Abstract

Abstract Nanofluids, which are suspension of nanoparticles in base fluids, have been found to enhance the properties of the conventional fluids for heat transfer applications. Research reveals that the greater thermal conduction effect of the selected base fluids has become enormously dominant when nanoparticles of metals, metal oxides and their hybrids are added to these base fluids. The possible reason behind this drastic change can be attributed to the large surface to volume ratio and high physicochemical properties viz.: thermal conductivity, rheology, viscosity, electrical conductivity and molar densities of the dispersed nanoparticles. Keeping this novel application in mind, the present research work reports the preparation of copper oxide nanofluids (CuONF) for heat transfer application using two-step method. At first, the copper oxide nanoparticles (CuONP) were synthesized using wet chemical (precipitation) method. Purified CuONP was characterised using UV-visible spectrophotometer (350 nm), High Resolution Transmission Electron Microscopy revealed the rod-shaped and polycrystalline nature of the nanoparticles (6nm to 15 nm sizes). Pure Monoclinic phase of CuONP was observed from Powder X-ray Diffraction studies with average grain size of 10 nm. Fourier Transformed-Infrared spectroscopy also revealed the presence of pure monoclinic phase of CuONP with bands at 538 cm-1 and 595 cm-1. In the second step, the tested CuONP was dispersed in ethylene glycol as base fluid at variable concentrations. Electrical, rheological, viscometric and density properties of CuONP nanofluids were studied at variable temperature and pH conditions. Conductivity studies showed the increase in conductivity of CuONP nanofluids with increase in temperature and volume concentrations. Rheological studies revealed the Newtonian behaviour of the prepared CuONP nanofluids. Thermophysical properties, viscosity and density increased with increase in volume concentration (0.01%-0.1%) and decreased with increase in temperature (25°C-65°C). Data validation was done using theoretical models.

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