Numerical optimization of 1D superconductor photonic crystals pressure sensor for low temperatures applications

Abstract

In this research, reflectance spectra for a one-dimensional (1D) photonic crystal (PC) consists of a high-temperature superconductor Hg-1223 and a semiconductor GaAs have been calculated using the well-known transfer matrix method (TMM) and the two-fluid model. The proposed PC was introduced as an optical pressure sensor at the mid-IR region. The pressure effect is studied on two types of PCs; a defective PC [Air (GaAs/Hg 1223)5 (GaAs) (GaAs/Hg 1223)5 substrate] and periodic PC [Air (GaAs/Hg-1223)10 substrate]. Herein, we have found that the pressure sensitivity reached a high value of 1.7467 nm/GPa at an applied pressure of 6 GPa. However, a small blue shift is noticed for the periodic design. Therefore, the number of periods, thickness, and incident angle were taken after many optimization steps to get the highest-pressure sensitivity for the defective PC. Based on the optimization process, the results reveled higher performance for the other sensitivity parameters such sensor resolution, signal to noise ratio, figure of merit, and quality factor (QF). Finally, we have studied the effect of the operating temperature on the defect mode, which shows a small redshift with increasing the operating temperature. We hope this research may be utilized for applications of tunable filters and hydrostatic pressure sensors.