Detection limit

Physics

Transfer-matrix method (optics)

Biosensor

Nanotechnology

MATLAB

Mathematics

Operating system

Analyte

Optics

Figure of merit

Resolution (logic)

Limit (mathematics)

Engineering

Mathematical analysis

Transmittance

Artificial intelligence

Chemistry

Materials science

Photonics

Sensitivity (control systems)

Electronic engineering

Computer science

Chromatography

Optoelectronics

Crystals

The present 1D photonic biosensor is composed of two sub-PhCs of alternate layers made of GaP and SiO2. The period number of each PhC has been fixed to 3. Both these PhCs are joined together through a cavity region of air in which different analytes are to be filled one by one under the scope of this study. The theoretical findings of this work have been formulated with the help of the well-known transfer matrix method. Moreover, all the computations pertaining to this work have been carried out with the help of MATLAB software. The effect of change in cavity thickness and angle of incidence corresponding to a TE wave on the transmittance of the structure (AB)ND(AB)N has been studied theoretically which in turn determines the performance of the proposed biosensor. Various parameters, such as sensitivity (S), signal to noise ratio (SNR), figure of merit (FOM), resolution (RS), detection limit (LOD), quality factor (Q) and dynamic range (DR) have been theoretically calculated to evaluate the performance of the proposed design in true sense. The sensitivity of this structure varies between the highest and lowest values of 337.3626 nm/RIU and 333.0882 nm/RIU corresponding to water samples containing Pseudomonas aeruginosa cells and Bacillus anthracia cells, respectively, under normal incidence condition with a cavity thickness of 2.0 µm. The resolution (in nm) and LOD (in RIU) values of the proposed design are small enough and are significant for our structure. This study may also be helpful for distinguishing various microbiological samples under investigation and find suitable applications for discriminating bacterial cells from spores.

MATLAB Simulation-Based Theoretical Study for Detection of a Wide Range of Pathogens Using 1D Defective Photonic Structure