Cauliflower-like CuO-ZnO modified glassy carbon electrode as an electrochemical platform for the detection of hydrogen peroxide in adulterated milk

IF 5.3 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchimica Acta Pub Date : 2025-04-01 DOI:10.1007/s00604-025-07130-z

Haiyan Song, Haobin Hu, Zhijun Li, Yun Wu, Chunxiao He, Yuanyuan Gao, Nana Hou, Qiqi He, Zhenyu Cheng

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引用次数: 0

Abstract

The detection of hydrogen peroxide (H₂O₂) is a crucial process in various industries, including food safety. In this study, a cauliflower-like CuO-ZnO composite with p–n junction was successfully synthesized using a straightforward one-pot hydrothermal method. The resulting material demonstrates outstanding electrocatalytic performance for H₂O₂ detection, outperforming the individual components. The electrochemical sensor constructed from the cauliflower-like CuO-ZnO composite exhibits a well-defined linear response in the concentration range 0.0005 to 0.105 mmol·L⁻¹ for H₂O₂. The sensor’s limit of detection (LOD) is 0.21 µmol·L⁻¹ at a signal-to-noise ratio (S/N) of 3, with a sensitivity of 1582.7 µA·(mmol·L⁻¹)⁻¹·cm⁻². Furthermore, the sensor has been successfully applied to detect trace amounts of H₂O₂ in milk samples, showcasing its potential for sensitive electrochemical sensing applications.

Graphical Abstract

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菜花状氧化锌修饰玻碳电极作为检测掺假牛奶中过氧化氢的电化学平台

过氧化氢（h2o2）的检测是包括食品安全在内的各个行业的关键过程。在本研究中，利用简单的一锅水热法成功合成了具有p-n结的菜花状CuO-ZnO复合材料。所得材料在H₂O₂检测方面表现出出色的电催化性能，优于单个组分。由花椰菜状CuO-ZnO复合材料构建的电化学传感器在H₂O₂的浓度范围为0.0005至0.105 mmol·L⁻1之间具有良好的线性响应。该传感器的检测限（LOD）为0.21µmol·L毒血症，信噪比（S/N）为3，灵敏度为1582.7µa·（mmol·L毒血症）·cm毒血症。此外，该传感器已成功应用于检测牛奶样品中的微量h2o₂，展示了其敏感电化学传感应用的潜力。图形抽象

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来源期刊

Microchimica Acta 化学-分析化学

CiteScore

9.80

自引率

5.30%

发文量

410

审稿时长

2.7 months

期刊介绍： As a peer-reviewed journal for analytical sciences and technologies on the micro- and nanoscale, Microchimica Acta has established itself as a premier forum for truly novel approaches in chemical and biochemical analysis. Coverage includes methods and devices that provide expedient solutions to the most contemporary demands in this area. Examples are point-of-care technologies, wearable (bio)sensors, in-vivo-monitoring, micro/nanomotors and materials based on synthetic biology as well as biomedical imaging and targeting.