Metamaterial as perfect absorber for high sensitivity refractive index based biosensing applications at infrared frequencies

Abstract In this paper, we introduce a novel design of a metamaterial unit cell absorber, which is based on a metal/insulator/metal sandwich structure. The design is subjected to comprehensive finite element method computational analysis to ensure accurate and reliable results. The proposed metamaterial sandwich structure demonstrates exceptional absorption performance, achieving a nearly perfect absorption rate of 99.996% at the resonance infrared frequency of 39.8 THz. To provide a detailed theoretical explanation of nearly perfect absorption, we employ the effective medium theory, impedance matching, and field distribution analysis. Additionally, we have optimized the structural parameters of the sensor to maximize its absorption peak. This includes optimizing the thickness of the gold (Au) layer (from 0.03 to 0.28 μ m), the distance between the L shape corners (from 0.60 to 0.90 μ m), and the thickness of SiC dielectric spacer (from 0.20 to 0.45 μ m). Furthermore, we showcase the remarkable sensitivity of the proposed metamaterial unit cell in detecting subtle changes in the refractive index through the implementation of a sensing medium setup in our model. Remarkably, we achieve a frequency shift sensitivity of 3.74 THz/RIU, along with a quality factor of 10.33, for a wide range of refractive indices (1.0–2.0). Moreover, for cancer detection, we attain a sensitivity of 3.5 THz/RIU. These findings highlight the exceptional performance of our approach in accurately detecting changes in refractive index, making it a promising candidate for various sensing applications. The novelty of our work lies in the design of a metamaterial unit cell structure. This configuration exhibits several noteworthy features, including wide incident angle ( θ ) coverage up to 60°, polarization insensitivity, exceptional frequency shift sensitivity, high absorption peaks across a wide range of refractive indices, and the ability to distinguish cancer cells from healthy ones.