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Thermal Conductivity of Multiwalled Carbon Nanotubes‐Kapok Seed Oil‐Based Nanofluid
Author(s) -
Ul Islam Badar,
Mukhtar Ahmad,
Saqib Sidra,
Mahmood Abid,
Rafiq Sikander,
Hameed Ayesha,
Khan Muhammad Saad,
Hamid Khalid,
Ullah Sami,
Al-Sehemi Abdullah G.,
Ibrahim Muhammad
Publication year - 2020
Publication title -
chemical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 81
eISSN - 1521-4125
pISSN - 0930-7516
DOI - 10.1002/ceat.201900600
Subject(s) - nanofluid , thermal conductivity , materials science , carbon nanotube , artificial neural network , dispersion (optics) , thermal , base (topology) , nanoparticle , chemical engineering , composite material , nanotechnology , thermodynamics , computer science , mathematics , artificial intelligence , engineering , physics , optics , mathematical analysis
The synthesis of a nanofluid from multiwalled carbon nanotubes (MWCNTs) and Kapok seed oil by a one‐step method is reported. The nanofluid showed excellent stability of nanoparticle dispersion in the base fluid. Furthermore, this study deals with the prediction of the thermal conductivity of the MWCNTs‐kapok seed oil nanofluid. To improve the prediction of the thermal conductivity of the nanofluid, the artificial neural network (ANN) computing approach was used with different algorithms including the back‐propagation, Levenberg‐Marquardt, and genetic algorithm (GA). Finally, the ANN‐GA model is recommended for the prediction of thermal conductivity with higher accuracy.