22
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Fluorescence turn-on detection of arsenite in rice and seawater samples using bisphosphonate-functionalised carbon quantum dots

, , , &
Received 01 Mar 2024, Accepted 22 May 2024, Published online: 20 Jun 2024
 

ABSTRACT

In this paper, we illustrate an efficient and simple fluorescence (FL) sensing approach for the specific determination of arsenite (As(III)) in aqueous solution by alendronate-functionalised carbon quantum dots (A-CQDs) as a turn-on fluorescent probe. A-CQDs exhibit linear FL turn-on response towards the increasing concentration of As(III) analyte with a limit of detection of 0.007 µM and a linear range of 0.03–1.87 µM. The selectivity study demonstrates that the A-CQDs are very selective for As(III) detection, even at a higher concentration of other interfering ions. The sensing pathway for the sensitivity of A-CQDs assay to quantify As(III) ions is expected to rely on the chelation-enhanced FL (CHEF) mechanism between A-CQDs and the analyte. This mechanism is verified by the density functional theory methodology. The practical application of this simple and reliable sensor is demonstrated by assaying As(III) in rice and seawater samples, which confirms that A-CQDs have good potential for real sample analysis in food and environmental samples.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/03067319.2024.2360712.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,223.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.