DESIGN AND PERFORMANCE EVALUATION OF A TERAHERTZ METAMATERIAL BIOSENSOR FOR TUBERCULOSIS DETECTION

Abstract

For the label-free and non-invasive detection of Tuberculosis (TB) cells, this work presents a detailed computational study of a highly sensitive Terahertz (THz) metamaterial (MM) based biosensor. The proposed structure are simulated and analyzed using CST Studio Suite. The finite element method (FEM) along with a frequency-domain electromagnetic (EM) solver are used to evaluate its performance characteristics. The proposed unit cell is consists of a ground plane made up of gold, an inexpensive dielectric substrate which is made up of paper material, and a top resonator which consists of two brick-shaped structure along with three closed circular ring structures placed between them. This resonator structure is made up of Vanadium dioxide (VO2). The absorptivity curves are also evaluated by varying several geometrical parameters, such as the substrate thickness, the separation between the two bricks, and the radii of the rings etc. The optimized design achieves 99.88 % absorption at a resonance frequency of 3.3777 THz. The sensing mechanism of the proposed sensor relies on the strong localization of electric and magnetic fields within the analyte layer at resonance. Consequently, small variations in the optical properties of the analyte sample, especially changes in the refractive index, can be accurately detected. A noticeable redshift in the resonant frequency is observed with the increase in the refractive index of the analyte, indicating a high sensitivity of the sensor to variations in the surrounding dielectric environment and enabling effective detection of TB cells. The proposed sensor exhibits clear resonance frequency variations in response to changes in the analyte, achieving a maximum sensitivity of 700 GHz/RIU for TB1. In addition, the highest quality factor (Q-factor) and figure of merit (FOM) values obtained are 16.2633 for TB4 and 3.4516 RIU-1 for TB1, respectively. These results indicate that the developed design has strong potential to be utilized as an effective computational platform for future development, fabrication, and experimental assessment of THz biosensors.