Evidence map›Paper›PMID 36140056›Full record

ReviewBiosensors2022

Low Platinum-Content Electrocatalysts for Highly Sensitive Detection of Endogenously Released H

Ana Morais, Patrícia Rijo, Belen Batanero, Marisa Nicolai

Abstract readReview
In one paragraph

Review in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Ana MoraisCBIOS-Universidade Lusófona´s Research Centre for Biosciences & Health Technologies, Campo Grande 376, 1749-024 Lisbon, Portugal.
Patrícia RijoCBIOS-Universidade Lusófona´s Research Centre for Biosciences & Health Technologies, Campo Grande 376, 1749-024 Lisbon, Portugal.ORCID 0000-0001-7992-8343
Belen BataneroDepartment of Organic Chemistry & Inorganic Chemistry, University of Alcala, 28805 Alcala de Henares, Spain.ORCID 0000-0003-2630-4814
Marisa NicolaiCBIOS-Universidade Lusófona´s Research Centre for Biosciences & Health Technologies, Campo Grande 376, 1749-024 Lisbon, Portugal.ORCID 0000-0002-2490-2522

Funding

Fundação para a Ciência e Tecnologia UIDB/04567/2020, UIDP/04567/2020
6 · The paper itself

Abstract

The commercial viability of electrochemical sensors requires high catalytic efficiency electrode materials. A sluggish reaction of the sensor's primary target species will require a high overpotential and, consequently, an excessive load of catalyst material to be used. Therefore, it is essential to understand nanocatalysts' fundamental structures and typical catalytic properties to choose the most efficient material according to the biosensor target species. Catalytic activities of Pt-based catalysts have been significantly improved over the decades. Thus, electrodes using platinum nanocatalysts have demonstrated high power densities, with Pt loading considerably reduced on the electrodes. The high surface-to-volume ratio, higher electron transfer rate, and the simple functionalisation process are the main reasons that transition metal NPs have gained much attention in constructing high-sensitivity sensors. This study has designed to describe and highlight the performances of the different Pt-based bimetallic nanoparticles and alloys as an enzyme-free catalytic material for the sensitive electrochemical detection of H

Indexed as

Biosensing TechniquesMetal NanoparticlesAlloysElectrochemical TechniquesElectrodesHydrogen PeroxidePlatinumProspective StudiesAlloysHydrogen PeroxidePlatinumbimetallic alloyscathodic reductionelectrochemical sensinghydrogen peroxideplatinum-based electrocatalysts

Identifiers

PMID36140056
PMCPMC9496631

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.