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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:

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

Showing 1-25 of 134 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: 243
Synthesis, stability, thermophysical properties and heat transfer applications of nanofluid – A review
Bhavin Mehta, Dattatraya Subhedar, Hitesh Panchal, et al.
Journal of Molecular Liquids (2022) Vol. 364, pp. 120034-120034
Closed Access | Times Cited: 132
Nanofluids application in machining: a comprehensive review
Xiaoming Wang, Yuxiang Song, Changhe Li, et al.
The International Journal of Advanced Manufacturing Technology (2023) Vol. 131, Iss. 5-6, pp. 3113-3164
Closed Access | Times Cited: 95
Intelligent approaches for sustainable management and valorisation of food waste
Zafar Said, Prabhakar Sharma, Quach Thi Bich Nhuong, et al.
Bioresource Technology (2023) Vol. 377, pp. 128952-128952
Open Access | Times Cited: 83
Application of novel framework based on ensemble boosted regression trees and Gaussian process regression in modelling thermal performance of small-scale Organic Rankine Cycle (ORC) using hybrid nanofluid
Zafar Said, Prabhakar Sharma, Arun Kumar Tiwari, et al.
Journal of Cleaner Production (2022) Vol. 360, pp. 132194-132194
Closed Access | Times Cited: 81
Temperature field model in surface grinding: a comparative assessment
Min Yang, Ming Kong, Changhe Li, et al.
International Journal of Extreme Manufacturing (2023) Vol. 5, Iss. 4, pp. 042011-042011
Open Access | Times Cited: 75
Tribological Performance of Different Concentrations of Al2O3 Nanofluids on Minimum Quantity Lubrication Milling
Xiufang Bai, Juan Jiang, Changhe Li, et al.
Chinese Journal of Mechanical Engineering (2023) Vol. 36, Iss. 1
Open Access | Times Cited: 72
Performance characterization of a solar-powered shell and tube heat exchanger utilizing MWCNTs/water-based nanofluids: An experimental, numerical, and artificial intelligence approach
Zafar Said, S. M. A. Rahman, Prabhakar Sharma, et al.
Applied Thermal Engineering (2022) Vol. 212, pp. 118633-118633
Closed Access | Times Cited: 71
Dynamic formulation of a sandwich microshell considering modified couple stress and thickness-stretching
Meichang Zhang, Xin Jiang, Mohammad Arefi
The European Physical Journal Plus (2023) Vol. 138, Iss. 3
Closed Access | Times Cited: 61
Application of modern approaches to the synthesis of biohydrogen from organic waste
Prabhakar Sharma, Akshay Jain, Bhaskor Jyoti Bora, et al.
International Journal of Hydrogen Energy (2023) Vol. 48, Iss. 55, pp. 21189-21213
Closed Access | Times Cited: 49
Using Gaussian Process Regression (GPR) models with the Matérn covariance function to predict the dynamic viscosity and torque of SiO2/Ethylene glycol nanofluid: A machine learning approach
Xiaohong Dai, Hamid Taheri Andani, As’ad Alizadeh, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 122, pp. 106107-106107
Closed Access | Times Cited: 46
A class of promising fuel cell performance: International status on the application of nanofluids for thermal management systems
A.G.N. Sofiah, Jagadeesh Pasupuleti, M. Samykano, et al.
Materials Today Sustainability (2024) Vol. 26, pp. 100709-100709
Closed Access | Times Cited: 18
Optimizing ternary hybrid nanofluids using neural networks, gene expression programming, and multi-objective particle swarm optimization: a computational intelligence strategy
Tao Hai, Ali Basem, As’ad Alizadeh, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 2
Experimental analysis of novel ionic liquid-MXene hybrid nanofluid's energy storage properties: Model-prediction using modern ensemble machine learning methods
Zafar Said, Prabhakar Sharma, Navid Aslfattahi, et al.
Journal of Energy Storage (2022) Vol. 52, pp. 104858-104858
Closed Access | Times Cited: 65
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
Improving the thermal efficiency of a solar flat plate collector using MWCNT-Fe3O4/water hybrid nanofluids and ensemble machine learning
Zafar Said, Prabhakar Sharma, L. Syam Sundar, et al.
Case Studies in Thermal Engineering (2022) Vol. 40, pp. 102448-102448
Open Access | Times Cited: 63
Multi-objective optimization of Venetian blinds in office buildings to reduce electricity consumption and improve visual and thermal comfort by NSGA-II
Mohammadreza Baghoolizadeh, Mohammad Rostamzadeh‐Renani, Reza Rostamzadeh‐Renani, et al.
Energy and Buildings (2022) Vol. 278, pp. 112639-112639
Closed Access | Times Cited: 63
Developing gasification process of polyethylene waste by utilization of response surface methodology as a machine learning technique and multi-objective optimizer approach
Rezgar Hasanzadeh, Parisa Mojaver, Taher Azdast, et al.
International Journal of Hydrogen Energy (2022) Vol. 48, Iss. 15, pp. 5873-5886
Closed Access | Times Cited: 59
Recent progress in catalytic deoxygenation of biomass pyrolysis oil using microporous zeolites for green fuels production
Salman Raza Naqvi, Asif Hussain Khoja, Imtiaz Ali, et al.
Fuel (2022) Vol. 333, pp. 126268-126268
Closed Access | Times Cited: 57
An ANFIS-RSM based modeling and multi-objective optimization of syngas powered dual-fuel engine
Prabhakar Sharma, Bibhuti B. Sahoo
International Journal of Hydrogen Energy (2022) Vol. 47, Iss. 44, pp. 19298-19318
Closed Access | Times Cited: 56
Modeling-optimization of performance and emission characteristics of dual-fuel engine powered with pilot diesel and agricultural-food waste-derived biogas
Zafar Said, Prabhakar Sharma, Bhaskor Jyoti Bora, et al.
International Journal of Hydrogen Energy (2022) Vol. 48, Iss. 18, pp. 6761-6777
Closed Access | Times Cited: 53
Using Bayesian optimization and ensemble boosted regression trees for optimizing thermal performance of solar flat plate collector under thermosyphon condition employing MWCNT-Fe3O4/water hybrid nanofluids
Zafar Said, Prabhakar Sharma, L. Syam Sundar, et al.
Sustainable Energy Technologies and Assessments (2022) Vol. 53, pp. 102708-102708
Closed Access | Times Cited: 47
Thermal and rheological properties of magnetic nanofluids: Recent advances and future directions
Sithara Vinod, John Philip
Advances in Colloid and Interface Science (2022) Vol. 307, pp. 102729-102729
Closed Access | Times Cited: 45
Using response surface methodology approach for optimizing performance and emission parameters of diesel engine powered with ternary blend of Solketal-biodiesel-diesel
Prabhakar Sharma, Minh Phung Le, Ajay Chhillar, et al.
Sustainable Energy Technologies and Assessments (2022) Vol. 52, pp. 102343-102343
Closed Access | Times Cited: 44
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
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