Evidence map›Paper›PMID 38867513›Full record

ArticleAnalytical chemistry2024

Spark-Discharge-Activated 3D-Printed Electrochemical Sensors.

Juan F Hernández-Rodríguez, Maria G Trachioti, Jan Hrbac, Daniel Rojas, Alberto Escarpa, Mamas I Prodromidis

Abstract read
In one paragraph

Article in Analytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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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

6 authors.

Juan F Hernández-RodríguezDepartment of Analytical Chemistry, Physical Chemistry and Chemical Engineering, University of Alcalá, Alcalá de Henares 28802, Madrid, Spain.ORCID 0000-0001-5035-6791
Maria G TrachiotiDepartment of Chemistry, University of Ioannina, 45 110 Ioannina, Greece.
Jan HrbacDepartment of Chemistry, Masaryk University, 625 00 Brno, Czech Republic.
Daniel RojasDepartment of Analytical Chemistry, Physical Chemistry and Chemical Engineering, University of Alcalá, Alcalá de Henares 28802, Madrid, Spain.ORCID 0000-0002-4404-4668
Alberto EscarpaDepartment of Analytical Chemistry, Physical Chemistry and Chemical Engineering, University of Alcalá, Alcalá de Henares 28802, Madrid, Spain.ORCID 0000-0002-7302-0948
Mamas I ProdromidisDepartment of Chemistry, University of Ioannina, 45 110 Ioannina, Greece.ORCID 0000-0002-1309-403X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

3D printing technology is a tremendously powerful technology to fabricate electrochemical sensing devices. However, current conductive filaments are not aimed at electrochemical applications and therefore require intense activation protocols to unleash a suitable electrochemical performance. Current activation methods based on (electro)chemical activation (using strong alkaline solutions and organic solvents and/or electrochemical treatments) or combined approaches are time-consuming and require hazardous chemicals and dedicated operator intervention. Here, pioneering spark-discharge-activated 3D-printed electrodes were developed and characterized, and it was demonstrated that their electrochemical performance was greatly improved by the effective removal of the thermoplastic support polylactic acid (PLA) as well as the formation of sponge-like and low-dimensional carbon nanostructures. This reagent-free approach consists of a direct, fast, and automatized spark discharge between the 3D-electrode and the respective graphite pencil electrode tip using a high-voltage power supply. Activated electrodes were challenged toward the simultaneous voltammetric determination of dopamine (DP) and serotonin (5-HT) in cell culture media. Spark discharge has been demonstrated as a promising approach for conductive filament activation as it is a fast, green (0.94 GREEnness Metric Approach), and automatized procedure that can be integrated into the 3D printing pipeline.

Identifiers

PMID38867513
PMCPMC11209655

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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.