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Investigation of Glucose Sensing via Controlled Copper Concentration in CuO for Non-Enzymatic Glucose Biosensor
Non-enzymatic glucose sensors have emerged as pivotal tools for monitoring blood glucose levels, offering advantages over traditional enzymatic methods in terms of sensitivity, selectivity, and cost-effectiveness. This study explores the utilization of a simple and low-cost method for preparation of...
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Published in: | ECS journal of solid state science and technology 2023-11, Vol.12 (11), p.117004 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Non-enzymatic glucose sensors have emerged as pivotal tools for monitoring blood glucose levels, offering advantages over traditional enzymatic methods in terms of sensitivity, selectivity, and cost-effectiveness. This study explores the utilization of a simple and low-cost method for preparation of copper oxide (CuO) nanostructures to look for the non-enzymatic glucose sensing. Morphological and structural analysis via Scanning Electron Microscopy and X-ray diffraction of synthesized CuO nanostructures revealed nearly same size, shape, and a pure monoclinic crystal structure. Fourier transform infrared spectroscopy further confirmed the monoclinic phase. More importantly, we employed CuO nanostructures-modified glassy carbon electrodes (GCE) to investigate the glucose sensing and sensing parameters. The electrodes exhibited comparable sensitivity, selectivity, and an extended dynamic range 0.4–0.6 V applied potentials with regard to earlier reports. Amperometric responses of lower concentration based synthesized CuO sample recorded at 0.5 V unveiled a low limit of detection of 5.9
μ
M, a sensitivity of approximately 10.6
μ
A/(mM·cm
2
), and a rapid 2 s response time. Manipulating the CuO-nanostructures and integrating on the GCE can offer a promising opportunity for enhanced non-enzymatic glucose sensing with high sensitivity, selectivity, and broad dynamic range towards utility in real-time glucose monitoring, contributing to improved healthcare diagnostics and diabetes management. |
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ISSN: | 2162-8769 2162-8777 |
DOI: | 10.1149/2162-8777/ad0aad |