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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:

A unique thermal conductivity model (ANN) for nanofluid based on experimental study
Ashutosh Pare, Subrata Kumar Ghosh
Powder Technology (2020) Vol. 377, pp. 429-438
Closed Access | Times Cited: 62

Showing 1-25 of 62 citing articles:

Recent Advances in Machine Learning Research for Nanofluid-Based Heat Transfer in Renewable Energy System
Prabhakar Sharma, Zafar Said, Anurag Kumar, et al.
Energy & Fuels (2022) Vol. 36, Iss. 13, pp. 6626-6658
Closed Access | Times Cited: 242
Using perceptron feed-forward Artificial Neural Network (ANN) for predicting the thermal conductivity of graphene oxide-Al2O3/water-ethylene glycol hybrid nanofluid
Shaopeng Tian, Noreen Izza Arshad, Davood Toghraie, et al.
Case Studies in Thermal Engineering (2021) Vol. 26, pp. 101055-101055
Open Access | Times Cited: 124
MHD Hybrid Nanofluid Mixed Convection Heat Transfer and Entropy Generation in a 3-D Triangular Porous Cavity with Zigzag Wall and Rotating Cylinder
Aissa Abderrahmane, Naef A.A. Qasem, Obai Younis, et al.
Mathematics (2022) Vol. 10, Iss. 5, pp. 769-769
Open Access | Times Cited: 75
On the assessment of specific heat capacity of nanofluids for solar energy applications: Application of Gaussian process regression (GPR) approach
Mehdi Jamei, Iman Ahmadianfar, Ismail Adewale Olumegbon, et al.
Journal of Energy Storage (2020) Vol. 33, pp. 102067-102067
Closed Access | Times Cited: 94
Applying Artificial Neural Networks (ANNs) for prediction of the thermal characteristics of water/ethylene glycol-based mono, binary and ternary nanofluids containing MWCNTs, titania, and zinc oxide
Xiaowei Yang, Ahmadreza Boroomandpour, Shiwei Wen, et al.
Powder Technology (2021) Vol. 388, pp. 418-424
Closed Access | Times Cited: 77
A novel comparative analysis between the experimental and numeric methods on viscosity of zirconium oxide nanofluid: Developing optimal artificial neural network and new mathematical model
Andaç Batur Çolak
Powder Technology (2021) Vol. 381, pp. 338-351
Closed Access | Times Cited: 69
Specific heat capacity of molten salt-based nanofluids in solar thermal applications: A paradigm of two modern ensemble machine learning methods
Mehdi Jamei, Masoud Karbasi, Ismail Adewale Olumegbon, et al.
Journal of Molecular Liquids (2021) Vol. 335, pp. 116434-116434
Closed Access | Times Cited: 59
Spectral Simulation on the Flow Patterns and Thermal Control of Radiative Nanofluid Spraying on an Inclined Revolving Disk Considering the Effect of Nanoparticle Diameter and Solid–Liquid Interfacial Layer
Nilankush Acharya
Journal of Heat Transfer (2022) Vol. 144, Iss. 9
Closed Access | Times Cited: 56
Comparative evaluation of AI ‐based intelligent GEP and ANFIS models in prediction of thermophysical properties of Fe 3 O 4 ‐coated MWCNT hybrid nanofluids for potential application in energy systems
Prabhakar Sharma, Zafar Said, Saim Memon, et al.
International Journal of Energy Research (2022) Vol. 46, Iss. 13, pp. 19242-19257
Open Access | Times Cited: 44
A novel integrated model to improve the dynamic viscosity of MWCNT-Al2O3 (40:60)/Oil 5W50 hybrid nano-lubricant using artificial neural networks (ANNs)
Mohammad Hemmat Esfe, Reza Esmaily, Mohamad Khaje Khabaz, et al.
Tribology International (2022) Vol. 178, pp. 108086-108086
Closed Access | Times Cited: 40
Thermophysical properties of nanofluids and their potential applications in heat transfer enhancement: A review
Sujata Kalsi, Sunil Kumar, Anil Kumar, et al.
Arabian Journal of Chemistry (2023) Vol. 16, Iss. 11, pp. 105272-105272
Open Access | Times Cited: 38
Multi-objective optimization of thermophysical properties GO powders-DW/EG Nf by RSM, NSGA-II, ANN, MLP and ML
Mahmoud Kiannejad Amiri, Seyed Peiman Ghorbanzade Zaferani, Mohammad Reza Sarmasti Emami, et al.
Energy (2023) Vol. 280, pp. 128176-128176
Closed Access | Times Cited: 27
State-of-the-art review on water-based nanofluids for low temperature solar thermal collector application
Fazlay Rubbi, Likhan Das, Khairul Habib, et al.
Solar Energy Materials and Solar Cells (2021) Vol. 230, pp. 111220-111220
Open Access | Times Cited: 53
Efficacy evaluation of oxide-MWCNT water hybrid nanofluids: An experimental and artificial neural network approach
Vikas Kumar, Ashutosh Pare, Arun Kumar Tiwari, et al.
Colloids and Surfaces A Physicochemical and Engineering Aspects (2021) Vol. 620, pp. 126562-126562
Closed Access | Times Cited: 52
Statistical review of studies on the estimation of thermophysical properties of nanofluids using artificial neural network (ANN)
Mohammad Hemmat Esfe, Mohammad Hassan Kamyab, Davood Toghraie
Powder Technology (2022) Vol. 400, pp. 117210-117210
Closed Access | Times Cited: 33
Modeling and Sensitivity Analysis of Thermal Conductivity of Ethylene Glycol-Water Based Nanofluids with Alumina Nanoparticles
Mohammad Mehdi Rashidi, Mohammad Alhuyi Nazari, Ibrahim Mahariq, et al.
Experimental Techniques (2022) Vol. 47, Iss. 1, pp. 83-90
Closed Access | Times Cited: 32
MHD williamson nanofluid flow in the rheology of thermal radiation, joule heating, and chemical reaction using the Levenberg–Marquardt neural network algorithm
Aatif Ali, N. Ameer Ahammad, Sayed M. Eldin, et al.
Frontiers in Energy Research (2022) Vol. 10
Open Access | Times Cited: 29
Comprehensive study and scientific process to increase the accuracy in estimating the thermal conductivity of nanofluids containing SWCNTs and CuO nanoparticles using an artificial neural network
Mohammad Hemmat Esfe, Fatemeh Amoozad, Hossein Hatami, et al.
Micro and Nano Systems Letters (2024) Vol. 12, Iss. 1
Open Access | Times Cited: 7
Prediction of heat transfer enhancement of delta-wing tape inserts using artificial neural network
Muhammed Zafar Ali Khan, Muhammad Aziz, Agung Tri Wijayanta
Case Studies in Thermal Engineering (2021) Vol. 27, pp. 101322-101322
Open Access | Times Cited: 37
Clathrate hydrate for phase change cold storage: Simulation advances and potential applications
Yuan Lv, Xinran Xia, Fan Wang, et al.
Journal of Energy Storage (2022) Vol. 55, pp. 105835-105835
Closed Access | Times Cited: 24
Optimization and design of ANN with Levenberg-Marquardt algorithm to increase the accuracy in predicting the viscosity of SAE40 oil-based hybrid nano-lubricant
Mohammad Hemmat Esfe, Davood Toghraie, Fatemeh Amoozadkhalili
Powder Technology (2022) Vol. 415, pp. 118097-118097
Closed Access | Times Cited: 22
Reliable prediction of thermophysical properties of nanofluids for enhanced heat transfer in process industry: a perspective on bridging the gap between experiments, CFD and machine learning
Atta Ullah, Mustafa Kılıç, Ghulam Habib, et al.
Journal of Thermal Analysis and Calorimetry (2023) Vol. 148, Iss. 12, pp. 5859-5881
Closed Access | Times Cited: 14
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: 14
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
Prediction of thermal conductivity of MWCNT (85)-ZnO (15)/EG hybrid nano-refrigerant using optimized ANN and comparison of its deviation with experimental data and classical model
Mohammad Hemmat Esfe, Davood Toghraie, Hossein Hatami
Journal of Thermal Analysis and Calorimetry (2025)
Closed Access
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