Plasmonic Signals Modified by Dielectric Layers and Exploited by Multivariate Analysis

Jaione Etxebarria-Elezgarai, Luca Bergamini, Eneko Lopez Corrillero, Maria Carmen Morant-Minana, Jost Adam*, Andreas Seifert

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

We present a sensing device that combines plasmonic Au nanodiscs with dielectric layers. The sensor is operated in Kretschmann configuration and provides highly complex and sensitive reflectance curves as a result of hybridized plasmons and Fresnel reflections from the microfluidic device in which the plasmonic chip is embedded. Using multi-variate analysis to analyze multiple features of the reflectance curves in angular interrogation contributes significantly to the improvement of the sensing performance compared to a standard continuous Au thin film sensor chip. We improve sensitivity twofold and prediction error by almost 40%.

Original languageEnglish
Title of host publication2023 International Conference on Optical MEMS and Nanophotonics (OMN) and SBFoton International Optics and Photonics Conference (SBFoton IOPC)
PublisherIEEE
Publication date2023
ISBN (Electronic)9798350304022
DOIs
Publication statusPublished - 2023
Event2023 International Conference on Optical MEMS and Nanophotonics and SBFoton International Optics and Photonics Conference, OMN/SBFoton IOPC 2023 - Campinas, Sao Paulo, Brazil
Duration: 31. Jul 20233. Aug 2023

Conference

Conference2023 International Conference on Optical MEMS and Nanophotonics and SBFoton International Optics and Photonics Conference, OMN/SBFoton IOPC 2023
Country/TerritoryBrazil
CityCampinas, Sao Paulo
Period31/07/202303/08/2023
SeriesInternational Conference on Optical MEMS and Nanophotonics
Volume2023-July
ISSN2160-5033

Keywords

  • 2D Au metamaterial
  • Fresnel reflections
  • multivariate analysis
  • Plasmonic sensing

Fingerprint

Dive into the research topics of 'Plasmonic Signals Modified by Dielectric Layers and Exploited by Multivariate Analysis'. Together they form a unique fingerprint.

Cite this