# Hypersentized Metamaterials Based on a Corona-Shaped Resonator for Efficient Detection of Glucose
## 4 Numerical and Experimental Studies of the Proposed Sensor for Glucose Detection  
The designed (MTM) metamaterials corona-shaped sensor was simulated by the CST Studio suite electromagnetic solver. When the sensing layer was filled with air, the reflection coefficient (S\({}_{11}\)) and transmission coefficient (S\({}_{21}\)) were monitored over the frequency range of 1-8 GHz, as shown in Figure 6. It can be noted from Figure 6a that the S\({}_{11}\) had two resonance frequencies at 3.6 GHz and 6.2 GHz with \(-32\) dB and \(-26\) dB, respectively. These correspond to the two maximal values of the transmission coefficient at the same frequencies in Figure 6b. These two sharp peaks of the transmission and reflection coefficient are considered to be one of the important advantages of the proposed design, which helps to detect any trivial shift/change in the resonance frequency. In order to optimize the performance of the proposed sensor, a parametric study was performed to tune the sensor dimensions. For this purpose, the overall dimensions of the proposed structure were optimized by using a genetic algorithm technique, which is a built-in function in the CST software. To address the effects of changing the dimensions of the proposed sensor, the most influential parameters, which are the width of the outer ring resonator radius (Ro), transmission line width (WTI) and sensor layer radius (Rs), were investigated, as shown in Figures 7-9. Figure 5: The complex permittivity of glucose-blood mixture: (**a**) measured real part, (**b**) calculated real part, (**c**) measured imaginary part and (**d**) calculated imaginary part. From the studied results, a clear shift in the resonance frequencies of the reflection coefficient to the upper-frequency limit was noted when the value of Ro was increased from 9.5 mm to 11.5 mm, as shown in Figure 7. Besides, the Ro increment led to the amplitude variation and increment of the resonance frequency of the transmission coefficient. The effects of changing the transmission line width (WTI) from 0.5 to 2.5 mm are presented in Figure 8. As can be seen from the figure, with WTI decrement in 0.5 steps, the resonance frequency of the reflection coefficient increased by a small amount. Noticeably, the amplitude of the transmission coefficient was reduced with this WTI reduction, while this had a very small effect on the resonance frequency shift of the transmission coefficient. Figure 9 shows the variation of the resonance frequency and amplitude of the reflection coefficient and transmission coefficient of the proposed sensor when the sensor layer radius was changed from 8.4 to 9.6 mm in 0.3 mm steps. The result showed that there is a direct proportionality relation between the sensor layer radius and the resonance frequency of the reflection coefficient. When the radius is increased, the resonance frequency is also increased linearly by about 100 MHz in each step. Consequently, based on the optimization of the genetic algorithm technique, the optimum values of the outer ring resonator radius  
Figure 6: Simulated results of the reflection and transmission coefficients for the proposed corona-shaped sensor when the sensor layer was filled with air: (**a**) in dB and (**b**) in magnitude. Figure 7: Effect of the width of the outer ring resonator radius on the resonant frequency of (**a**) reflection and (**b**) transmission spectra. In conclusion, it can be said that the positions of the resonance frequencies are mostly affected by the outer ring resonator radius (\(R_{\rm o}\)) and the sensor layer radius. This implies that these two parameters are the most influential parameters of the proposed structure, as they are highly related to the investigated samples. Consequently, any minor change in the electrical characteristics of the samples led to the shift in resonance frequency. The measurements were run seven times sequentially and the average of the measurements was taken. Hence, the standard deviation of the measurements is represented by error bars on the corresponding plots.