Abstract
A terahertz sensor structure is proposed that can sense any variations in analyte permittivity. The sensor essentially works according to the shifts in the resonance frequencies of its propagated spoof surface plasmonic modes. The proposed structure shows great support for surface plasmon oscillations, which is proved by the calculated dispersion diagram. To achieve this in terahertz frequencies, a metamaterial structure is presented in the form of a structure with two-dimensional periodic elements. Afterward, it is shown that the performance of the sensor can be affected by different parameters such as metal stripe thickness, length of metal stripe, and width of metal stripe as the most influential parameters. Each of the parameters mentioned can directly influence on the electric field confinement in the metal structure as well as the strength of propagation modes. Therefore, two propagation modes are compared, and the stronger mode is chosen for sensing purposes. The primary results proved that the quality factors of the resonances are substantially dependent on certain physical parameters. To illustrate this, a numerical parametric sweep on the thickness of the metal stripe is performed, and the output shows that only for some specific dimensions the electromagnetic local field binds strongly with the metal part. In a similar way, a sweeping analysis is run to reveal the outcome of the variation in analyte permittivity. In this section, the sensor demonstrates an average sensitivity value, ~1,550 GHz/Permittivity unit, for a permittivity range between 1 and 2.2, which includes the permittivity of many biological tissues in the terahertz spectrum. Following this, an analysis is presented, in the form of two contour plots, for two electrical parameters, maximum electric field and maximum surface current, based on 24 different paired values of metal thickness and metal width as the two most critical physical parameters. Using the plotted contour diagrams, which are estimated using the bi-harmonic fitting function, the best physical dimension for the maximum capability of the proposed sensor is achieved. As mentioned previously, the proposed sensor can be applied for biological sensing due to the simplicity of its fabrication and its performance.