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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: 126

Showing 1-25 of 126 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
Synthesis, stability, density, viscosity of ethylene glycol-based ternary hybrid nanofluids: Experimental investigations and model -prediction using modern machine learning techniques
Zafar Said, Neşe Keklikçioğlu Çakmak, Prabhakar Sharma, et al.
Powder Technology (2022) Vol. 400, pp. 117190-117190
Closed Access | Times Cited: 134
Heat transfer analysis of hybrid nanofluid flow with thermal radiation through a stretching sheet: A comparative study
Hassan Waqas, Umar Farooq, Dong Liu, et al.
International Communications in Heat and Mass Transfer (2022) Vol. 138, pp. 106303-106303
Closed Access | Times Cited: 114
Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques
Laith Abualigah, Raed Abu Zitar, Khaled H. Almotairi, et al.
Energies (2022) Vol. 15, Iss. 2, pp. 578-578
Open Access | Times Cited: 112
Application of artificial intelligence for prediction, optimization, and control of thermal energy storage systems
A.G. Olabi, Aasim Ahmed Abdelghafar, Hussein M. Maghrabie, et al.
Thermal Science and Engineering Progress (2023) Vol. 39, pp. 101730-101730
Closed Access | Times Cited: 90
Heat transfer enhancement of phase change materials embedded with metal foam for thermal energy storage: A review
Wei Cui, Tianyu Si, Xiangxuan Li, et al.
Renewable and Sustainable Energy Reviews (2022) Vol. 169, pp. 112912-112912
Closed Access | Times Cited: 86
Modeling of Darcy–Forchheimer bioconvective Powell Eyring nanofluid with artificial neural network
Andaç Batur Çolak, Anum Shafiq, Tabassum Naz Sindhu
Chinese Journal of Physics (2022) Vol. 77, pp. 2435-2453
Closed Access | Times Cited: 76
Modeling of Soret and Dufour’s Convective Heat Transfer in Nanofluid Flow Through a Moving Needle with Artificial Neural Network
Anum Shafiq, Andaç Batur Çolak, Tabassum Naz Sindhu
Arabian Journal for Science and Engineering (2022) Vol. 48, Iss. 3, pp. 2807-2820
Closed Access | Times Cited: 76
Nanofluids in compact heat exchangers for thermal applications: A State-of-the-art review
Wagd Ajeeb, S. M. Sohel Murshed
Thermal Science and Engineering Progress (2022) Vol. 30, pp. 101276-101276
Open Access | Times Cited: 75
Modeling and simulation of Maxwell nanofluid flows in the presence of Lorentz and Darcy–Forchheimer forces: toward a new approach on Buongiorno’s model using artificial neural network (ANN)
Zeeshan Khan, Samina Zuhra, Saeed Islam, et al.
The European Physical Journal Plus (2023) Vol. 138, Iss. 1
Closed Access | Times Cited: 47
Performance optimization of energy-efficient solar absorbers for thermal energy harvesting in modern industrial environments using a solar deep learning model
Ammar Armghan, J. Logeshwaran, S. Raja, et al.
Heliyon (2024) Vol. 10, Iss. 4, pp. e26371-e26371
Open Access | Times Cited: 26
Numerical study and machine learning on local flow and heat transfer characteristics of supercritical carbon dioxide mixtures in a sinusoidal wavy channel PCHE
Zhe-Xi Wen, Jinglin Wu, Shuaishuai Wang, et al.
International Journal of Heat and Mass Transfer (2024) Vol. 223, pp. 125278-125278
Closed Access | Times Cited: 19
Thermal Conductivity of Nanofluids: A Review on Prediction Models, Controversies and Challenges
Inês M. Gonçalves, Reinaldo Rodrigues de Souza, Gonçalo Coutinho, et al.
Applied Sciences (2021) Vol. 11, Iss. 6, pp. 2525-2525
Open Access | Times Cited: 78
Status, Challenges, and Potential for Machine Learning in Understanding and Applying Heat Transfer Phenomena
Matthew T. Hughes, Girish Kini, Srinivas Garimella
Journal of Heat Transfer (2021) Vol. 143, Iss. 12
Closed Access | Times Cited: 59
Sustainable energies and machine learning: An organized review of recent applications and challenges
Pouya Ifaei, Morteza Nazari‐Heris, Amir Saman Tayerani Charmchi, et al.
Energy (2022) Vol. 266, pp. 126432-126432
Closed Access | Times Cited: 47
Non-Fourier energy transmission in power-law hybrid nanofluid flow over a moving sheet
Awatif Alhowaity, Muhammad Bilal, Haneen Hamam, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 45
Computational methods to simulate molten salt thermophysical properties
Talmage Porter, Michael M. Vaka, Parker Steenblik, et al.
Communications Chemistry (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 40
A review of the enhancement of solar thermal collectors using nanofluids and turbulators
Aissa Abderrahmane, Naef A.A. Qasem, Abed Mourad, et al.
Applied Thermal Engineering (2022) Vol. 220, pp. 119663-119663
Closed Access | Times Cited: 40
Enhancing performance of nanofluid mini-channel heat sinks through machine learning and multi-objective optimization of operating parameters
Qifan Wang, Shengqi Zhang, Yu Zhang, et al.
International Journal of Heat and Mass Transfer (2023) Vol. 210, pp. 124204-124204
Closed Access | Times Cited: 29
Can Artificial Intelligence Accelerate Fluid Mechanics Research?
Dimitris Drikakis, Filippos Sofos
Fluids (2023) Vol. 8, Iss. 7, pp. 212-212
Open Access | Times Cited: 28
Investigation and optimization of biodiesel production based on multiple machine learning technologies
Xin Jin, Shi‐Hao Li, Haoran Ye, et al.
Fuel (2023) Vol. 348, pp. 128546-128546
Closed Access | Times Cited: 22
A comprehensive review on the recent advances in applications of nanofluids for effective utilization of renewable energy
Uma Sankar Behera, Jitendra S. Sangwai, Hun‐Soo Byun
Renewable and Sustainable Energy Reviews (2024) Vol. 207, pp. 114901-114901
Closed Access | Times Cited: 11
Machine learning and prediction study on heat transfer of supercritical CO2 in pseudo-critical zone
Zhe-Xi Wen, Jinglin Wu, Xuewei Cao, et al.
Applied Thermal Engineering (2024) Vol. 243, pp. 122630-122630
Closed Access | Times Cited: 10
Deep learning with multilayer perceptron for optimizing the heat transfer of mixed convection equipped with MWCNT-water nanofluid
Xiaogang Dong, Salah Knani, Hamdi Ayed, et al.
Case Studies in Thermal Engineering (2024) Vol. 57, pp. 104309-104309
Open Access | Times Cited: 10
Numerical paradigm to explore the chemically reacting Williamson nanofluid flow with the influence of bioconvection effects using neural networks
Saddiqa Hussain, Taghreed A. Assiri, Zeeshan Khan, et al.
Numerical Heat Transfer Part A Applications (2024), pp. 1-21
Closed Access | Times Cited: 10
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