Novel sampling procedure and statistical analysis for the thermal characterization of ionic nanofluids

Abstract

An efficient storage system is crucial for the effective implementation of renewable energies in the energy ecosystem, required to mitigate the climate change and to reach the European Green Deal. Nanofluids features improved thermal properties, being able to store unexpected amount of energy by adding around 1 wt% nanoparticles at the base fluid. Therefore, nanofluids become more attractive for their implementation as Thermal Energy Storage (TES) medium or Heat Transfer Fluid (HTF). However, the main drawbacks of nanofluids are the lack of consensus on a theoretical explanation of this behaviour, and the controversial lack of uniformity of the thermophysical experimental results in the literature. The goal of this work is to develop and perform a study of the thermophysical properties of several nanofluid samples and the subsequent statistical analysis. To achieve this objective, three batches of 24- samples were analysed: NaNO3 based nanofluids with three types of nanoparticles (1% wt.): SiO2, Al2O3 and clay. The statistical analysis indicates that nanoparticles have a low impact in the melting enthalpy and melting temperature and a strong impact in the specific heat capacity (Cp). The most remarkable result is the high dispersion of Cp values despite considering the sampling procedure. This fact agrees with the high variability of results found in the literature. Finally, the methodology proposed in this work may facilitate the comparison among measured results and literature results.