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Hydrogen peroxide (H 2 O 2) is a common oxidant that plays an important role in many biological processes and is also an important medium analysis in various fields. In this work, a new electrochemical nanosensor capable of detecting and quantifying hydrogen peroxide was introduced. This nanosensor was fabricated by electrodepositing prussian blue (PB)/graphene quantum dots (GQDs)/polypyrrole (PPy) on single nanopore electrode etched from single gold nanoelectrode. This prepapred nanosensor exhibits good electrochemical response to hydrogen peroxide with high sensitivity and stability, with a linear response in the 2.0 and 80 μM by using amperometric method and differential pulse voltammetry (DPV) method. The limit of detections are 0.33 μM (S/N = 3) for amperometric method and 0.67 μM (S/N = 3) for differential pulse voltammetry (DPV) method, respectively. This nanosensor can be used for the determination of hydrogen peroxide in human urine, and can serve as a new electrochemical platform to monitor H 2 O 2 release from single living cells due to its small overal dimension and high sensitivity. [Display omitted] • Nanosensor was fabricated on single nanopore electrode filled with Prussian blue and graphene quantum dots coated by Polypyrrole. • New nanosensor shows good electrocatalytic activity towards H2O2 oxidation. • This nanosensor can serve as a new electrochemical platform to monitor H2O2 release from single living cells due to its small overal dimension. [ABSTRACT FROM AUTHOR]

A new nanozyme (CuGaa) with switchable enzyme-like activity of peroxidase and polyphenol oxidase was successfully prepared based on guanidinoacetic acid and copper. The two enzyme-like activities can be easily switched by changing temperature or adding MnCl 2. At 4 °C, polyphenol oxidase-like activity decreased to nearly 1%, and the material is mainly characterized by peroxidase-like activity at this point. However, at 60 °C in the presence of 20 mM MnCl 2 , the peroxidase-like activity decreased to nearly 10%, and the polyphenol oxidase-like activity of the materials increased to 140%. Based on the switchable enzyme-like activity of CuGaa, detection methods for thymol and hydrogen peroxide were developed. In addition, a rapid combination strategy was further established combined with logic gate technology for the facile identification of complex contamination in honey, which provided new ideas for low-cost and rapid honey identification. The graphic descriptives that CuGaa has polyphenol oxidase-like and peroxidase-like activities, and that under different conditions, CuGaa can be made to exhibit only one enzyme activity. [Display omitted] • Nanozyme with switchable enzyme-like activity. • Thymol detection at high temperature based on the nanozyme. • A sensing strategy combined with logic gate technology. • A facile identification of complex contamination in honey. [ABSTRACT FROM AUTHOR]

A novel sensor array was developed based on the enzyme/nanozyme hybridization for the identification of tea polyphenols (TPs) and Chinese teas. The enzyme/nanozyme with polyphenol oxidase activity can catalyze the reaction between TPs and 4-aminoantipyrine (4-AAP) to produce differences in color, and the sensor array was thus constructed to accurately identify TPs mixed in different species, concentrations, or ratios. In addition, a machine learning based dual output model was further used to effectively predict the classes and concentrations of unknown samples. Therefore, the qualitative and quantitative detection of TPs can be realized continuously and quickly. Furthermore, the sensor array combining the machine learning based dual output model was also utilized for the identification of Chinese teas. The method can distinguish the six teas series in China, and then precisely differentiate the more specific tea varieties. This study provides an efficient and facile strategy for the identification of teas and tea products. [Display omitted] • A novel sensor array was developed based on the enzyme/nanozyme hybridization. • Six TPs in Chinese tea were successfully distinguished. • Effective identification of six major teas series and more specific 17 tea varieties. • Machine learning based dual output model for TPs' qualitation and quantitation. • Machine learning based dual output model for identifying tea samples. [ABSTRACT FROM AUTHOR]