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

Povzetek

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.

Ključne besede

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

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UNG - Univerza v Novi Gorici
UDK: 54
COBISS: 112981763 Povezava se bo odprla v novem oknu
ISSN: 2574-0970
Št. ogledov: 577
Št. prenosov: 0
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

URN: URN:SI:UNG
Vrsta dela (COBISS): Delo ni kategorizirano
Strani: str. 3416-3425
Letnik: ǂVol. ǂ4
Zvezek: ǂiss. ǂ4
Čas izdaje: Apr. 2021
DOI: 10.1021/acsanm.0c03219
ID: 15766861