Silver-modified nitrogen-doped graphene quantum dots as a sensor for formaldehyde in milk using headspace micro-extraction on a single-drop of aqueous nanoparticles dispersion
Fraudulent practices used to distort the quality of milk and derivatives include the addition of formaldehyde. A formaldehyde sensor was developed based on the luminescence of newly proposed N-doped graphene quantum dots modified with silver (N-GQDs-Ag) that were prepared using a simple method. A mi...
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Veröffentlicht in: | Analytica chimica acta 2022-11, Vol.1232, p.340479-340479, Article 340479 |
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Sprache: | eng |
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Zusammenfassung: | Fraudulent practices used to distort the quality of milk and derivatives include the addition of formaldehyde.
A formaldehyde sensor was developed based on the luminescence of newly proposed N-doped graphene quantum dots modified with silver (N-GQDs-Ag) that were prepared using a simple method. A microdroplet of the nanoparticle dispersion was used to collect formaldehyde vapor by headspace single-drop micro-extraction (HS-SDME). After, the microdroplet was diluted in water, the nanoparticle photoluminescence quenching, caused by the analyte, was measured. The strong luminescent quenching allowed a detection limit at 1.7 × 10−4% w/v. Response was selective towards formaldehyde.
The method was effective and a cost-effective method for screening analysis of milk samples with matrix interferences minimized due to the nature of nanoparticle (prepared using Tollen's reagent) and due to the probing at the headspace of the sample cell. Results were statistically similar to those obtained using liquid chromatography.
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•N-doped graphene quantum dots modified with silver (N-GQDs-Ag) were produced.•Headspace single drop sampling of formaldehyde in a N-GQDs-Ag droplet.•Formaldehyde efficiently quenched photoluminescence of the N-GQDs-Ag probe.•N-GQDs-Ag were used to determine formaldehyde in milk probing sample headspace.•Method can quantify formaldehyde at concentrations below 1 × 10−3% w/v in sample. |
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ISSN: | 0003-2670 1873-4324 |
DOI: | 10.1016/j.aca.2022.340479 |