Issue 3, 2024, Issue in Progress

Preparation of carbon quantum dot fluorescent probe from waste fruit peel and its use for the detection of dopamine

Abstract

Carbon quantum dots (CQDs), as a new type of fluorescent nanomaterial, are widely used in the detection of small molecules. Abnormal dopamine secretion can lead to diseases such as Parkinson's disease and schizophrenia. Therefore, it is highly significant to detect dopamine levels in the human body. Using discarded fruit peels to prepare carbon quantum dots can achieve the reuse of kitchen waste, reduce pollution, and create value. Nitrogen-doped carbon quantum dots (N-CQDs) were prepared using the hydrothermal method, with orange peel as the raw material. The fluorescence quantum yield of N-CQDs reached a high value of 35.37% after optimizing the temperature, reaction time, and ethylenediamine dosage. N-CQDs were characterized using various techniques, including ultraviolet visible (UV-vis) spectroscopy, fluorescence spectrophotometer (PL), transmission electron microscopy (TEM), and Fourier transform infrared spectroscopy (FT-IR). These analyses confirmed the successful doping of nitrogen in the CQDs. The DA concentration ranged from 0 to 300 μmol L−1, and the linear equation for fluorescence quenching of N-CQDs was F/F0 = −0.0056c + 0.98647, with an R2 value of 0.99071. The detection limit was 0.168 μmol L−1. The recovery and precision of dopamine in rabbit serum were 98% to 103% and 2% to 6%, respectively. The prepared N-CQDs could be used as a fluorescent probe to effectively detect DA.

Graphical abstract: Preparation of carbon quantum dot fluorescent probe from waste fruit peel and its use for the detection of dopamine

Supplementary files

Article information

Article type
Paper
Submitted
06 Oct 2023
Accepted
26 Dec 2023
First published
08 Jan 2024
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2024,14, 1813-1821

Preparation of carbon quantum dot fluorescent probe from waste fruit peel and its use for the detection of dopamine

L. Han, Y. Guo, H. Zhang, Z. Wang, F. Zhang, Y. Wang, X. Li, Y. Wang and J. Ye, RSC Adv., 2024, 14, 1813 DOI: 10.1039/D3RA06799H

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