Evidence map›Paper›PMID 42825003›Full record

ArticleACS omega2026

On-Site Electrochemical Detection of Sulfentrazone Using a Fully 3D-Printed Portable Sensing Platform.

Jacqueline Marques Petroni, Jonas Raul Balbinoti, Elias Jorge, Osvaldo Cavalcante da Costa Neto, Rodrigo Amorim Bezerra da Silva, Magno Aparecido Gonçalves Trindade, Bruno Gabriel Lucca

Abstract read
In one paragraph

Article in ACS omega, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jacqueline Marques PetroniInstitute of Chemistry, Federal University of Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul 79074-460, Brazil.
Jonas Raul BalbinotiOccupational Health and Safety Management Systems, Industry Social Service Innovation Center, Campo Grande, Mato Grosso do Sul 79002-072, Brazil.
Elias JorgeOccupational Health Department, Eldorado Brasil, Três Lagoas, Mato Grosso do Sul 79641-300, Brazil.
Osvaldo Cavalcante da Costa NetoOccupational Health Department, Eldorado Brasil, Três Lagoas, Mato Grosso do Sul 79641-300, Brazil.
Rodrigo Amorim Bezerra da SilvaInstitute of Chemistry, Federal University of Uberlandia, Uberlandia, Minas Gerais 38400-902, Brazil.ORCID https://orcid.org/0000-0002-0210-5311
Magno Aparecido Gonçalves TrindadeFaculty of Exact Sciences and Technology, Federal University of Grande Dourados, Dourados, Mato Grosso do Sul 79804-970, Brazil.ORCID https://orcid.org/0000-0003-4674-4809
Bruno Gabriel LuccaInstitute of Chemistry, Federal University of Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul 79074-460, Brazil.ORCID https://orcid.org/0000-0002-5782-6845

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The widespread use of pesticides in agricultural activities has increased concerns regarding environmental contamination and occupational exposure, particularly through dermal contact. In this work, we report a portable and low-cost electrochemical sensing platform for on-site monitoring of sulfentrazone (SFT), a herbicide extensively used in eucalyptus cultivation. The proposed device consists of a fully 3D-printed miniaturized electrochemical system fabricated by multi-material printing using conductive and non-conductive filaments, enabling accessible and decentralized analysis. SFT detection was performed by square-wave voltammetry (SWV), exhibiting a single irreversible oxidation peak at +0.86 V (pH 6.5). Under optimized conditions, the platform showed a linear response from 1.1 to 101.1 μmol L

Identifiers

PMID42825003
PMCPMC13628626

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.