mallik, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4
Detection of Manufacturing Defects in Steel Using Deep Learning With Explainable Artificial Intelligence
Zeina Aboulhosn, Ahmad Musamih, Khaled Salah, et al.
IEEE Access (2024) Vol. 12, pp. 99240-99257
Open Access | Times Cited: 4
Impact of hybrid and mono nanofluids on the cooling performance of lithium-ion batteries: Experimental and machine learning insights
Praveen Kumar Kanti, Edmond Soong Jia Yang, V. Vicki Wanatasanappan, et al.
Journal of Energy Storage (2024) Vol. 101, pp. 113613-113613
Closed Access | Times Cited: 4
Explainable machine learning techniques for hybrid nanofluids transport characteristics: an evaluation of shapley additive and local interpretable model-agnostic explanations
Praveen Kumar Kanti, Prabhakar Sharma, V. Vicki Wanatasanappan, et al.
Journal of Thermal Analysis and Calorimetry (2024) Vol. 149, Iss. 21, pp. 11599-11618
Closed Access | Times Cited: 3
On the evaluation of mono-nanofluids’ density using a radial basis function neural network optimized by evolutionary algorithms
Omid Deymi, Farzaneh Rezaei, Saeid Atashrouz, et al.
Thermal Science and Engineering Progress (2024) Vol. 53, pp. 102750-102750
Closed Access | Times Cited: 2
Recent Applications of Explainable AI (XAI): A Systematic Literature Review
Mirka Saarela, Vili Podgorelec
Applied Sciences (2024) Vol. 14, Iss. 19, pp. 8884-8884
Open Access | Times Cited: 2
A deep reinforcement learning-based method for dynamic quality of service aware energy and occupant comfort management in intelligent buildings
Amirhossein Azimi, Omid Akbari
e-Prime - Advances in Electrical Engineering Electronics and Energy (2024) Vol. 9, pp. 100700-100700
Open Access | Times Cited: 1
Harnessing nano-synergy: A comprehensive study of thermophysical characteristics of silver, beryllium oxide, and silicon carbide in hybrid nanofluid formulations
Hamza Babar, Hongwei Wu, Wenbin Zhang, et al.
Journal of Molecular Liquids (2024), pp. 126175-126175
Open Access | Times Cited: 1
Introducing an integrated self-organizing map and radial basis function network for accurate prediction of water- Fe3O4 nanofluid viscosity versus solid volume fraction and temperature
Chang Lei, Wenqing Yang, Mohamad Khaje Khabaz, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 209, pp. 115119-115119
Closed Access
Characterization of Silicon Dioxide Nanofluids: Viscosity and Thermal Conductivity Analysis for Hybrid Vehicle Applications
V. Sundaram, S. Madhu, S. Vidhyalakshmi, et al.
SAE technical papers on CD-ROM/SAE technical paper series (2024) Vol. 1
Closed Access
Numerical treatment for Darcy–Forchheimer flow of propylene glycol with carbon nanotubes under the impacts of MHD and activation energy
Hafiz Muhammad Shahbaz, Iftikhar Ahmad
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
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