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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:

On the specific heat capacity estimation of metal oxide-based nanofluid for energy perspective – A comprehensive assessment of data analysis techniques
Mehdi Jamei, Iman Ahmadianfar, Ismail Adewale Olumegbon, et al.
International Communications in Heat and Mass Transfer (2021) Vol. 123, pp. 105217-105217
Closed Access | Times Cited: 57

Showing 1-25 of 57 citing articles:

Recent advances on the fundamental physical phenomena behind stability, dynamic motion, thermophysical properties, heat transport, applications, and challenges of nanofluids
Zafar Said, L. Syam Sundar, Arun Kumar Tiwari, et al.
Physics Reports (2021) Vol. 946, pp. 1-94
Closed Access | Times Cited: 306
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: 243
Recent advances on improved optical, thermal, and radiative characteristics of plasmonic nanofluids: Academic insights and perspectives
Zafar Said, Sahil Arora, Sajid Farooq, et al.
Solar Energy Materials and Solar Cells (2021) Vol. 236, pp. 111504-111504
Closed Access | Times Cited: 165
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
Optimization of thermophysical properties of nanofluids using a hybrid procedure based on machine learning, multi-objective optimization, and multi-criteria decision-making
Tao Zhang, Anahita Manafi Khajeh Pasha, S. Mohammad Sajadi, et al.
Chemical Engineering Journal (2024) Vol. 485, pp. 150059-150059
Closed Access | Times Cited: 24
Exploring the specific heat capacity of water-based hybrid nanofluids for solar energy applications: A comparative evaluation of modern ensemble machine learning techniques
Zafar Said, Prabhakar Sharma, Rajvikram Madurai Elavarasan, et al.
Journal of Energy Storage (2022) Vol. 54, pp. 105230-105230
Closed Access | Times Cited: 64
On the Thermal Conductivity Assessment of Oil-Based Hybrid Nanofluids using Extended Kalman Filter integrated with feed-forward neural network
Mehdi Jamei, Ismail Adewale Olumegbon, Masoud Karbasi, et al.
International Journal of Heat and Mass Transfer (2021) Vol. 172, pp. 121159-121159
Closed Access | Times Cited: 61
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: 60
A critical review of specific heat capacity of hybrid nanofluids for thermal energy applications
Humphrey Adun, Ifeoluwa Wole‐Osho, Eric C. Okonkwo, et al.
Journal of Molecular Liquids (2021) Vol. 340, pp. 116890-116890
Closed Access | Times Cited: 59
Novel treatments for the bioconvective radiative Ellis nanofluids wedge flow with viscous dissipation and an activation energy
Sameh E. Ahmed, Anas A. M. Arafa, Sameh A. Hussein, et al.
Case Studies in Thermal Engineering (2022) Vol. 40, pp. 102510-102510
Open Access | Times Cited: 58
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
Optimized ANFIS models based on grid partitioning, subtractive clustering, and fuzzy C-means to precise prediction of thermophysical properties of hybrid nanofluids
Zhongwei Zhang, Mohammed Al‐Bahrani, Behrooz Ruhani, et al.
Chemical Engineering Journal (2023) Vol. 471, pp. 144362-144362
Closed Access | Times Cited: 35
Enhancing Solar Energy Conversion Efficiency: Thermophysical Property Predicting of MXene/Graphene Hybrid Nanofluids via Bayesian-Optimized Artificial Neural Networks
Dheyaa J. Jasim, Husam Rajab, As’ad Alizadeh, et al.
Results in Engineering (2024) Vol. 24, pp. 102858-102858
Open Access | Times Cited: 12
Estimating the density of hybrid nanofluids for thermal energy application: Application of non-parametric and evolutionary polynomial regression data-intelligent techniques
Mehdi Jamei, Masoud Karbasi, Mehdi Mosharaf‐Dehkordi, et al.
Measurement (2021) Vol. 189, pp. 110524-110524
Closed Access | Times Cited: 47
Prediction of Maximum Scour Depth near Spur Dikes in Uniform Bed Sediment Using Stacked Generalization Ensemble Tree-Based Frameworks
Manish Pandey, Mehdi Jamei, Masoud Karbasi, et al.
Journal of Irrigation and Drainage Engineering (2021) Vol. 147, Iss. 11
Closed Access | Times Cited: 44
Effect of Inclined Magnetic Field on the Entropy Generation in an Annulus Filled with NEPCM Suspension
Seyyed Masoud Seyyedi, M. Hashemi‐Tilehnoee, Mohsen Sharifpur
Mathematical Problems in Engineering (2021) Vol. 2021, pp. 1-14
Open Access | Times Cited: 43
Significance of chemical reaction with activation energy for Riga wedge flow of tangent hyperbolic nanofluid in existence of heat source
Sohaib Abdal, Imran Siddique, Ali Saleh Alshomrani, et al.
Case Studies in Thermal Engineering (2021) Vol. 28, pp. 101542-101542
Open Access | Times Cited: 43
Impact of sonication durations on thermophysical properties, contact angle and surface tension of f-MWCNTs nanofluid for heat transfer
Zafar Said, Maham Aslam Sohail, Rashmi Walvekar, et al.
Journal of Molecular Liquids (2022) Vol. 358, pp. 119164-119164
Closed Access | Times Cited: 28
Employing ensemble learning techniques for modeling nanofluids' specific heat capacity
Omid Deymi, Fahimeh Hadavimoghaddam, Saeid Atashrouz, et al.
International Communications in Heat and Mass Transfer (2023) Vol. 143, pp. 106684-106684
Closed Access | Times Cited: 18
Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation
Zihao Zheng, Mumtaz Ali, Mehdi Jamei, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 185, pp. 113645-113645
Closed Access | Times Cited: 18
Melting and heat generating influences on radiative flow of two-phase magneto-Williamson nanofluid via stretchable surface with slippage velocity and activation energy
Imran Ullah, Wasim Jamshed, Nek Muhammad Katbar, et al.
Numerical Heat Transfer Part A Applications (2024), pp. 1-23
Closed Access | Times Cited: 7
Synthesis of hierarchical micro-mesoporous LDH/MOF nanocomposite with in situ growth of UiO-66-(NH2)2 MOF on the functionalized NiCo-LDH ultrathin sheets and its application for thallium (I) removal
Yan Cao, Afrasyab Khan, Tonni Agustiono Kurniawan, et al.
Journal of Molecular Liquids (2021) Vol. 336, pp. 116189-116189
Closed Access | Times Cited: 40
4E (energy, exergy, economic and environmental) investigation of LFR using MXene based silicone oil nanofluids
Mokhtar Ghodbane, Zafar Said, Arun Kumar Tiwari, et al.
Sustainable Energy Technologies and Assessments (2021) Vol. 49, pp. 101715-101715
Closed Access | Times Cited: 40
Thermal conductivity prediction of nano enhanced phase change materials: A comparative machine learning approach
Farzad Jaliliantabar
Journal of Energy Storage (2021) Vol. 46, pp. 103633-103633
Closed Access | Times Cited: 34
Investigation on two-phase fluid mixture flow, heat transfer and entropy generation of a non-Newtonian water-CMC/CuO nanofluid inside a twisted tube with variable twist pitch: Numerical and evolutionary machine learning simulation
Amin Shahsavar, Sajad Entezari, Ighball Baniasad Askari, et al.
Engineering Analysis with Boundary Elements (2022) Vol. 140, pp. 322-337
Closed Access | Times Cited: 24
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