The present work, theoretically examined the poliovirus sensor model composed of one-dimensional photonic crystal with defect. The transfer matrix method with the help of MATLAB software has been used to detect poliovirus present in the water sample. The main objective of the present work is to design an efficient sensor by identifying the minute variation in the refractive index of water sample due to change in the poliovirus concentration present in the sample. The alternate layers of aluminum nitride and gallium nitride has been taken to realize Bragg reflector having defect layer of air at center of the Bragg reflector. The effect of change in thickness of defect layer region, period number and incident angle corresponding to transverse electric wave has been examined to optimize the structure which correspond maximum performance of the proposed poliovirus sensing structure. The maximum performance of the structure has been obtained with optimum value of defect layer thickness 1200 nm, period number 10 and incident angle 40°. Under optimum condition maximum sensitivity of 1189.65517 nm/RIU has been obtained when the structure is loaded with waters sample of poliovirus concentration C = 0.005 g/ml whereas figure of merit, quality factor, signal to noise ratio, dynamic range, limit of detection and resolution values become 2618.28446 per RIU, 3102.06475, 2.27791, 2090.99500, 1.91E−05 and 0.24656 respectively.

In the present research work we have theoretically examined the biosensing capabilities of proposed one dimensional defective photonic crystal for swift detection of malignant brain tissues. The transfer matrix formulation and MATLAB computational tool have been used to examine the transmission properties of proposed structure. The identical buffer layers of nanocomposite superconducting material have been used either side of cavity region to enhance the interaction between incident light and different brain tissue samples poured into the cavity region. All the investigations have been carried out under normal incidence to suppress the experimental liabilities involved. We have investigated the biosensing performance of the proposed design by changing the values of two internal parameters (1) the cavity layer thickness (d4) and (2) volume fraction (η) of nanocomposite buffer layers one by one to get the optimum biosensing performance from the structure. It has been found that the sensitivity of the proposed design becomes 1.42607 μm/RIU when the cavity region of thickness 15dd is loaded with lymphoma brain tissue. This value of sensitivity can be further increased to 2.66136 μm/RIU with η = 0.8. The findings of this work are very beneficial for designing of various bio-sensing structures composed of nanocomposite materials of diversified biomedical applications.

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