Characterisation of optical properties of solar nanofluids by an inverse problem based on a numerical model

Some nanoparticles (NPs) possess an outstanding photothermal conversion under optical illumination. For this reason, these NPs are under research in a wide variety of light-induced heating applications such as solar nanofluids, which could be used for direct light absorption in solar collectors. Experimental characterisation of solar nanofluids for their application to light-to-heat conversion processes requires a considerable amount of resources to determine the properties of this mixture, at the nanoscale level. On this ground, an inverse problem based on a high-frequency and light-to-heat finite element model is proposed in the present work to numerically predict the optical properties of these nanofluids. In particular, a cost function based on a L2 norm is formulated to compare experimental measurements and numerical predictions. Then, this function is minimised by means of heuristic techniques –specifically, genetic algorithms- and the desired properties can be determined. In conclusion, the current work presents a numerical tool that could help in the characterisation of properties of solar nanofluids and contribute to reduce the number of experiments to be conducted for this purpose.