Design and development of ultra-broadband hexagonal-shaped MXene-based metamaterial solar absorber optimized by machine learning for renewable energy applications

Abstract To optimise the production of energy and minimise energy loss concerning the availability of of green energy, especially solar energy, a number of sun light absorber prototypes composed of various materials were examined. Tungsten and MXene serve as components in the Hexagonal with Square-shaped Resonator Metamaterial MXene-based Solar Absorber (HWSRMMSA), the resonator with a hexagonal and square form. The substrate of the recommended HWSRMMSA solar absorber was SiO2, in contrast to the bottom layer was Fe. Polarization is important for this ultra-wideband HWSRMMSA, which has a wide bandwidth is 2020 and 1140 nm with 91% and 96% absorptance at 200–4000 nm wavelength. Permittivity characteristics, refractive index, and permeability were among the negative metamaterial consequences of the HWSRMMSA that expanded reliability and absorptance. According to the calculation, the maximum possible R2 value of 0.999551 for HWSRMMSA parameter modification in the ML (machine learning) model, using liner regression aims to reduce simulation duration by a quarter within comparison to previous techniques while lowering other simulation requirements. Finally, the previously described absorber was used to observe and compare, the HWSRMMSA Electric intensity studied and described. Because of its outstanding absorptance, and surface plasmon resonance with ultra-broadband, this HWSRMMSA has been utilized in solar water heaters.