Experimental and molecular-level insights into thermal conductivity of cobalt hydroxychloride nanofluids

Abstract

This study reports the influence of shape and size on the thermal conductivity of cobalt hydroxychloride (Co2(OH)3Cl) nanofluids synthesised via a low temperature hydrothermal precipitation process at varying propanol concentrations ranging from 0 % to 100 %. The structural and morphological properties of resulting powders were analysed using XRD, FTIR, and HRTEM. Thermal conductivity analysis was performed at temperature from 298 K to 318 K using a steady state cylindrical guarded hot plate method. Equilibrium molecular dynamics with the Green–Kubo method were utilised to obtain further insight into the thermal conductivity enhancement, simulating spherical, rhombus nanoplates and a mixed system. XRD confirmed the presence of Co2(OH)3Cl with varying purities depending on propanol concentration; higher concentrations (70–100 %) yielded purer phases. Morphological analysis using HRTEM revealed hexagonally shaped Co2(OH)3Cl nanoplates with average sizes ranging from 85 to 55 nm at propanol concentrations below 50 %. In contrast, spherical Co2(OH)3Cl nanoparticles and rhombus-shaped nanoplates, with average sizes ranging from 23 to 10 nm, were formed at propanol concentrations ranging from 70 % to 100 %. Higher propanol concentration therefore restricts particle growth and promotes shape transition from nanoplates to nanospheres. A reduction in nanoparticle size and rise in temperature resulted in enhancing the thermal conductivity of the obtained nanofluids. At 318 K, a thermal conductivity enhancement of 17.7 % was achieved at nanoparticle sizes below 10 nm. The equilibrium molecular dynamics study confirmed that the observed 17.7 % enhancement in thermal conductivity could be credited to the combination of nanoparticle shapes at very narrow particle sizes. This study highlights the significant impact of nanoparticle size and shape on the thermal conductivity of novel Co2(OH)3Cl nanofluids and pave a way to optimising nanofluid performance based on EMD studies prior to synthesis.