dc.contributor.author |
Alqaed, Saeed
|
|
dc.contributor.author |
Mustafa, Jawed
|
|
dc.contributor.author |
Sharifpur, Mohsen
|
|
dc.contributor.author |
Cheraghian, Goshtasp
|
|
dc.date.accessioned |
2023-09-27T05:02:46Z |
|
dc.date.available |
2023-09-27T05:02:46Z |
|
dc.date.issued |
2022-08 |
|
dc.description.abstract |
Viscosity shifts the flow features of a liquid and
affects the consistency of a product, which is a primary
factor in demonstrating forces that should be overcome
when fluids are transported in pipelines or employed
in lubrication. In carbon-based materials, due to their
extensive use in industry, finding the simple and reliable
equations that can predict the rheological behavior is
essential. In this research, the rheological nature of graphene/
aqueous nanofluid was examined. Fourier transform
infrared spectroscopy, dynamic light scattering,
energy-dispersive X-ray spectroscopy, and X-ray powder
diffraction were used for analyzing the phase and structure.
Transmission electron microscopy and field emission
scanning electron microscopy were also employed
for micro and nano structural-study. Moreover, nanofluid
stability was examined via zeta-potential measurement.
Results showed that nanofluid has non-Newtonian nature,
the same as the power-law form. Further, from 25 to 50°C,
at 12.23 s−1, viscosity decreased by 56.9, 54.9, and 38.5%for
1.0, 2.0, and 3.5 mg/mL nanofluids, respectively. From 25
to 50°C, at 122.3 s−1, viscosity decreased by 42.5, 42.3, and
33.3% for 1.0, 2.0, and 3.5mg/mL nanofluids, respectively.
Besides, to determine the viscosity of nanofluid in varied
temperatures and mass concentrations, an artificial neural
network via R2 = 0.999 was applied. Finally, the simple
and reliable equations that can predict the rheological
behavior of graphene/water nanofluid are calculated. |
en_US |
dc.description.department |
Mechanical and Aeronautical Engineering |
en_US |
dc.description.librarian |
am2023 |
en_US |
dc.description.sponsorship |
The Deanship of Scientific Research at Najran University and the German Research Foundation (DFG). |
en_US |
dc.description.uri |
https://www.degruyter.com/journal/key/ntrev/html |
en_US |
dc.identifier.citation |
Alqaed, S., Mustafa, J., Sharifpur, M. et al. 2022, 'The effect of graphene nano-powder on the viscosity of water : an experimental study and artificial neural network modeling', Nanotechnology Reviews, vol. 11, pp. 2768-2785. DOI : 10.1515/ntrev-2022-0155. |
en_US |
dc.identifier.issn |
2191-9089 (print) |
|
dc.identifier.issn |
2191-9097 (online) |
|
dc.identifier.other |
10.1515/ntrev-2022-0155 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/92423 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
De Gruyter |
en_US |
dc.rights |
© 2022 Saeed Alqaed et al., published by De Gruyter.
This work is licensed under the Creative Commons Attribution 4.0. |
en_US |
dc.subject |
Graphene nano-powder |
en_US |
dc.subject |
Viscosity |
en_US |
dc.subject |
Correlation |
en_US |
dc.subject |
Flake graphite |
en_US |
dc.subject |
Artificial neural network (ANN) |
en_US |
dc.title |
The effect of graphene nano-powder on the viscosity of water : an experimental study and artificial neural network modeling |
en_US |
dc.type |
Article |
en_US |