Multilayer with periodic grating based high performance SPR waveguide sensor

Teotia, Pradeep Kumar; Kaler, R.S.

doi:10.1016/j.optcom.2016.06.008

Cited by 17 publications

(5 citation statements)

References 15 publications

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“…Comparison for different materials is as shown in fig 5.From the observation, it is concluded that silver has lowest value of FWHM that is 28nm and better FOM as compared to copper and aluminum as shown in table 2. LSPR sensor using silver particles having sensitivity of 300nm/RIU which is comparatively better than the previous work [19]. …”

Section: Design and Simulation Methodsmentioning

confidence: 59%

“…These Plasmonic resonances of the metal surfaces can be adapted by proper tuning of the physical and geometrical parameters of such structures [11,12].Because of these benefits the surface Plasmon resonance-based optical fiber sensors have drawn a lot of attention [13][14][15][16][17][18].For LSPR sensor various type of metals like silver, copper and aluminium used at the surface near sensing layer to excite these waves. Pradeep Kumar Teotia et al [19] obtained high sensitivity using multilayer grating configuration. Peipei Jia et al [20] found that Sensitivity of SPR based sensor highly affected by changing the shapes and thickness of the metal.…”

Section: Introductionmentioning

confidence: 99%

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Plasmonic Optical Fiber Sensors using Different Nanoparticles

Singh¹,

Dewra²

2018

IJCA

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This paper present an investigation on Localized Surface Plasmon based optical fiber sensor and comparative performance of design with nanoparticles of different material on the tip of fiber. It is found that the Silver nanoparticles have higher sensitivity of 300nm/RIU and 10.7 figure of merit when refractive index of surrounding varies from 1.33 to 1.36. Whereas the copper and aluminum has the sensitivity of 133nm, 333nm, figure of merit of 2.7 and 8.1 respectively. It is also observed that the Surface Plasmon Resonance curve of silver nanoparticles has narrow width which improves the detection of accuracy as compared to copper and aluminum.

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Section: Design and Simulation Methodsmentioning

confidence: 59%

Section: Introductionmentioning

confidence: 99%

Plasmonic Optical Fiber Sensors using Different Nanoparticles

Singh¹,

Dewra²

2018

IJCA

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“…All these novel configurations have allowed for the development of systems for multiplexed determinations of analytes. Gratings have also been combined with other evanescent wave-based biosensors such as interferometric [138], SPR [139], SPR imaging [140], optical fiber [141], and silicon microring resonators [142] in order to create more flexible and sensitive biosensors. A reverse symmetry waveguide sensor with an integrated grating coupler was applied for the detection of E. coli K12 in buffer by monitoring the adhesion of bacteria cells onto the sensor surface, which was modified with poly-L-lysine, creating a positively charged layer that enabled bacteria binding through electrostatic interactions [143].…”

Section: Grating-coupler-based Immunosensorsmentioning

confidence: 99%

Optical Immunosensors for Bacteria Detection in Food Matrices

et al. 2023

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Optical immunosensors are one of the most popular categories of immunosensors with applications in many fields including diagnostics and environmental and food analysis. The latter field is of particular interest not only for scientists but also for regulatory authorities and the public since food is essential for life but can also be the source of many health problems. In this context, the current review aims to provide an overview of the different types of optical immunosensors focusing on their application for the determination of pathogenic bacteria in food samples. The optical immunosensors discussed include sensors based on evanescent wave transduction principles including surface plasmon resonance (SPR), fiber-optic-, interferometric-, grating-coupler-, and ring-resonator-based sensors, as well as reflectometric, photoluminescence, and immunosensors based on surface-enhanced Raman scattering (SERS). Thus, after a short description of each transduction technique, its implementation for the immunochemical determination of bacteria is discussed. Finally, a short commentary about the future trends in optical immunosensors for food safety applications is provided.

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“…All these novel configurations allowed the development of systems for multiplexed determinations of analytes. Gratings have been also combined with other evanescent wave-based biosensors such as interferometric [138], SPR [139], SPR imaging [140], optical fiber [141], and silicon microring resonators [142], in order to create more flexible and sensitive biosensors.…”

Section: Spr Immunosensorsmentioning

confidence: 99%

Optical Immunosensors for Bacteria Detection in Food Matrices

Kourti¹,

Angelopoulou²,

Petrou³

et al. 2023

Preprint

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Optical immunosensors are one of the most popular category of immunosensors with applications in many fields including diagnostics, environmental and food analysis. The latter field is of particular interest not only for the scientists but also for the regulatory authorities and the public since food is essential for life but can be also the source of many health problems. In this context, the current review aims to provide an overview of the different types of optical immunosensors focusing onto their application for the determination of pathogenic bacteria in food samples. In particular, after the description of main optical transduction techniques, their implementation for the immunochemical determination of bacteria will be discussed. Finally, a short commentary about the future trends in optical immunosensors for food safety applications will be provided.

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Multilayer with periodic grating based high performance SPR waveguide sensor

Cited by 17 publications

References 15 publications

Plasmonic Optical Fiber Sensors using Different Nanoparticles

Plasmonic Optical Fiber Sensors using Different Nanoparticles

Optical Immunosensors for Bacteria Detection in Food Matrices

Optical Immunosensors for Bacteria Detection in Food Matrices

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