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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:

Recent trends on nanofluid heat transfer machine learning research applied to renewable energy
Ting Ma, Zhixiong Guo, Mei Lin, et al.
Renewable and Sustainable Energy Reviews (2020) Vol. 138, pp. 110494-110494
Open Access | Times Cited: 127

Showing 51-75 of 127 citing articles:

Bio-convection in tri-hybrid nanofluid flow with Arrhenius activation energy: Incorporating the Cattaneo-Christov heat flux model
Muhammad Jawad, Zhuojia Fu, Hamid Hassan Khan, et al.
Journal of Radiation Research and Applied Sciences (2025) Vol. 18, Iss. 1, pp. 101296-101296
Closed Access
Impact of tube shapes on the energy storage and thermal-hydraulic performances of finned latent heat energy storage systems
Zihao Cheng, Juan Du, Shuao Jia, et al.
Case Studies in Thermal Engineering (2025), pp. 105827-105827
Open Access
Advancements in CNT research: Integrating machine learning with microscopic simulations, macroscopic techniques, and application of performance prediction and functional optimization
Dianming Chu, Chenyu Gao, Zongchao Ji, et al.
Materials Today Chemistry (2025) Vol. 45, pp. 102616-102616
Closed Access
Exploring the impact of particle stability, size, and morphology on nanofluid thermal conductivity: A comprehensive review for energy applications
Sajid Farooq, Muhammad Habib, Olavo Cardozo, et al.
Advances in Colloid and Interface Science (2025), pp. 103495-103495
Closed Access
Modeling and performance analysis of phase change materials in advanced thermal energy storage systems: A comprehensive review
Houssam Eddine Abdellatif, Ahmed Belaadi, Adeel Arshad, et al.
Journal of Energy Storage (2025) Vol. 121, pp. 116517-116517
Closed Access
Experimental and artificial neural network based study on the heat transfer and flow performance of ZnO-EG/water nanofluid in a mini-channel with serrated fins
Tao Wen, Guangya Zhu, Lin Lu
International Journal of Thermal Sciences (2021) Vol. 170, pp. 107149-107149
Closed Access | Times Cited: 28
Accurate prediction of dynamic viscosity of polyalpha-olefin boron nitride nanofluids using machine learning
Yazeed AbuShanab, Wahib A. Al‐Ammari, Samer Gowid, et al.
Heliyon (2023) Vol. 9, Iss. 6, pp. e16716-e16716
Open Access | Times Cited: 11
Machine learning-assisted correlations of heat/mass transfer and pressure drop of microchannel membrane-based desorber/absorber for compact absorption cycles
Chong Zhai, Yunren Sui, Wei Wu
International Journal of Heat and Mass Transfer (2023) Vol. 214, pp. 124431-124431
Closed Access | Times Cited: 11
AN OPTIMIZATION TECHNIQUE TO IDENTIFY SIMULATION ASSUMPTIONS FOR VARIOUS NANOFLUIDS USING MACHINE LEARNING
Ekene Onyiriuka, Daniel Raphael Ejike Ewim, Sogo Mayokun Abolarin
Proceeding of International Heat Transfer Conference 9 (2023), pp. 12-12
Closed Access | Times Cited: 11
Design improvement of latent heat thermal energy storage in wavy channel enclosures using neural networks
Hakim S. Sultan Aljibori, Mohammed Hasan Ali, Jana Shafi, et al.
Journal of Energy Storage (2023) Vol. 79, pp. 110061-110061
Closed Access | Times Cited: 11
Development of a hybrid CFD-ANN method with multi-objective optimization for airfoil-finned PCHE used in Gen-IV nuclear systems
Jinneng Ding, Qihang Liu, Juntao Ke, et al.
Progress in Nuclear Energy (2024) Vol. 175, pp. 105346-105346
Closed Access | Times Cited: 4
Nanofluid heat transfer and machine learning: Insightful review of machine learning for nanofluid heat transfer enhancement in porous media and heat exchangers as sustainable and renewable energy solutions
Tri W.B. Riyadi, Safarudin Gazali Herawan, Andy Tirta, et al.
Results in Engineering (2024), pp. 103002-103002
Open Access | Times Cited: 4
Optimizing solar panel performance with new algorithm incorporating duct with helical tape and hybrid nanofluid
A. Anisi, M. Sheikholeslami, Z. Khalili, et al.
Journal of the Taiwan Institute of Chemical Engineers (2024) Vol. 167, pp. 105908-105908
Closed Access | Times Cited: 4
Shannon Entropy in Uncertainty Quantification for the Physical Effective Parameter Computations of Some Nanofluids
Marcin Kamiński, Rafał Ossowski
Nanomaterials (2025) Vol. 15, Iss. 3, pp. 250-250
Open Access
Energy and mass transport through hybrid nanofluid flow passing over an extended cylinder with the magnetic dipole using a computational approach
M. Riaz Khan, N. Ameer Ahammad, Sharifah E. Alhazmi, et al.
Frontiers in Energy Research (2022) Vol. 10
Open Access | Times Cited: 18
Estimation of forced heat convection in a rectangular channel with curved-winglet vortex generator: A machine learning approach
Adnan Berber, Mehmet Gürdal
Thermal Science and Engineering Progress (2022) Vol. 37, pp. 101563-101563
Closed Access | Times Cited: 16
From experimental data to predictions: Artificial intelligence supported new mathematical approaches for estimating thermal conductivity, viscosity and zeta potential in Fe3O4-water magnetic nanofluids
Fevzi Şahin, Ömer Genç, Murat Gökçek, et al.
Powder Technology (2023) Vol. 430, pp. 118974-118974
Closed Access | Times Cited: 10
Prediction of transient melt fraction in metal foam - nanoparticle enhanced PCM hybrid shell and tube heat exchanger: A machine learning approach
Gopi Krishna Amudhalapalli, Jaya Krishna Devanuri
Thermal Science and Engineering Progress (2023) Vol. 46, pp. 102241-102241
Closed Access | Times Cited: 10
Recent advances in the applications of machine learning methods for heat exchanger modeling—a review
Junjia Zou, Tomoki Hirokawa, Jiabao An, et al.
Frontiers in Energy Research (2023) Vol. 11
Open Access | Times Cited: 10
Heat transfer performance in a Hybrid nanofluid (Cu-Al2O3 /kerosene oil) flow over a shrinking cylinder
Abdul Hafeez, F. M. Aldosari, Maha M. Helmi, et al.
Case Studies in Thermal Engineering (2023) Vol. 52, pp. 103539-103539
Open Access | Times Cited: 10
Machine learning and artificial intelligence-distributed renewable energy sources: technologies, perspectives, and challenges
Xiaojun Yu, Yuekuan Zhou
Elsevier eBooks (2024), pp. 17-30
Closed Access | Times Cited: 3
Modeling of Average Nusselt Number by Machine Learning and Interpolation Techniques
Bengisen Pekmen Geridönmez
ASME Journal of Heat and Mass Transfer (2024) Vol. 146, Iss. 4
Closed Access | Times Cited: 3
A study on the impact of solar radiations and activation energy effects in existence of nanofluid over stretching solar sheets
Bilal Ahmad, Muhammad Idrees, Syed Asif Ali Shah, et al.
Case Studies in Thermal Engineering (2024) Vol. 59, pp. 104448-104448
Open Access | Times Cited: 3
Deep learning based analysis of microstructured materials for thermal radiation control
Jonathan Sullivan, Arman Mirhashemi, Jaeho Lee
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 14
Production of hydrogen as value added product from the photovoltaic thermal system operated with graphene nanoparticles: An experimental study
M. Sangeetha, Beáta Gavurová, Manigandan Sekar, et al.
Fuel (2022) Vol. 334, pp. 126792-126792
Closed Access | Times Cited: 14

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