A Numerical Analysis of Graphene Based D-Shaped Plasmonic Sensor for Multi-Analyte Detection

Abstract

Since decades ago, the PCF-based surface plasmon resonance (SPR) sensor has attracted increased attention due to its unique properties, including compact size, simple light transmission via the fiber core, control over light propagation, design flexibility, and excellent sensing ability. The D-shaped PCF-based SPR sensing phenomenon is extensively employed in sensing applications for liquid detection, chemical detection, and biomolecular interaction in medical diagnostics. Although the D-shaped PCF based SPR sensor demonstrates great sensitivity, its main limitation is the requirement for deep polishing depth, which makes fibers more fragile in the manufacturing environment. This thesis investigates how to enhance existing PCF sensors based on SPR and how to employ a better understanding of their physical and sensing principles to suggest new design concepts and ideas with smaller polishing depth. A systematic approach was used to look at several structural factors, such as the location, optical characteristics, shape, and thickness of the metal components, that might affect how well a sensor performs. In this paper, we have proposed a graphene embedded photonic crystal fiber (PCF) based surface plasmon resonance (SPR) sensor for multi-analyte detection simultaneously. The graphene layer improves the sensing performance due to their high surface to volume ratio. The proposed sensor is numerically investigated where channels are coated with gold and graphene layers. Top and bottom side of the fiber etched down to make it double sided D-shape. The double D-shaped structure works based on external sensing mechanism and facilitate to utilize the multi-analyte detection approach. The proposed fiber consists with six air holes, and two of them are used as fiber cores by filling up with the high refractive index (RI) liquid of 1.46. The fiber is fabricated using stack-and-draw fiber fabrication method. The finite element method (FEM) approach is used to investigate the fiber's characteristics and sensing performance numerically. Due to asymmetry of the fiber structure, the proposed sensor demonstrates polarization dependency and exhibits sensing phenomena for the x-polarized mode. The sensor can detect the unknown analyte RI at the detection range of 1.32 to 1.42. The sensing range is separated into two groups such as Ch-1 (RI from 1.32 to 1.37) and Ch-2 (RI from 1.38 to 1.42) to demonstrate multi-analyte detection phenomena. The proposed sensor exhibits the maximum wavelength and amplitude sensitivities of 14,000 nm/RIU and 1922 RIU-1, respectively. Also, the effects of structural parameters on the sensor performance, such as graphene layer thickness, gold layer thickness, air holes, fused silica, and diameter are numerically investigated. Consequently, we may anticipate that the demonstrated sensor with multi-analyte detection capacity will make it more promising choice for medical diagnostics, biochemical, and organic chemical detection.