Evidence map›Paper›PMID 34372121›Full record

ArticlePolymers2021

Microstructured Surface Plasmon Resonance Sensor Based on Inkjet 3D Printing Using Photocurable Resins with Tailored Refractive Index.

Nunzio Cennamo, Lorena Saitta, Claudio Tosto, Francesco Arcadio, Luigi Zeni, Maria Elena Fragalá, Gianluca Cicala

Abstract read
In one paragraph

Article in Polymers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Nunzio CennamoDepartment of Engineering, University of Campania Luigi Vanvitelli, Via Roma 29, 81031 Aversa, Italy.ORCID 0000-0001-7769-0984
Lorena SaittaDepartment of Civil Engineering and Architecture, University of Catania, Via S. Sofia 64, 95125 Catania, Italy.
Claudio TostoDepartment of Civil Engineering and Architecture, University of Catania, Via S. Sofia 64, 95125 Catania, Italy.ORCID 0000-0001-6814-7293
Francesco ArcadioDepartment of Engineering, University of Campania Luigi Vanvitelli, Via Roma 29, 81031 Aversa, Italy.ORCID 0000-0001-7863-743X
Luigi ZeniDepartment of Engineering, University of Campania Luigi Vanvitelli, Via Roma 29, 81031 Aversa, Italy.ORCID 0000-0001-8356-7480
Maria Elena FragaláDepartment of Chemical Sciences, University of Catania, Viale Andrea Doria 6, 95125 Catania, Italy.ORCID 0000-0001-9414-7780
Gianluca CicalaDepartment of Civil Engineering and Architecture, University of Catania, Via S. Sofia 64, 95125 Catania, Italy.ORCID 0000-0002-4680-152X

Funding

Ministero dell'Istruzione, dell'Università e della Ricerca 20179SWLKA - Multiple Advanced Materials Manufactured by Additive technologies (MAMMA),
6 · The paper itself

Abstract

In this work, a novel approach to realize a plasmonic sensor is presented. The proposed optical sensor device is designed, manufactured, and experimentally tested. Two photo-curable resins are used to 3D print a surface plasmon resonance (SPR) sensor. Both numerical and experimental analyses are presented in the paper. The numerical and experimental results confirm that the 3D printed SPR sensor presents performances, in term of figure of merit (FOM), very similar to other SPR sensors made using plastic optical fibers (POFs). For the 3D printed sensor, the measured FOM is 13.6 versus 13.4 for the SPR-POF configuration. The cost analysis shows that the 3D printed SPR sensor can be manufactured at low cost (∼15 €) that is competitive with traditional sensors. The approach presented here allows to realize an innovative SPR sensor showing low-cost, 3D-printing manufacturing free design and the feasibility to be integrated with other optical devices on the same plastic planar support, thus opening undisclosed future for the optical sensor systems.

Indexed as

3D printingadditive manufacturingphotocurable resinsplasmonicsensor

Identifiers

PMID34372121
PMCPMC8347231

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.