A broadband thin film plasmonic metamaterial absorber nanostructure that operates in the frequency range from 100 GHz to 1000 GHz is introduced and analyzed in this paper. The structure consists of three layers: a 200 nm thick gold layer that represents the ground plate (back reflector), a dielectric substrate, and an array of metallic nanorods. A parametric study is conducted to optimize the structure based on its absorption property using different materials, gold (Au), aluminum (Al), and combined Au, and Al for the nanorods. The effect of different dielectric substrates on the absorption is examined using silicon dioxide (SiO2), aluminum oxide (Al2O3), titanium dioxide (TiO2), and a combination of these three materials. This was followed by the analysis of the effect of the distribution of Al, and Au nanorods and their dimensions on the absorption. The zinc oxide (ZnO) layer is added as a substrate on top of the Au layer to enhance the absorption in the microwave range. The optimized structure achieved more than 80% absorption in the ranges 100–280 GHz, 530–740 GHz and 800–1000 GHz. The minimum optimized absorption is more than 65% in the range 100 GHz to 1000 GHz.
A low-cost Si-based optical nano-sensor that monitors traditional water pollutants is introduced in this paper. The introduced sensor works in the near-infrared region, 900 nm to 2500 nm spectral range. The proposed structure consists of a Si layer with an optimized thickness of 300 nm on the top of the Al layer acting as a back reflector. On the top of the Si layer, the water pollutants are modeled as nanoparticle materials of different sizes. The finite difference time domain method is utilized to optimize the thicknesses of the Si layer by analyzing the optical light absorption considering different Si layer thicknesses and different pollutant nanoparticles’ sizes. Different interpolation techniques, including polynomials with various degrees and locally weighted smoothing quadratic regression, are used to find the best fitting model representing the simulated data points with goodness of fit analysis. Three features are proposed to identify the water pollutant with its size, peak absorption wavelength, relative amplitude, and a full width at half maximum. The device’s performance in detecting six different pollutants, silver, aluminum, copper, chromium, selenium, and ammonia, is evaluated. Sensitivity, a figure of merit, and a quality factor are used to evaluate the proposed sensor. The obtained maximum sensitivity is 11,300 nm/RIU, FOM of 740, and quality factor of 670.
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