Optimal geometric parameters of ordered arrays of nanoprisms for enhanced sensitivity in localized plasmon based sensors

Plasmonic sensors based on ordered arrays of nanoprisms are optimized in terms of their geometric parameters like size, height, aspect ratio for Au, Ag or Au0.5–Ag0.5 alloy to be used in the visible or near IR spectral range. The two figures of merit used for the optimization are the bulk and the su...

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Bibliographic Details
Published in:Biosensors & bioelectronics 2015-03, Vol.65, p.346-353
Main Authors: Michieli, Niccolò, Kalinic, Boris, Scian, Carlo, Cesca, Tiziana, Mattei, Giovanni
Format: Article
Language:English
Subjects:
Alloys - chemistry
Arrays
Biosensors
Computer simulation
Finite Element Analysis
Finite element method
Finite Elements
Gold - chemistry
Metal Nanoparticles - chemistry
Metal Nanoparticles - ultrastructure
Nanostructure
Optimization
Plasmonic
Refractometry
Sensitivity
Sensor arrays
Sensors
Silver - chemistry
Simulation
Surface Plasmon Resonance - methods
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Summary:Plasmonic sensors based on ordered arrays of nanoprisms are optimized in terms of their geometric parameters like size, height, aspect ratio for Au, Ag or Au0.5–Ag0.5 alloy to be used in the visible or near IR spectral range. The two figures of merit used for the optimization are the bulk and the surface sensitivity: the first is important for optimizing the sensing to large volume analytes whereas the latter is more important when dealing with small bio-molecules immobilized in close proximity to the nanoparticle surface. A comparison is made between experimentally obtained nanoprisms arrays and simulated ones by using Finite Elements Methods (FEM) techniques. •We model the nanoprisms array-based plasmonic biosensors.•We carry out a systematic analysis on the sensitivity varying geometric parameters.•We determine the resonance wavelength as a function of geometric parameters.•We determine the best parameters for building local and bulk sensors.•We consider the role of the metal, modeling Au, Ag and AuAg alloy.
ISSN:0956-5663
1873-4235
DOI:10.1016/j.bios.2014.10.064