Self-referenced optical fiber sensor based on LSPR generated by gold and silver nanoparticles embedded in layer-by-layer nanostructured coatings
Fecha
2022Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión publicada / Argitaratu den bertsioa
Identificador del proyecto
Impacto
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10.3390/chemosensors10020077
Resumen
In this work, an optical fiber sensor based on the localized surface plasmon resonance (LSPR) phenomenon has been designed for the detection of two different chemical species (mercury and hydrogen peroxide) by using Layer-by-Layer Embedding (LbL-E) as a nanofabrication technique. In the first step, silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) have been synthesized by using a chemic ...
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In this work, an optical fiber sensor based on the localized surface plasmon resonance (LSPR) phenomenon has been designed for the detection of two different chemical species (mercury and hydrogen peroxide) by using Layer-by-Layer Embedding (LbL-E) as a nanofabrication technique. In the first step, silver nanoparticles (AgNPs) and gold nanoparticles (AuNPs) have been synthesized by using a chemical protocol as a function of the strict control of three main parameters, which were polyelectrolyte concentration, a loading agent, and a reducing agent. In the second step, their incorporation into nanometric thin films have been demonstrated as a function of the number of bilayers, which shows two well-located absorption peaks associated to their LSPR in the visible region at 420 nm (AgNPs) and 530 nm (AuNPs). Finally, both plasmonic peaks provide a stable real-time reference measurement, which can be extracted from the spectral response of the optical fiber sensor, which shows a specific sensing mechanism as a function of the analyte of study. [--]
Materias
Fiber optic sensor,
Gold nanoparticles,
Hydrogen peroxide,
Layer-by-Layer Embedding,
Localized surface plasmon resonance,
Mercury,
Silver nanoparticles
Editor
MDPI
Publicado en
Chemosensors, 2022, 10 (2), p. 77
Departamento
Universidad Pública de Navarra. Departamento de Ingeniería /
Nafarroako Unibertsitate Publikoa. Ingeniaritza Saila /
Universidad Pública de Navarra. Departamento de Ingeniería Eléctrica, Electrónica y de Comunicación /
Nafarroako Unibertsitate Publikoa. Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza Saila /
Universidad Pública de Navarra/Nafarroako Unibertsitate Publikoa. Institute of Smart Cities - ISC /
Universidad Pública de Navarra/Nafarroako Unibertsitate Publikoa. Institute for Advanced Materials and Mathematics - INAMAT2
Versión del editor
Entidades Financiadoras
This research was funded by the Spanish Agencia Estatal de Investigación (AEI), grant number PID2019-106070RB-I00.