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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:

Applying Artificial Neural Network and Response Surface Method to Forecast the Rheological Behavior of Hybrid Nano-Antifreeze Containing Graphene Oxide and Copper Oxide Nanomaterials
Ammar A. Melaibari, Yacine Khetib, Abdullah K. Alanazi, et al.
Sustainability (2021) Vol. 13, Iss. 20, pp. 11505-11505
Open Access | Times Cited: 13

Showing 13 citing articles:

Utilizing machine learning algorithms for prediction of the rheological behavior of ZnO (50%)-MWCNTs (50%)/ Ethylene glycol (20%)-water (80%) nano-refrigerant
Xiedong Song, Mohammadreza Baghoolizadeh, As’ad Alizadeh, et al.
International Communications in Heat and Mass Transfer (2024) Vol. 156, pp. 107634-107634
Closed Access | Times Cited: 9
Enhancing thermal conductivity of water/CeO2-MWCNTs hybrid nanofluid: experimental insights and artificial neural network modeling
Saeed Alqaed, Jawed Mustafa, S. Mohammad Sajadi, et al.
Journal of Thermal Analysis and Calorimetry (2024) Vol. 149, Iss. 9, pp. 4019-4031
Closed Access | Times Cited: 6
Experimental examination of the properties of Fe3O4/water nanofluid, and an estimation of a correlation using an artificial neural network
Hamed Eshgarf, Afshin Ahmadi Nadooshan, Afrasiab Raisi, et al.
Journal of Molecular Liquids (2023) Vol. 374, pp. 121150-121150
Closed Access | Times Cited: 15
Regression modeling and multi-objective optimization of rheological behavior of non-Newtonian hybrid antifreeze: Using different neural networks and evolutionary algorithms
WeiHong Jin, Ali Basem, Mohammadreza Baghoolizadeh, et al.
International Communications in Heat and Mass Transfer (2024) Vol. 155, pp. 107578-107578
Closed Access | Times Cited: 5
Impact of virtual baffles and magnetic nanofluid on thermo-hydraulic characteristics of sine wave mini channel
Basma Souayeh
Journal of Thermal Analysis and Calorimetry (2025)
Closed Access
Effect of Magnetic Baffles and Magnetic Nanofluid on Thermo-Hydraulic Characteristics of Dimple Mini Channel for Thermal Energy Applications
Basma Souayeh, Suvanjan Bhattacharyya, Najib Hdhiri, et al.
Sustainability (2022) Vol. 14, Iss. 16, pp. 10419-10419
Open Access | Times Cited: 14
Applying different machine learning algorithms to predict the viscosity behavior of MWCNT–alumina/water–ethylene glycol (80:20) hybrid antifreeze
Shaymaa Abed Hussein, Ihab Omar, Ali B. Saddam, et al.
International Journal of Thermofluids (2024) Vol. 24, pp. 100966-100966
Open Access | Times Cited: 2
Selection of Best Suitable Eco-Friendly Refrigerants for HVAC Sector and Renewable Energy Devices
Basma Souayeh, Suvanjan Bhattacharyya, Najib Hdhiri, et al.
Sustainability (2022) Vol. 14, Iss. 18, pp. 11663-11663
Open Access | Times Cited: 10
Development of knowledge management for viscosity of nanolubricant in hot and cold lubrication conditions
Mohammad Hemmat Esfe, Rouhollah Tavallaee, Morteza Sarbaz Karajabad, et al.
Tribology International (2023) Vol. 188, pp. 108873-108873
Closed Access | Times Cited: 5
Prediction and Optimization of Process Parameters for Composite Thermoforming Using a Machine Learning Approach
Long Bin Tan, Nguyen Dang Phuc Nhat
Polymers (2022) Vol. 14, Iss. 14, pp. 2838-2838
Open Access | Times Cited: 8
RETRACTED: Improve the rheological and thermal performances of the antifreeze liquids for cooling the batteries and radiators in automobiles via provide a new hybrid material composed from Carbon Nanotubes in Ethylene Glycol/Propylene Glycol
Nidal H. Abu‐Hamdeh, Arash Karimipour, Randa I. Hatamleh, et al.
Journal of Energy Storage (2022) Vol. 52, pp. 104982-104982
Closed Access | Times Cited: 7
Prediction and Optimization of Process Parameters for Composite Thermoforming Using a Machine Learning Approach
Long Bin Tan, Nguyen Dang Phuc Nhat
Vide Leaf, Hyderabad eBooks (2023)
Open Access | Times Cited: 2
Thermal and Rheological Characterization of Aqueous Nanofluids Based on Reduced Graphene Oxide (rGO) with Manganese Dioxide Nanocomposites (MnO2)
Felipe Lozano-Steinmetz, María Paz Ramírez-Navarro, Leonardo Vivas, et al.
Nanomaterials (2022) Vol. 12, Iss. 17, pp. 3042-3042
Open Access | Times Cited: 4
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