Thermal lensing of multi-walled carbon nanotube solutions as heat transfer nanofluids

Mohanachandran Nair Sindhu Swapna (Author), Vimal Raj (Author), Humberto Cabrera (Author), Sankaranarayana Iyer Sankararaman (Author)

Abstract

This paper unwraps nanofluids’ particle dynamics with multi-walled carbon nanotubes (MWCNTs) in base fluids such as acetone, water, and ethylene glycol. Having confirmed the morphology and structure of the MWCNTs by field emission scanning electron microscopy, X-ray diffraction, and Raman spectroscopic analyses, the nanofluids are prepared in three different concentrations. The nonzero absorbance at the laser wavelength, revealed through the UV−visible spectrum, makes the thermal diffusivity study of the sample by the sensitive nondestructive single beam thermal lens (TL) technique possible. The TL signal analysis by time series and fractal techniques divulges the complex particle dynamics, through phase portrait, sample entropy, fractal dimension, and Hurst exponent. The study unveils the effect of the amount of nanoparticles and the viscosity of the medium on thermal diffusivity and particle dynamics. The observed inverse relation between thermal diffusivity and viscosity is in good agreement with the Sankar−Swapna model. The complexity of particle dynamics in MWCNT nanofluids reflected through sample entropy, and fractal dimension shows an inverse relation to the base fluid’s viscosity. This paper investigates the role of viscosity of the base fluid on particle dynamics and thermal diffusivity of the nanofluid to explore its applicability in various thermal systems, thereby suggesting a method to tune the sample entropy through proper selection of base fluid.

Keywords

MWCNT;thermal lens;fractals;nonlinear time series;phase portrait;sample entropy;

Data

Language:	English
Year of publishing:	2021
Typology:	1.01 - Original Scientific Article
Organization:	UNG - University of Nova Gorica
UDC:	54
COBISS:	112981763
ISSN:	2574-0970
Views:	577
Downloads:	0
Average score:	0 (0 votes)
Metadata:

Other data

URN:	URN:SI:UNG
Type (COBISS):	Not categorized
Pages:	str. 3416-3425
Volume:	ǂVol. ǂ4
Issue:	ǂiss. ǂ4
Chronology:	Apr. 2021
DOI:	10.1021/acsanm.0c03219
ID:	15766861