A nitrogen-doped carbon nanosheet/poly(amidoamine) dendrimer-based electrochemical sensor for nicotine in flavored hookah pipe tobacco

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−1, was found in the sampled hookah pipe tobacco products suggesting possible harm to human health.

Graphical abstract: A nitrogen-doped carbon nanosheet/poly(amidoamine) dendrimer-based electrochemical sensor for nicotine in flavored hookah pipe tobacco

Supplementary files

Article information

Article type
Paper
Submitted
04 Jul 2024
Accepted
10 Sep 2024
First published
26 Sep 2024
This article is Open Access
Creative Commons BY license

Anal. Methods, 2024, Advance Article

A nitrogen-doped carbon nanosheet/poly(amidoamine) dendrimer-based electrochemical sensor for nicotine in flavored hookah pipe tobacco

S. Makaluza, N. Midzi, F. O. G. Olorundare, D. S. Sipuka, T. I. Sebokolodi, D. Nkosi and O. A. Arotiba, Anal. Methods, 2024, Advance Article , DOI: 10.1039/D4AY01257G

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