Evidence map›Paper›PMID 35528575›Full record

ArticleRSC advances2019

Sulfur-doped graphene quantum dot-based paper sensor for highly sensitive and selective detection of 4-nitrophenol in contaminated water and wastewater.

Nguyen Thi Ngoc Anh, Pei-Yi Chang, Ruey-An Doong

Open access · goldAbstract read
In one paragraph

Article in RSC advances, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.0field-weighted citation impact, top 8% of its field
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

12 citing papers in PubMed, 66 citations in OpenAlex.

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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

3 authors at 2 institutions in 4 countries.

Nguyen Thi Ngoc AnhInstitute of Environmental Engineering, National Chiao Tung University 1001, University Road Hsinchu 30010 Taiwan.
Pei-Yi ChangCenter for Measurement Standard, Industrial Technology Research Institute (ITRI) 321, Sec. 2, Kuang Fu Road Hsinchu 30011 Taiwan.
Ruey-An DoongInstitute of Environmental Engineering, National Chiao Tung University 1001, University Road Hsinchu 30010 Taiwan.ORCID https://orcid.org/0000-0002-4913-0602
National Yang Ming Chiao Tung University · TWITRI International · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

4-Nitrophenol (4-NP) is a promulgated priority pollutant, which can cause a negative impact on human health. The development of a direct and effective technique for the rapid detection and screening of 4-NP is, therefore, of urgent need. In this study, the blue luminescent sulfur-doped graphene quantum dots (S-GQDs) with a size of 1-5 nm are fabricated using a one-step pyrolysis procedure in the presence of citric acid and 3-mercaptosuccinic acid. The S-GQDs exhibit a strong emission band at 450 nm under the excitation of 330 nm UV light. 4-NP can serve as the fluorescence quencher by the π-π interaction with S-GQD, resulting in the linear decrease in fluorescence intensity after the addition of various 4-NP concentrations ranging from 10 nM to 200 μM. The S-GQDs serve as the sensing probe to enhance the analytical performance on 4-NP detection with the limit of detection values of 0.7 and 3.5 nM in deionized water and wastewater, respectively. The S-GQD based sensing platform can be used to detect 4-NP in different matrices of water and wastewater. In addition, the detected percentages of spiked 4-NP concentrations in the presence of different matrices and interferences are in the range of (98 ± 5)-(108 ± 2)%. Moreover, the S-GQD based paper sensor can rapidly screen 4-NP in wastewater within 1 min. Results obtained in this study clearly demonstrate the superiority of S-GQDs as a promising fluorescence probe for highly sensitive and selective detection of a wide concentration range of 4-NP in deionized water and wastewater.

Identifiers

PMID35528575
PMCPMC9070512
OpenAlexW2970443384

What OpenQuestion holds

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LicenceCC BY-NC
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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.