Computational study of 2D photonic crystal based biosensor for SARS-COV-2 detection

Abstract

Abstract A computational study to design a 2D-photonic crystal (PC) structure with a fluorescence-based biosensor has been demonstrated for the detection of the severe acute respiratory syndrome corona virus 2 (SARS-COV-2) virus in the lungs. The proposed sensor can detect the different concentrations of the virus without any pretreatment of the sample. The virus detection is performed by measuring the mid-gap wavelength from the dispersion diagram and a redshift in the mid-gap wavelength has been observed as the concentration of virus increases in the lung tissue. The plane wave expansion method is used to determine the dispersion diagram of the proposed PC. The interaction of incident light with the proposed PC-based biosensor has been analyzed to evaluate the shift in the mid-gap wavelength. A maximum sensitivity of about 1459.3 nm/RIU is obtained for r/a = 0.45 with a mid-gap wavelength shift of 145.93 nm at n net = 1.49 concentration of SARS-COV-2. Moreover, a very small detection time has been observed with the proposed device as compared to conventional methods. This study provides a simple process to detect the presence of a virus within a short period and could be helpful in the development of a direct and easy-to-use portable detection kit in the future.