Numerical Simulation of Tunable Terahertz Graphene-Based Sensor for Breast Tumor Detection

This article presents a modeling and analysis of a tunable graphene-based sensor for breast tumor detection operating in the terahertz frequency range using the wave concept iterative process (WCIP) method. Through the novel implementation approach of the biological tissues in the WCIP method, we can integrate the normal and tumor of human breast tissues into this algorithm. At the beginning, the details of the algorithms of human breast tissue and graphene modeling in the WCIP method are presented. In order to verify the results obtained by the WCIP algorithm, we presented a comparative study with the CST simulator. Then, using the WCIP method, the numerical simulation results demonstrate the capability of the proposed sensor to detect the normal breast tissue with good sensitivity of 7.11 (THz/RIU) and breast tumor with a high sensitivity of 8.21 THz/RIU and large figure of merits of 17.51 and 20.23 RIU1, respectively. Finally, the simplicity, efficiency and tunability are the benefits of the proposed sensor, which makes it suitable for breast tumor detection in the THz band.

Automated summary

This article presents a modeling and analysis of a tunable graphene-based sensor for breast tumor detection using the WCIP method. The sensor demonstrates good sensitivity for normal breast tissue detection and high sensitivity for breast tumor detection, with the benefits of simplicity, efficiency, and tunability, making it suitable for breast tumor detection in the THz band.