Optimization of Metamaterial‐Based Solar Energy Absorber for Enhancing Solar Thermal Energy Conversion Using Artificial Intelligence. Issue 8 (12th May 2022)

• Record Type: Journal Article
• Authors: Patel, Shobhit K.; Surve, Jaymit; Katkar, Vijay; Parmar, Juveriya
• Is Part Of: Advanced theory and simulations. Volume 5:Issue 8(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-12
• Subjects: artificial intelligence -- metamaterials -- optimization -- solar energy conversion; Science -- Simulation methods -- Periodicals; Science -- Methodology -- Periodicals; Engineering -- Simulation methods -- Periodicals; Engineering -- Methodology -- Periodicals; 507.21
• DOI: 10.1002/adts.202200139
• Languages: English
• ISSNs: 2513-0390

Abstract

Abstract: A highly efficient psi‐shaped solar energy absorber in the paper is developed. This structure is designed using titanium‐based psi shaped resonator, SiO2 based substrate, and Tungsten metal‐based base layer to achieve a near‐perfect ultrawideband absorption spectrum under solar radiation. The average absorption of 97.04% is achieved in the observed range including the ultraviolet to mid‐infrared regimes and the ultrawideband characteristics are also achieved. It is also noted that for the bandwidth of 3730 and 2500 nm, above 90% and 95% absorption rate are achieved, respectively. The effect of several design parameters on the spectrum of absorption is explored and accordingly, optimized design is identified. Furthermore, the absorption response of the developed solar energy absorber is polarization‐insensitive and wide‐angle from 0° to 50°. Experiments are meant to identify the optimal parameter values for solar absorber design by employing a random restart hill climbing optimization approach. According to the experimental data, this strategy can reduce the computing power and time requirements of the simulation process by 97.57%. Abstract : Psi shaped solar energy absorber with the average absorption of 97.04% in the spectrum 0.2–4 µm with above 95% and 90% absorption rate for 2500 and 3730 nm bandwidth, respectively is developed with wide‐angle and polarization‐independent characteristics. Artificial Intelligence based random restart hill climbing method is employed to reduce the computational power and simulation process by 97.57%.