Abstract

This study aims to experimentally investigate the effects of temperature and nanoparticle concentration on dynamic viscosity, which is one of the most significant thermophysical properties. Diluted water-based graphene nanoplatelets (GNP) nanofluids are prepared using a two-step approach, with concentrations ranging from 0.00005 to 0.001 vol.%. Surfactants such as Gum Arabic (GA) and Sodium dodecyl sulfate (SDS) are dispersed in the nanofluid medium at 1:1 weight ratios with respect to GNP. The suspensions are rheologically characterized from 20°C to 50°C using a rotational rheometer at shear rates ranging from 10 to 100 (s-1). The rheological behavior of GNP nanofluids is examined to ultimately develop a regression model for viscosity, that considers the effects of nanoparticle concentration and temperature for different surfactant type. Results indicate that GNP-GA and GNP-SDS nanofluids at 0.001 vol.% retained their stability over a time frame of 21 days. An increase in viscosity with the increase in nanoparticle concentration and a decrease in viscosity with the rise in temperature is reported. GNP-GA nanofluid at 0.001 vol.% concentration depicts the highest viscosity value. The rheological analysis demonstrates a Newtonian flow behavior for GNP nanofluids throughout the studied shear rate range, except for GNP-SDS nanofluids that exhibit shear thinning behavior at highest nanoparticle loading, and GNP-GA nanofluids that exhibit shear thickening behavior at the lowest nanoparticle loading. The proposed regression model has high prediction accuracy (R2>99%) for GNP nanofluids with different surfactants. The outcomes of this work are anticipated to aid several industrial and engineering applications like heat exchangers, refrigeration systems, cryogenic systems, air-conditioning units, power plants and solar panels.

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