Journal
ADVANCED THEORY AND SIMULATIONS
Volume 5, Issue 8, Pages -Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/adts.202200139
Keywords
artificial intelligence; metamaterials; optimization; solar energy conversion
Categories
Funding
- Department of Science and Technology (DST), Government of India [MU/NewGen/2020/3]
Ask authors/readers for more resources
A highly efficient psi-shaped solar energy absorber has been developed, which achieves a near-perfect ultrawideband absorption spectrum under solar radiation. The absorber has an average absorption of 97.04% in the observed range and achieves absorption rates above 90% and 95% for bandwidths of 3730 nm and 2500 nm, respectively. It has a polarization-insensitive absorption response and is wide-angle from 0 degrees to 50 degrees. Experiments show that using a random restart hill climbing optimization approach can significantly reduce the computing power and time requirements of the simulation process by 97.57%.
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 degrees to 50 degrees. 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%.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available