Highly exposed Cu active sites as efficient peroxidase mimics for colorimetric analysis

Abstract

Nanozymes are nanomaterials with intrinsic enzyme-mimic activity, but their large-scale application is generally limited by their low catalytic activity. Herein, we demonstrated that highly exposed Cu active sites on two-dimensional (2D) nitrogen-doped carbon (Cu_x/NC) can serve as efficient peroxidase-like (POD) catalysts with high atomic utilization. Specially, the uniformly distributed Cu active sites could react with H₂O₂ to produce singlet oxygen (¹O₂) under acidic conditions, which can efficiently oxidizes colorless 3,3′, 5,5′-tetramethylbenzidine (TMB) to blue oxidized TMB (oxTMB). Among various Cu_x/NC nanozymes studied, the Cu_0.14/NC exhibited smaller maximum catalytic velocities (V_max) and Menten constant (K_m) for TMB and H₂O₂. Benefiting from the highly active peroxidase-like activity, the Cu_0.14/NC nanozyme could be successfully applied for the hydroquinone (HQ) and ascorbic acid (AA) detection applications through the inhibitory effect of HQ and AA. More interestingly, α-glucosidase (α-Glu) detection sensing platform could be constructed based on HQ as a signal transmitter, with the detection range ranging from 0 to 12 U/L and the minimum detection limit being 0.68 U/L. This work provides not only an idea for the rational design of highly exposed Cu active sites but also fabricate an effective detection sensing platform for HQ, AA, and α-Glu detection.

Keywords

Nanozyme / Highly exposed active sites / Peroxidase-like / $\alpha $\alpha-glucosidase / Sensing

Ethics approval

Experimental design and procedures were approved by the Ethics Committee of University of Jinan (UJN-MSE-2023-002). Written informed consent was obtained from all participants.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CRediT authorship contribution statement

Hengya Wei: Investigation, Writing - original draft, Writing - review & editing. Shushu Chu: Investigation, Validation. Fangning Liu: Formal analysis, Data curation. Shengzhen Li: Supervision. Yizhong Lu: Conceptualization, Methodology, Resources.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (22172063), the Young Taishan Scholar Program (tsqn201812080) and the Independent Cultivation Program of Innovation Team of Jinan City (2021GXRC052).

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.chphma.2023.12.001.

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