Electrochemically amplified nanozymatic activity of biolinker-based Co-MOF for H2O2 and dopamine detection

Abstract

Rapid, sensitive and selective H2O2 and dopamine sensors provide enormous opportunities to health, food and environmental monitoring, which could prevent major social and economic losses. To overcome the sluggish response and low sensitivity of the conventional colorimetric assays, an electrochemical platform integrated with the conventional assay was proposed in this work. First, a microwave-assisted cobalt MOF (Co-MOF) was synthesized using a bio-linker and characterized using FESEM and TEM. The electrochemical performance of Co-MOF was examined through cyclic voltammetry (CV), where eight-fold higher currents were achieved for Co-MOF compared to those of the unmodified electrode. However, Co-MOF exhibits very weak nanozymatic activity in a mixture of 3,3′,5,5′-tetramethylbenzidine (TMB) and H2O2. Integration of the superior electrochemical characteristics of Co-MOF with the nanozymatic activity resulted in a six-fold enhanced nanozymatic activity that enabled H2O2 quantification with a limit of detection (LOD) of 32 nM under optimized conditions. The modified electrode was further used to quantify dopamine, achieving an LOD of 0.81 µM, with a remarkably shorter detection time (60 fold shorter) compared to the conventional nanozyme. A mechanistic study showed that Co-MOF provides a large surface area and abundant redox-active sites, facilitating fast electron transfer and significantly enhancing the electrochemical signal.

Graphical abstract: Electrochemically amplified nanozymatic activity of biolinker-based Co-MOF for H2O2 and dopamine detection

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Article information

Article type
Paper
Submitted
01 Mar 2026
Accepted
22 Apr 2026
First published
22 Apr 2026
This article is Open Access
Creative Commons BY-NC license

Anal. Methods, 2026, Advance Article

Electrochemically amplified nanozymatic activity of biolinker-based Co-MOF for H2O2 and dopamine detection

J. Look, S. R. Ahmed, M. H. Mahana, Md. Shalauddin, S. Akhter, W. J. Basirun, S. Srinivasan and A. R. Rajabzadeh, Anal. Methods, 2026, Advance Article , DOI: 10.1039/D6AY00361C

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