Design of Quadra Halo-shaped wideband solar thermal absorber optimized with machine learning for renewable energy harvesting
Raj Agravat, Shobhit K. Patel, Abdullah Baz
Abstract
Examined numerous solar absorber architectures composed of diverse materials to optimize energy production and decrease loss of energy throughout the framework of renewable energy sources, particularly solar energy. This paper shows the MXene-based Quadra Halo-shaped Solar Absorber (MQHSA), where a simple resonator geometry traps the ultra-broadband 510 and 1170 nm bandwidth absorptance with 94.16 average absorptance in the area of UV to IR spectrum, and MQHSA has achieved 99.98% maximum absorption in the range of 200 to 4000 nm wavelength. Sn and SiO 2 are considered the back and substrate layer of MQHSA, and MXene is used in the resonator. Polarization-insensitive MQHSA achieved 94.7% absorptance under the AM 1.5 setup. Further, discussed the MQHSA Transverse Electric (TE) and (TM) and optimized with Machine Learning (ML) to predict the outcome, and enhanced the result of MQHSA, achieving a 0.999632 value of R 2 , and achieved 9.783982 x 10 -7 mean square error, and enhanced the performance. Study the MQHSA wide-incident angle and the Electric intensity field. Higher absorption with a polarization-insensitive structure, MQHSA is utilized for a renewable energy harvester.