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A nitrogen-doped carbon nanosheet/poly(amidoamine) dendrimer-based electrochemical sensor for nicotine in flavored hookah pipe tobacco.
- Source :
-
Analytical methods : advancing methods and applications [Anal Methods] 2024 Nov 14; Vol. 16 (44), pp. 7518-7526. Date of Electronic Publication: 2024 Nov 14. - Publication Year :
- 2024
-
Abstract
- Towards the nicotine addiction challenge in the smoking of hookah pipe products, we hereby present the development of an electrochemical sensor for nicotine detection. A nitrogen-doped carbon nanosheet (N-CNS)/poly(amidoamine) dendrimer (PAMAM) nanocomposite-modified electrode was prepared as a sensor for the detection of nicotine in analytical and real samples. The N-CNSs were prepared by a hydrothermal method and dropcast on a glassy carbon electrode followed by electro-deposition of the PAMAM dendrimer to form the sensor (GCE/N-CNSs/PAMAM). The N-CNSs were characterized with electron microscopy, Raman spectroscopy and FTIR. The sensor was characterized with voltammetry and electrochemical impedance spectroscopy. The N-CNS/PAMAM enhanced the electrochemical performance of the electrode towards the oxidation of nicotine. The sensor achieved a detection limit of 0.05 μM in a linear concentration range of 1.93-61.64 μM nicotine standard samples. The sensor showed good reproducibility, repeatability, and selectivity. The sensor was successful in selectively detecting nicotine in two local brands of hookah pipe tobacco with a 113-121 percent recovery. Nicotine, up to a concentration of 0.35-0.39 mg g <superscript>-1</superscript> , was found in the sampled hookah pipe tobacco products suggesting possible harm to human health.
- Subjects :
- Limit of Detection
Tobacco Products analysis
Reproducibility of Results
Electrodes
Nanostructures chemistry
Nanocomposites chemistry
Polyamines
Nicotine analysis
Carbon chemistry
Nitrogen chemistry
Nitrogen analysis
Electrochemical Techniques methods
Electrochemical Techniques instrumentation
Dendrimers chemistry
Subjects
Details
- Language :
- English
- ISSN :
- 1759-9679
- Volume :
- 16
- Issue :
- 44
- Database :
- MEDLINE
- Journal :
- Analytical methods : advancing methods and applications
- Publication Type :
- Academic Journal
- Accession number :
- 39370887
- Full Text :
- https://doi.org/10.1039/d4ay01257g