Constrained multi-objective optimization problem model to design multi-band terahertz metamaterial absorbers

Abstract

The multi-band metamaterial absorbers studied today offer optimal sensing performance by maximizing the absorption at resonance frequencies. A constrained multi-objective optimization problem (CMOP) model is proposed to intelligently obtain the optimized geometrical parameters of the designed MA for optimal multi-band absorption. The proposed multi-band terahertz metamaterial absorber is formed by a patterned metallic patches (symmetric snowflake-shaped resonators) layer and a continuous metallic layer separated by a dielectric layer. The simulation results show that there are three discrete narrow resonance peaks with the absorption of 99.1%, 90.0%, and 99.9% in the range of 0.5–2 THz after being optimized by the proposed CMOP model. The reflection loss of all resonance modes is improved significantly compared with the conventional brute-force approach. Specifically, reflection loss at the highest resonance frequency is suppressed from -6.76 dB to -28.17 dB. Consequently, the reported MA design can be used as a refractive index sensor with the highest sensitivity of 495 GHz/RIU and the figure of merit (FoM) of 8.9 RIU−1 through a refractive index ranging from 1.0 to 1.6 at the analyte thickness of 18.5 μm. It is worth noting that most of the liquid samples have a refractive index ranging from 1.0 to 1.6. Therefore, the reported sensor can be used for liquid detection with high sensitivity.