Analysis of low-cost inkjet-printed Optical platforms covered by Molecularly Imprinted Polymers to detect furfural in water

This work proposes an analysis relative to an optical-chemical sensor used to detect furanic compounds in aqueous solutions. The optical platform consists of a flexible substrate covered with inkjet-printed silver nanoparticle lines; on the latter, a molecularly imprinted polymer (MIP) layer specifi...

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Veröffentlicht in:IEEE sensors journal 2023-10, Vol.23 (19), p.1-1
Hauptverfasser: Cennamo, Nunzio, Arcadio, Francesco, Minardo, Aldo, Del Prete, Domenico, Zeni, Luigi, Pesavento, Maria, Alberti, Giancarla, Marletta, Vincenzo, Ando, Bruno
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Sprache:eng
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Zusammenfassung:This work proposes an analysis relative to an optical-chemical sensor used to detect furanic compounds in aqueous solutions. The optical platform consists of a flexible substrate covered with inkjet-printed silver nanoparticle lines; on the latter, a molecularly imprinted polymer (MIP) layer specific for a furanic compound detection, i.e., furan-2-carbaldehyde (2-FAL), is then deposited. Two plastic optical fibers (POFs) are used to launch the light into the optical-chemical sensor and collect it at the platform's output. For the first time, an oblique lines-based pattern has been tested for 2-FAL detection in water. The performances of the sensor based on this pattern have been compared to two other similar sensor configurations in which the inkjet-printed lines are located in different directions with respect to the input light respectively longitudinally and orthogonally. In this work, the characterization has been carried out by two different experimental setups. In such a way, it has been determined that the printed pattern has a noticeable influence on the chemical performance of the proposed 2-FAL sensor. Moreover, selectivity tests have been performed, to confirm the good selectivity of the proposed optical-chemical platform. The obtained results have added more information relative to a simple, low-cost, highly sensitive and selective sensing approach.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2023.3306705