Smart Prussian Blue Analog Decorated with Zinc Oxide Nanohybrid: Fluorescent Sensing and Sustainability of Sunset Yellow in Food and Environment

普鲁士蓝 荧光 检出限 柠檬黄 材料科学 纳米技术 光漂白 微晶 分析化学(期刊) 化学 光学 环境化学 色谱法 冶金 物理 电极 物理化学 电化学
作者
Hany A. Batakoushy,Amr K. A. Bass,Hassanien Gomaa,Sami El Deeb,Adel Ehab Ibrahim
出处
期刊:Biosensors [Multidisciplinary Digital Publishing Institute]
卷期号:15 (4): 263-263
标识
DOI:10.3390/bios15040263
摘要

In the current study, the Prussian blue analog decorated with zinc oxide (PBA@ZnO) was produced using a simple chemical co-precipitation method. The nanohybrid was examined using XRD, EDX, SEM, and TEM techniques, where it exhibited a polycrystalline structure with highly intense broadening peaks. The surface morphology was observed as thin nanosheets decorated with tiny spheres. Following excitation at 360 nm, the fluorescence spectra of PBA@ZnO showed fluorescence emission at 455 nm. The developed PBA@ZnO was used to qualitatively and quantitatively assess sunset yellow (SY), where its native fluorescence was selectively quenched as SY concentrations increased. For the first time, PBA@ZnO was used as a turn-off nano-sensor for the spectrofluorimetric measurement of SY. The method’s markable sensitivity was demonstrated within an SY linearity range of 50–500 ng/mL, where the limit of detection was calculated as 9.77 ng/mL. Real sample analysis in the food industry, including samples from real food, soft drinks, and sun cream, was made possible by the detection of tiny amounts of SY. Analytical Greenness (AGREE), AGREEprep, and the complementing Green Analytical Procedure Index (Complex MoGAPI) were used to illustrate the new approach’s exceptional eco-friendliness and greenness. The RGB 12 algorithm worked to demonstrate that the suggested approach is less costly, more environmentally friendly, more sustainable, analytically sound, and whiter than the ones that were previously published. In accordance with ICH principles, the suggested method was validated. This approach offers a promising way to rapidly and accurately identify and measure SY in the food industry, helping to guarantee food safety and maintain the health of customers.
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