基于钴酸锌纳米花嵌入多孔3D还原氧化石墨烯的新型电化学传感器对乳制品中必需氨基酸的纳摩尔检测

Neethu Sebastian , Wan-Chin Yu , Deepak Balram , Ashish Patel , Deepak Kumar , Virendra Kumar Yadav
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摘要

l -色氨酸(L-Trp)是一种影响神经功能、免疫和肠道稳态的重要氨基酸,在食物样品中准确检测它是至关重要的。本研究的目的是将钴酸锌(ZCO)纳米颗粒和3D多孔还原氧化石墨烯(rGO)集成在丝网印刷碳电极(SPCE)表面,构建一种新型电化学传感器,以灵敏地检测食品中的l -色氨酸。采用低温水溶液法合成ZCO纳米花,水热法制备三维还原氧化石墨烯。对制备的纳米复合材料ZCO/3DrGO进行了SEM、元素图、XRD、拉曼光谱、XPS和EIS表征。采用循环和差分脉冲伏安法进行电化学实验,对ZCO/3DrGO/SPCE的催化性能进行了有效评价。低检出限为3 nM,高灵敏度为19.53 μ a - μ m - 1cm - 2,线性范围为0.08 ~ 5.93;5.93 ~ 87.18 μM,传感器对L-Trp具有良好的电催化活性。通过对l -色氨酸的稳定性、重复性、再现性和选择性分析,验证了该传感器的可靠性。利用该传感器成功检测乳制品(酸奶、牛奶和白干酪)中的l -色氨酸,回收率高达98.16% ~ 101.16%,RSD低至2.8%,证明了该传感器的实际可行性。
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Nanomolar detection of essential amino acid in dairy products using a novel electrochemical sensor based on zinc cobaltite nanoflowers embedded porous 3D reduced graphene oxide

L-tryptophan (L-Trp) is a vital amino acid that sways neuronal function, immunity, and gut homeostasis, and its accurate detection in food samples is crucial. The aim of this study is to integrate zinc cobaltite (ZCO) nanoparticles and 3D porous reduced graphene oxide (rGO) on a screen-printed carbon electrode (SPCE) surface for building a novel electrochemical sensor to sensitively detect L-Trp in food products. A low-temperature aqueous solution method was employed in ZCO nanoflower synthesis and a hydrothermal approach was utilized to prepare 3D rGO. SEM, elemental mapping, XRD, Raman spectroscopy, XPS, and EIS characterizations were performed on the prepared nanocomposite, ZCO/3DrGO. Electrochemical experiments conducted with the cyclic and differential pulse voltammetric techniques were used for effectively assessing the catalytic power of ZCO/3DrGO/SPCE. With a low detection limit of 3 nM, high sensitivity of 19.53 μAμM−1cm−2, and a broad linear range of 0.08–5.93; 5.93–87.18 μM, the sensor demonstrated promising electrocatalytic activity towards L-Trp. Further, the reliability of the sensor was proved by analyzing its stability, repeatability, reproducibility, and selectivity towards L-Trp. The successful detection of L-Trp in dairy products (yogurt, milk, and cottage cheese) using the proposed sensor evinced its practical feasibility with high recovery of 98.16%–101.16% and low RSD of 2.8%.

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