Design of a highly efficient graphene-coated ultra-wideband solar thermal absorber for renewable mining energy applications using artificial intelligence optimization.

Although many technologies have advanced in electricity production, their carbon footprint remains a crucial factor in selecting the most sustainable option. Solar energy provides a promising solution, as it is a clean and renewable resource harnessed directly from the sun. Multi-layer type thermal absorbers are considered the most effective structures, and their efficiency can be further enhanced with the incorporation of advanced materials such as graphene and MXene. In the current study, the solar absorber is fabricated using Cr-Fe₃O₄-InSb materials, with a thin graphene film added to enhance overall thermal performance. The design features two square structures with a cylindrical resonator inserted at the center. The proposed structure achieves an impressive thermal absorption rate of 93.28% through a broad wavelength range of up to 2800 nm. Specifically, the structure can be configured to achieve a thermal absorption rate of 90.9%, 93.32%, and 94.72% for UV-Vis-NIR regions while maintaining these rates across the respective ranges: 90.9% in the ultraviolet, 93.32% in the visible, and 94.72% in the NIR, with the polarization-insensitive property applicable for incidence angles from 0 to 80 degrees. To extract precise performance values based on regression analysis for varying layer heights, machine learning techniques for a 0.25 test size and the R² value reach above 0.98. As a thermal energy innovation, the proposed absorber can be utilized in various thermal processes, including water heaters, cookers, solar ponds, fuel production, coffee roasters, swimming pool heating, and more.