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Updated: May 17, 2025

Principles of Site-Specific Recombinase SSR Technology
Published on: May 29, 2008
ZrS2 Nanoparticles Embedded in Chitosan-Based Hydrogel for the Electrochemical Detection of Antimalarial Drug
Divyasri Ramasamy1,2, Gopika Mukundan3, Manaswini Ravipati2
1Center for Interdisciplinary Programs, Indian Institute of Technology, Hyderabad 502284, India.
Abstract:
In this study, we report the synthesis of ZrS2 nanoparticles embedded in a chitosan-based hydrogel (ZrS2/CS hydrogel) for the electrochemical detection of amodiaquine (ADQ). The ZrS2 nanoparticles are synthesized via a hydrothermal synthesis technique. Morphologically, transmission electron microscopy images show that the ZrS2 nanoparticles agglomerated to form nanoclusters. Scanning electron microscopy images reveal the porous interconnected structure of the stacked hydrogel layer with ZrS2 nanoparticles that have a high surface area and electrochemically active sites. These ZrS2 nanoparticles embedded in the hydrogel enhanced the high electron transport during the redox process. Differential pulse voltammetry is employed to electrochemically detect ADQ in a wide linear range of 0.02 nM to 2 μM. The sensitivity of ADQ is calculated to be 1.138 μA/nM with a limit of detection of 0.4 nM and a limit of quantification of 1.33 nM. The possible mechanism behind the enhanced performance can be ascribed to the electrochemical oxidation of ADQ, its corresponding quinone-imine, and the improved interaction between the electrode and electrolyte solution, leading to enhanced electron transfer and more stable signals for electrochemical sensing. The sensor developed here has a highly selective response toward ADQ over other interferents such as NaCl, urea, uric acid, glucose, ascorbic acid, and dopamine. In simulated human serum, the sensor shows a recovery rate from 98.58 to 100.62%, suggesting its potential in developing electrochemical sensors. The repeatability and reproducibility results of the ZrS2/CS hydrogel show excellent consistent results, with relative standard deviations of 3.41 and 3.46%, respectively, further affirming the reliability of the sensor. This approach opens up future research directions for detecting various analytes in point-of-care and other biomedical devices.
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