Rheological Profile of Surfactant-Free Non-Newtonian MWCNT-Oil Hybrid Nanofluids with Carbon Nanofiber Additives

The tremendous potential of nanofluid technology has been demonstrated in several applications, including lubrication and thermal control. The rheological profile of the hybrid nanofluid (NF) must be thoroughly examined to elucidate the fluid flow behavior. The rheological characteristics of carbon nanofiber and multiwalled carbon nanotube (CNF-MWCNT) dispersions in thermal oil are evidenced by this investigation. Both nanomaterials are known to have high thermal conductivity. However, limited attention has been given to the flow behavior characteristics in non-Newtonian fluids. Several characterizations of nanomaterials were carried out to assess the morphology and stability in thermal oil. To achieve high stability, a combination of stabilizer addition and ultrasonication was used. Different concentrations (0.5, 0.8, 1.0, 1.2, 1.5%) of hybrid nanofluids were used to inspect the impact of shear rate and viscosity in the experimental study. A broad shear range of 30-2000 s<sup>-1</sup> and five distinct temperatures, ranging from 25 to 65 °C, were used to measure the viscosity trend of all concentrations of MWCNT+CNF in thermal oil. It exhibited non-Newtonian fluid behavior, following shear-thinning characteristics. The effects of the temperature, concentration, and shear rate are all considered in a parametric study of rheological behavior. The modeling of flow behavior indicates that the nanofluids followed Herschel-Bulkley's model; however, the pure thermal oil follows Power law behavior. The machine learning approach, i.e., ANN modeling, was used to build a model and optimize it using a feed-forward multilayer perceptron method to predict the viscosity of the hybrid nanofluids using experimental data. The model's performance was assessed, and the expected outcomes showed excellent agreement with the experiment, with an <i>R</i> <sup>2</sup> of 99.99%. This result indicates the importance of the rheological behavior of hybrid NFs with non-Newtonian behavior for their application in heat transfer and lubrication.

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Journal
ACS Omega
Published
2025-07-21
DOI
https://doi.org/10.1021/acsomega.4c10749
Citations
1
Primary Topic
Nanofluid Flow and Heat Transfer
Type
article
Field-Weighted Citation Impact
0.67

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article

Rheological Profile of Surfactant-Free Non-Newtonian MWCNT-Oil Hybrid Nanofluids with Carbon Nanofiber Additives

Anas Ahmed, Noor e Hira, Mustafa Alsaady, Serene Sow Mun Lock et al.
1 citations
ACS Omega
Nanofluid Flow and Heat Transfer
0.67
article

Rheological Profile of Surfactant-Free Non-Newtonian MWCNT-Oil Hybrid Nanofluids with Carbon Nanofiber Additives

Anas Ahmed, Noor e Hira, Mustafa Alsaady, Serene Sow Mun Lock, Aymn Abdulrahman, Suhaib Umer Ilyas, Ahmed Aljehani
article en
1 citations

Abstract

The tremendous potential of nanofluid technology has been demonstrated in several applications, including lubrication and thermal control. The rheological profile of the hybrid nanofluid (NF) must be thoroughly examined to elucidate the fluid flow behavior. The rheological characteristics of carbon nanofiber and multiwalled carbon nanotube (CNF-MWCNT) dispersions in thermal oil are evidenced by this investigation. Both nanomaterials are known to have high thermal conductivity. However, limited attention has been given to the flow behavior characteristics in non-Newtonian fluids. Several characterizations of nanomaterials were carried out to assess the morphology and stability in thermal oil. To achieve high stability, a combination of stabilizer addition and ultrasonication was used. Different concentrations (0.5, 0.8, 1.0, 1.2, 1.5%) of hybrid nanofluids were used to inspect the impact of shear rate and viscosity in the experimental study. A broad shear range of 30-2000 s<sup>-1</sup> and five distinct temperatures, ranging from 25 to 65 °C, were used to measure the viscosity trend of all concentrations of MWCNT+CNF in thermal oil. It exhibited non-Newtonian fluid behavior, following shear-thinning characteristics. The effects of the temperature, concentration, and shear rate are all considered in a parametric study of rheological behavior. The modeling of flow behavior indicates that the nanofluids followed Herschel-Bulkley's model; however, the pure thermal oil follows Power law behavior. The machine learning approach, i.e., ANN modeling, was used to build a model and optimize it using a feed-forward multilayer perceptron method to predict the viscosity of the hybrid nanofluids using experimental data. The model's performance was assessed, and the expected outcomes showed excellent agreement with the experiment, with an <i>R</i> <sup>2</sup> of 99.99%. This result indicates the importance of the rheological behavior of hybrid NFs with non-Newtonian behavior for their application in heat transfer and lubrication.

ACS OmegaVol. 10(29)
Monash University Malaysia (MY), Universiti Teknologi Petronas (MY), University of Jeddah (SA), Industrial Systems and Control (United Kingdom) (GB), Carbon Capture & Storage Association (GB)
University of Jeddah
Openalex Percentile: Top 29%
Nanofluid Flow and Heat Transfer
0.67
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