Enhanced electrochemical glucose sensing of Co/Cu-MOF by hydroxyl adsorption induced reactive oxygen species
Exploring the factors affecting the electrochemical catalytic signal of an organic-metal material sensor and analyzing the decisive steps of the glucose oxidation behavior are challenging problems. Here, we designed a copper-cobalt-based organic backbone with excellent sensing properties based on th...
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Veröffentlicht in: | Analytical methods 2023-06, Vol.15 (22), p.2766-2772 |
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Sprache: | eng |
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Zusammenfassung: | Exploring the factors affecting the electrochemical catalytic signal of an organic-metal material sensor and analyzing the decisive steps of the glucose oxidation behavior are challenging problems. Here, we designed a copper-cobalt-based organic backbone with excellent sensing properties based on the nanostructure of "ultramicroelectrodes", and explored the role of different hydroxyl adsorption capacities in the sensing process of glucose oxidation. Dimethylimidazole was used as a starting substrate, and then copper and cobalt ions were introduced by hydrothermal treatment to prepare a copper-cobalt-based organic backbone (Co/Cu-MOF) with good electrochemical glucose sensing ability. Due to the abundant micro-reaction sites of Co/Cu-MOF and the ability to control the hydroxyl group adsorption by adjusting the Co/Cu ratio, excellent electrocatalytic sensing performance was ensured. Co/Cu-MOF (Co/Cu molar ratio of 20 : 1) showed the best adsorption capacity for hydroxyl groups with a sensitivity of 0.45 mA mM
−1
cm
−2
and a LOD of 0.82 μM in electrochemical glucose sensing. In summary, the sensing performance was effectively improved by adding adsorbed hydroxyl groups to provide an oxygen source for the glucose oxidation step without changing the specific components.
Here, we designed a copper-cobalt-based organic backbone with excellent sensing properties based on the nanostructure of "ultramicroelectrodes", and explored the role of different hydroxyl adsorption capacities for glucose oxidation. |
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ISSN: | 1759-9660 1759-9679 |
DOI: | 10.1039/d3ay00441d |