High-Sensitivity Biosensor Based on Glass Resonance PhC Cavities for Detection of Blood Component and Glucose Concentration in Human Urine

Author:

Jalil Abduladheem TurkiORCID,Ashfaq Shameen,Bokov Dmitry OlegovichORCID,Alanazi Amer M.,Hachem KaddaORCID,Suksatan WanichORCID,Sillanpää MikaORCID

Abstract

In this work, a novel structure of an all-optical biosensor based on glass resonance cavities with high detection accuracy and sensitivity in two-dimensional photon crystal is designed and simulated. The free spectral range in which the structure performs well is about FSR = 630 nm. This sensor measures the concentration of glucose in human urine. Analyses to determine the glucose concentration in urine for a normal range (0~15 mg/dL) and urine despite glucose concentrations of 0.625, 1.25, 2.5, 5 and 10 g/dL in the wavelength range 1.326404~1.326426 μm have been conducted. The detection range is RIU = 0.2 × 10−7. The average bandwidth of the output resonance wavelengths is 0.34 nm in the lowest case. In the worst case, the percentage of optical signal power transmission is 77% with an amplitude of 1.303241 and, in the best case, 100% with an amplitude of 1.326404. The overall dimensions of the biosensor are 102.6 µm2 and the sensitivity is equal to S = 1360.02 nm/RIU and the important parameter of the Figure of Merit (FOM) for the proposed biosensor structure is equal to FOM = 1320.23 RIU−1.

Publisher

MDPI AG

Subject

Materials Chemistry,Surfaces, Coatings and Films,Surfaces and Interfaces

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1. Exploring the Role of Deep Learning in Industrial Applications: A Case Study on Coastal Crane Casting Recognition. Human Centric Computing and Information Sciences;Maqsood;Hum. Cent. Comput. Inf. Sci.,2021

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