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Research Article | Open Access | Just Accepted

Single cobalt sites on defective carbon nanosheets as efficient oxidase mimics for visual biosensing

Xueli ZhangChenyu TaoShushu ChuWendong Liu()Mingyuan XiaYuanyuan Jiang()Yizhong Lu()

School of Materials Science and Engineering, University of Jinan, Jinan 250022, China

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Abstract

Single-atom cobalt catalysts have been recognized as promising alternatives to natural enzymes. However, their relatively low catalytic activity greatly limits their further application. Herein, we demonstrate that single cobalt sites immobilized on  defective carbon nanosheets (2D Co-CN(H)) can act as efficient oxidase mimics with high atom utilization efficiency. In particular, the 2D Co-CN(H) catalysts are found to be twice as effective as defect-free Co-CN catalysts. Combined experimental and theoretical analyses reveal that the defects around atomic cobalt sites can rationally regulate the electronic distribution, significantly promoting the cleavage of O-O bonds and thus improving their oxidase-like performance. The oxidase-like activity of 2D Co-CN(H) catalysts can effectively catalyze the oxidization of 3,3',5,5'-tetramethylbenzidine (TMB) into oxidized TMB (oxTMB) with sensitive colorimetric readout. And the oxTMB generated can also serve as a photothermal agent to convert the colorimetric readout into heat under near-infrared (NIR) irradiation. Taking advantage of the excellent oxidase-like activity of 2D Co-CN(H) catalysts and the good photothermal properties of oxTMB, an innovative dual-mode colorimetric-photothermal sensing platform toward effective discrimination and detection of dihydroxybenzene isomers has been successfully constructed. This study not only highlights the important role of defects on the oxidase-like activity of single-atom nanozymes, but also broadens their potential applications in environmental conservation.

Nano Research
Cite this article:
Zhang X, Tao C, Chu S, et al. Single cobalt sites on defective carbon nanosheets as efficient oxidase mimics for visual biosensing. Nano Research, 2025, https://doi.org/10.26599/NR.2025.94907336
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