Graphene metamaterial solar absorber using Al-TiN-Fe for efficient solar thermal energy conversion and optimization using machine learning.

The contributed absorber design in graphene addition with the displacement of three materials for resonator design in Aluminum (Al), the middle substrate position with Titanium nitride (TiN), and the ground layer deposition by Iron (Fe) respectively. For the absorption validation highlight, the best four absorption wavelengths (µm) of 0.29, 0.58, 1, and 2 are also selected to indicate the changes in radiation outputs for every observation. With the displacement of wavelength and bandwidth configuration, the current absorber is observed at 97.32% (more than 97%) for 1.5-2.5 µm wavelength range (1000 nm bandwidth) and above 95% rate (95.38%) is displayed by the 2000 nm bandwidth due to 0.5 and 2.5 µm wavelength separation. The 2800 nm band rate demonstration by 0.2-3 µm wavelength separation verifies 92.42%. For every analysis in this work, the output radiation is shown in ultraviolet region (UV), visible spectrum (Vis), and near-infrared (NIR) area respectively. In the following distribution of the current absorber, the design development in lithography and step-by-step, parametric assignment and AM configuration, radiation analysis for each parameter changes in graph presentation and conclusion. Additionally, the ML approach is applied to reduce the time required in the study. The current solar absorber in the new design can be generated for the multi-solar purposes of water heating, lighting, ventilation, charging for electronic devices, and electric vehicle transportation.