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Rational design and optimization of plasmonic nanoarrays for surface enhanced infrared spectroscopy
We present an approach for rational design and optimization of plasmonic arrays for ultrasensitive surface enhanced infrared absorption (SEIRA) spectroscopy of specific protein analytes. Motivated by our previous work that demonstrated sub-attomole detection of surface-bound silk fibroin [Proc. Natl...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Optical Society of America
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482914/ https://www.ncbi.nlm.nih.gov/pubmed/22714181 http://dx.doi.org/10.1364/OE.20.011953 |
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author | Liberman, Vladimir Adato, Ronen Jeys, Thomas H. Saar, Brian G. Erramilli, Shyamsunder Altug, Hatice |
author_facet | Liberman, Vladimir Adato, Ronen Jeys, Thomas H. Saar, Brian G. Erramilli, Shyamsunder Altug, Hatice |
author_sort | Liberman, Vladimir |
collection | PubMed |
description | We present an approach for rational design and optimization of plasmonic arrays for ultrasensitive surface enhanced infrared absorption (SEIRA) spectroscopy of specific protein analytes. Motivated by our previous work that demonstrated sub-attomole detection of surface-bound silk fibroin [Proc. Natl. Acad. Sci. U.S.A. 106, 19227 (2009)], we introduce here a general framework that allows for the numerical optimization of metamaterial sensor designs in order to maximize the absorbance signal. A critical feature of our method is the explicit compensation for the perturbative effects of the analyte's refractive index which alters the resonance frequency and line-shape of the metamaterial response, thereby leading to spectral distortion in SEIRA signatures. As an example, we leverage our method to optimize the geometry of periodic arrays of plasmonic nanoparticles on both Si and CaF(2) substrates. The optimal geometries result in a three-order of magnitude absorbance enhancement compared to an unstructured Au layer, with the CaF(2) substrate offering an additional factor of three enhancement in absorbance over a traditional Si substrate. The latter improvement arises from increase of near-field intensity over the Au nanobar surface for the lower index substrate. Finally, we perform sensitivity analysis for our optimized arrays to predict the effects of fabrication imperfections. We find that <20% deviation from the optimized absorbance response is readily achievable over large areas with modern nanofabrication techniques. |
format | Online Article Text |
id | pubmed-3482914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Optical Society of America |
record_format | MEDLINE/PubMed |
spelling | pubmed-34829142013-05-10 Rational design and optimization of plasmonic nanoarrays for surface enhanced infrared spectroscopy Liberman, Vladimir Adato, Ronen Jeys, Thomas H. Saar, Brian G. Erramilli, Shyamsunder Altug, Hatice Opt Express Research-Article We present an approach for rational design and optimization of plasmonic arrays for ultrasensitive surface enhanced infrared absorption (SEIRA) spectroscopy of specific protein analytes. Motivated by our previous work that demonstrated sub-attomole detection of surface-bound silk fibroin [Proc. Natl. Acad. Sci. U.S.A. 106, 19227 (2009)], we introduce here a general framework that allows for the numerical optimization of metamaterial sensor designs in order to maximize the absorbance signal. A critical feature of our method is the explicit compensation for the perturbative effects of the analyte's refractive index which alters the resonance frequency and line-shape of the metamaterial response, thereby leading to spectral distortion in SEIRA signatures. As an example, we leverage our method to optimize the geometry of periodic arrays of plasmonic nanoparticles on both Si and CaF(2) substrates. The optimal geometries result in a three-order of magnitude absorbance enhancement compared to an unstructured Au layer, with the CaF(2) substrate offering an additional factor of three enhancement in absorbance over a traditional Si substrate. The latter improvement arises from increase of near-field intensity over the Au nanobar surface for the lower index substrate. Finally, we perform sensitivity analysis for our optimized arrays to predict the effects of fabrication imperfections. We find that <20% deviation from the optimized absorbance response is readily achievable over large areas with modern nanofabrication techniques. Optical Society of America 2012-05-10 /pmc/articles/PMC3482914/ /pubmed/22714181 http://dx.doi.org/10.1364/OE.20.011953 Text en ©2012 Optical Society of America http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 Unported License, which permits download and redistribution, provided that the original work is properly cited. This license restricts the article from being modified or used commercially. |
spellingShingle | Research-Article Liberman, Vladimir Adato, Ronen Jeys, Thomas H. Saar, Brian G. Erramilli, Shyamsunder Altug, Hatice Rational design and optimization of plasmonic nanoarrays for surface enhanced infrared spectroscopy |
title | Rational design and optimization of plasmonic nanoarrays for surface enhanced infrared spectroscopy |
title_full | Rational design and optimization of plasmonic nanoarrays for surface enhanced infrared spectroscopy |
title_fullStr | Rational design and optimization of plasmonic nanoarrays for surface enhanced infrared spectroscopy |
title_full_unstemmed | Rational design and optimization of plasmonic nanoarrays for surface enhanced infrared spectroscopy |
title_short | Rational design and optimization of plasmonic nanoarrays for surface enhanced infrared spectroscopy |
title_sort | rational design and optimization of plasmonic nanoarrays for surface enhanced infrared spectroscopy |
topic | Research-Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482914/ https://www.ncbi.nlm.nih.gov/pubmed/22714181 http://dx.doi.org/10.1364/OE.20.011953 |
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