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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 69 citing articles:

Effect of particle behavior on the apparent viscosity of semi-solid metal: CFD-DEM simulation and artificial neural networks prediction
Dianqiao Geng, Dandan Yan, Wenjie Yu, et al.
Particuology (2025)
Closed Access
Artificial Neural Network prediction on negative and positive activation energy of magnetohydrodynamic nanofluid flow with multiple slips
Suman Sarkar, Hiranmoy Mondal, Prabir Kumar Kundu
Hybrid Advances (2025), pp. 100452-100452
Open Access
Integration of machine learning to increase steam turbine condenser vacuum and efficiency through gasket resealing and higher heat extraction into the atmosphere
Dušan Strušnik
International Journal of Energy Research (2021) Vol. 46, Iss. 3, pp. 3189-3212
Open Access | Times Cited: 24
Relying on machine learning methods for predicting hydrogen solubility in different alcoholic solvents
Zongming Zhou, Pejman Nourani, Mehdi Karimi, et al.
International Journal of Hydrogen Energy (2022) Vol. 47, Iss. 9, pp. 5817-5827
Closed Access | Times Cited: 16
Dynamic viscosity prediction of nanofluids using artificial neural network (ANN) and genetic algorithm (GA)
Halil İbrahim Topal, Beytullah Erdoğan, Oğuz Koçar, et al.
Journal of the Brazilian Society of Mechanical Sciences and Engineering (2024) Vol. 46, Iss. 7
Closed Access | Times Cited: 3
An Experimental Study on Artificial Intelligence‐Based Prediction of Capacitance–Voltage Parameters of Polymer‐Interface 6H‐SiC/MEH‐PPV/Al Schottky Diodes
Tamer Güzel, Andaç Batur Çolak
physica status solidi (a) (2022) Vol. 219, Iss. 5
Closed Access | Times Cited: 15
Experimental exploration of rheological behavior of polyethylene glycol-carbon dot nanofluid: Introducing a robust artificial intelligence paradigm optimized with unscented Kalman filter technique
Amin Shahsavar, Mohamad Amin Mirzaei, Aidin Shaham, et al.
Journal of Molecular Liquids (2022) Vol. 358, pp. 119198-119198
Closed Access | Times Cited: 14
Experimental study on the density, surface tension and electrical properties of ZrO2–EG nanofluids
Julian Traciak, Jolanta Sobczak, Javier P. Vallejo, et al.
Physics and Chemistry of Liquids (2022) Vol. 61, Iss. 1, pp. 14-24
Closed Access | Times Cited: 12
Dynamics Modeling of Industrial Robotic Manipulators: A Machine Learning Approach Based on Synthetic Data
Sandi Baressi Šegota, Nikola Anđelić, Mario Šercer, et al.
Mathematics (2022) Vol. 10, Iss. 7, pp. 1174-1174
Open Access | Times Cited: 12
Entropy-optimized MHD three-dimensional solar slendering sheet of micropolar hybrid nanofluid flow using a machine learning approach
A. Vivek Anand, Rifaqat Ali, Shaik Jakeer, et al.
Journal of Thermal Analysis and Calorimetry (2023) Vol. 149, Iss. 13, pp. 7001-7023
Closed Access | Times Cited: 6
The effect of graphene nano-powder on the viscosity of water: An experimental study and artificial neural network modeling
Saeed Alqaed, Jawed Mustafa, Mohsen Sharifpur, et al.
Nanotechnology Reviews (2022) Vol. 11, Iss. 1, pp. 2768-2785
Open Access | Times Cited: 10
The Role of Technical Indicators in the Intraday Prediction of Stock Markets: Artificial Neural Network Models for Borsa Istanbul
Andaç Batur Çolak, Ayben Koy
Scientia Iranica (2023)
Open Access | Times Cited: 5
Using radial basis function network to model the heat transfer and pressure drop of water based nanofluids containing MgO nanoparticles
Mohammad Hemmat Esfe, Mohammad Hassan Kamyab, Ali Alirezaie, et al.
Case Studies in Thermal Engineering (2021) Vol. 28, pp. 101475-101475
Open Access | Times Cited: 12
Analysing of nano-silica usage with fly ash for grouts with artificial neural network models
Fatih Çeli̇k, Oğuzhan Yıldız, Andaç Batur Çolak, et al.
Advances in Cement Research (2022) Vol. 35, Iss. 5, pp. 191-206
Closed Access | Times Cited: 8
Optimal viscosity modelling of 10W40 oil-based MWCNT (40%)-TiO2 (60%) nanofluid using Response Surface Methodology (RSM)
Mohammad Hemmat Esfe, Sayyid Majid Motallebi, Davood Toghraie
Heliyon (2022) Vol. 8, Iss. 12, pp. e11944-e11944
Open Access | Times Cited: 8
EXPERIMENTAL ANALYSIS OF THE EFFECT OF NANOFLUID USE ON POWER AND EFFICIENCY ENHANCEMENT IN HEAT PIPE SOLAR COLLECTORS AND MODELING USING ARTIFICIAL NEURAL NETWORKS
Sinan Ünvar, Andaç Batur Çolak, Tayfun Menlik
Heat Transfer Research (2023) Vol. 54, Iss. 13, pp. 1-18
Closed Access | Times Cited: 4
Optimisation of artificial intelligence models and response surface methodology for predicting viscosity and relative viscosity of GNP-alumina hybrid nanofluid: incorporating the effects of mixing ratio and temperature
Adeola Borode, Peter Apata Olubambi
The Journal of Supercomputing (2023) Vol. 80, Iss. 4, pp. 4841-4869
Open Access | Times Cited: 4
Application of artificial intelligence techniques for heat exchanger predictions in food industry
Oznur Oztuna Taner, Hatice Mercan, Andaç Batur Çolak, et al.
Elsevier eBooks (2024), pp. 269-325
Closed Access | Times Cited: 1
Increasing the accuracy of estimating the viscosity of SAE40-based nanofluid containing MWCNT-TiO2 nanoparticles using a creative method in optimizing the structure of the artificial neural network
Mohammad Hemmat Esfe, Davood Toghraie, Fatemeh Amoozadkhalili
Tribology International (2022) Vol. 179, pp. 108161-108161
Closed Access | Times Cited: 7
Application of experimental and statistical methods in the study of rheology of MWCNT (25%)-TiO2 (75%)/ SAE40 HNF to identify and use in the lubrication industry
Mohammad Hemmat Esfe, Erfan Mohammadnejad Ardeshiri, Davood Toghraie
Colloids and Surfaces A Physicochemical and Engineering Aspects (2022) Vol. 643, pp. 128710-128710
Closed Access | Times Cited: 6
Artificial neural network-based modelling of optimized experimental study of xylanase production by Penicillium citrinum xym2
G.A. Kumar, Shyama Prasad Saha, Shilpi Ghosh, et al.
Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering (2021) Vol. 236, Iss. 4, pp. 1340-1348
Closed Access | Times Cited: 8
EXPERIMENTAL AND MODELING ANALYSES OF STABILITY AND THERMOPHYSICAL CHARACTERISTICS OF GRAPHENE OXIDE, CARBON NANOTUBE, AND SILICON CARBIDE DISPERSION IN PROPYLENE GLYCOL
Mohammad Khakpour, Behzad Vaferi
Heat Transfer Research (2023) Vol. 54, Iss. 14, pp. 1-15
Closed Access | Times Cited: 3
Finite element and neural computations for energy system containing conductive solid body and bottom circular heaters utilizing Ag–MgO (50:50)/water hybrid nanofluid
Puneet Rana, Jiapeng Ma, Yiran Zhang, et al.
Journal of Magnetism and Magnetic Materials (2023) Vol. 577, pp. 170775-170775
Closed Access | Times Cited: 3
A novel hybrid nanofluid including MWCNT and ZrO2 nanoparticles: implementation of response surface methodology and artificial neural network
Jawed Mustafa, Saeed Alqaed, M.M. Abdullah, et al.
Journal of Thermal Analysis and Calorimetry (2023) Vol. 148, Iss. 18, pp. 9619-9632
Closed Access | Times Cited: 3
An Experimental Investigation on Workability and Bleeding Features
Fatih Çeli̇k, Andaç Batur Çolak, Og ̆uzhan Yıldız, et al.
ACI Materials Journal (2022) Vol. 119, Iss. 5
Closed Access | Times Cited: 5

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