4.7 Article

Nanocomposite of gold nanoparticles@nickel disulfide-plant derived carbon for molecularly imprinted electrochemical determination of favipiravir

期刊

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.jelechem.2022.116745

关键词

Favipiravir; Biomass-derived carbon; Nickel disulfide nanospheres; Gold nanoparticles; p-Aminothiophenol; Molecular imprinted technology

资金

  1. Deanship of Scientific Research at Umm Al-Qura University [22UQU4290565DSR67]

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A molecularly imprinted electrochemical sensor was developed for sensitive and selective detection of the antiCOVID 19 drug favipiravir (FAV). The sensor exhibited high sensitivity and selectivity, and was successfully applied to detect FAV in tablets and human serum samples.
A molecularly imprinted electrochemical sensor was fabricated for sensitive and selective detection of antiCOVID 19 drug favipiravir (FAV). The sensor is based on the synthesis of biomass-derived carbon (BC) and nickel disulfide nanospheres (NiS2 NS), which were used to decorate glassy carbon electrode (GCE). Then, the gold nanoparticles (AuNPs) were electro- deposited on the surface of NiS2 NS/BC/GCE to enhance conductivity, increase electron transfer, and aid polymerization of p-aminothiophenol (p-ATP) functional monomer. The fabrication steps were characterized using different morphological and electrochemical techniques. Variables affecting the formation of molecularly imprinted layers and the determination of FAV were optimized. Under optimum conditions, the oxidation current (Ipa) was increased upon addition of FAV in the range of 0.42 -1100 nM with a limit of detection (LOD, S/N) of 0.13 nM. The as-fabricated sensor possesses several advantages such as high sensitivity and selectivity, good reproducibility, and acceptable stability. Furthermore, the proposed molecularly imprinted -based electrochemical sensor was efficiently applied for the determination of FAV in tablets and human serum samples with recoveries % of 99.2 to 102.1 % and RSDs % in the range of 2.4 -3.2 %, which confirms the reliability of the sensor to detect FAV in different matrices.

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