Journal
COLLOIDS AND SURFACES A-PHYSICOCHEMICAL AND ENGINEERING ASPECTS
Volume 598, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.colsurfa.2020.124816
Keywords
Ag-CuO nanocomposite; Multicore-shell heterostructures; Non-enzymatic glucose detection; CuO based electrochemical glucose sensors
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Funding
- Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education, Science and Technology [2017R1A2B4007213]
- Incheon National University
- National Research Foundation of Korea [2017R1A2B4007213] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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This article describes a non-enzymatic electrocatalyst with high sensitivity and selectivity towards glucose. The electrocatalyst is based on a multicore-shell Ag-CuO nanocomposite networked with CuO nanorods. The composition of Ag-CuO plays a critical role in the formation of the unique network-like structure of Ag-CuO as well as in its electrocatalytic and sensing effects towards glucose. The electrocatalytic activity of CuO towards glucose was drastically improved by the incorporation of silver nanoparticles (Ag NPs) into the CuO nanostructures, which was accompanied by a substantial decrease in the charge transfer resistance (as confirmed by electrochemical impedance spectroscopic analysis). Among the different Ag-CuO composites prepared by varying the Ag-to-Cu atomic ratio, Ag-CuO(1:2.5) exhibited the best electrocatalytic activity towards glucose. The limit of detection and sensitivity of the Ag-CuO(1:2.5)-modified electrode were calculated to be 5 mu M and 150.17 mu A mM(-1) cm(-2), respectively, with a wide glucose detection range from 5 mu M to 30 mM. Furthermore, the Ag-CuO(1:2.5) electrode exhibited excellent selectivity towards glucose in the presence of typical interfering agents (i.e., ascorbic acid, uric acid, dopamine, sucrose and NaCl) in blood. The Ag-CuO(1:2.5)-modified electrode further showed excellent reproducibility (relative standard deviation (RSD) of 2.9 %) and repeatability.
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