Evidence map›Paper›PMID 36772559›Full record

ArticleSensors (Basel, Switzerland)2023

Identification of Cadmium Compounds in a Solution Using Graphene-Based Sensor Array.

Tomoya Yoshii, Fuka Nishitsugu, Kazuki Kikawada, Kenzo Maehashi, Takashi Ikuta

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. 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. Review
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

5 authors.

Tomoya YoshiiInstitute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Nakacho, Koganei, Tokyo 184-8588, Japan.
Fuka NishitsuguInstitute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Nakacho, Koganei, Tokyo 184-8588, Japan.
Kazuki KikawadaInstitute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Nakacho, Koganei, Tokyo 184-8588, Japan.
Kenzo MaehashiInstitute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Nakacho, Koganei, Tokyo 184-8588, Japan.
Takashi IkutaInstitute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Nakacho, Koganei, Tokyo 184-8588, Japan.ORCID 0000-0003-1293-5084

Funding

Japan Society for the Promotion of Science JP20H02159, JP21H01336, JP21K18714
6 · The paper itself

Abstract

Rapid detection of heavy metals in solution is necessary to ensure human health and environmental protection. Some heavy-metal compounds are present in solution as compounds instead of as ions owing to their low ionization. Therefore, the development of sensor devices for the detection of heavy-metal compounds is important. In this study, as a proof of concept, we propose a sensor device using graphene and a chelating agent, which were used to develop an identification technique for three types of cadmium compounds. Pristine-graphene and two types of chelator-modified graphene-based sensors were successfully used to detect cadmium compounds at concentrations ranging from 50 to 1000 μM. The detection time was less than 5 min. The three type of graphene-based sensors responded differently to each cadmium compound, which indicates that they detected cadmium as a cadmium compound instead of as cadmium ions. Furthermore, we successfully identified cadmium compounds by operating these three types of sensors as a sensor array on the same substrate. The results indicate that sensors that focus on heavy-metal compounds instead of heavy-metal ions can be used for the detection of heavy metals in solution.

Indexed as

cadmium compoundgrapheneheavy metalsensor arrayterpyridine

Identifiers

PMID36772559
PMCPMC9921919

What OpenQuestion holds

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LicenceCC BY
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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.