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Analysis of Effects of Surface Roughness on Sensing Performance of Surface Plasmon Resonance Detection for Refractive Index Sensing Application
by
Treebupachatsakul, Treesukon
, Shinnakerdchoke, Siratchakrit
, Pechprasarn, Suejit
in
Glass substrates
/ Gold
/ instrumentation
/ Normal distribution
/ refractive index sensing
/ sensing performance
/ Sensors
/ Severe acute respiratory syndrome coronavirus 2
/ Simulation
/ surface plasmon resonance
/ surface roughness
2021
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Analysis of Effects of Surface Roughness on Sensing Performance of Surface Plasmon Resonance Detection for Refractive Index Sensing Application
by
Treebupachatsakul, Treesukon
, Shinnakerdchoke, Siratchakrit
, Pechprasarn, Suejit
in
Glass substrates
/ Gold
/ instrumentation
/ Normal distribution
/ refractive index sensing
/ sensing performance
/ Sensors
/ Severe acute respiratory syndrome coronavirus 2
/ Simulation
/ surface plasmon resonance
/ surface roughness
2021
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Analysis of Effects of Surface Roughness on Sensing Performance of Surface Plasmon Resonance Detection for Refractive Index Sensing Application
by
Treebupachatsakul, Treesukon
, Shinnakerdchoke, Siratchakrit
, Pechprasarn, Suejit
in
Glass substrates
/ Gold
/ instrumentation
/ Normal distribution
/ refractive index sensing
/ sensing performance
/ Sensors
/ Severe acute respiratory syndrome coronavirus 2
/ Simulation
/ surface plasmon resonance
/ surface roughness
2021
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Analysis of Effects of Surface Roughness on Sensing Performance of Surface Plasmon Resonance Detection for Refractive Index Sensing Application
Journal Article
Analysis of Effects of Surface Roughness on Sensing Performance of Surface Plasmon Resonance Detection for Refractive Index Sensing Application
2021
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Overview
This paper provides a theoretical framework to analyze and quantify roughness effects on sensing performance parameters of surface plasmon resonance measurements. Rigorous coupled-wave analysis and the Monte Carlo method were applied to compute plasmonic reflectance spectra for different surface roughness profiles. The rough surfaces were generated using the low pass frequency filtering method. Different coating and surface treatments and their reported root-mean-square roughness in the literature were extracted and investigated in this study to calculate the refractive index sensing performance parameters, including sensitivity, full width at half maximum, plasmonic dip intensity, plasmonic dip position, and figure of merit. Here, we propose a figure-of-merit equation considering optical intensity contrast and signal-to-noise ratio. The proposed figure-of-merit equation could predict a similar refractive index sensing performance compared to experimental results reported in the literature. The surface roughness height strongly affected all the performance parameters, resulting in a degraded figure of merit for surface plasmon resonance measurement.
Publisher
MDPI AG,MDPI
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