Issue 19, 2023

A sensitive and facile electrochemical paper-based sensor for glucose detection in whole blood using the Pd/CB-Ni@rGO modified electrode

Abstract

We created novel Pd/CB-Ni@rGO nanomaterials for glucose detection. The as-synthesized nanomaterials were dropped on the electrode surface using the drop casting technique. The prepared electrode was then attached to a paper-based device containing the sample zone and the reaction zone, enabling plasma isolation and an enzymatic reaction for glucose detection in whole blood. The nanomaterials and surfaces of electrodes were characterized by FTIR, TEM, and SEM. The proposed approach is a disposable glucose detection method that is unaffected by protein fouling on the electrode, and it requires only one drop of human blood. Therefore, there is no need for extensive sample preparation, and there is less sample consumption. Under optimal conditions, Pd/CB-Ni@rGO can accurately measure blood glucose levels with a linear range of 7 to 7140 μM (R2 = 0.9986) and a low detection limit of 0.82 μM. Besides, the developed sensor shows excellent anti-interference capacity, stability, and satisfactory reproducibility and repeatability. Importantly, Pd/CB-Ni@rGO was successfully applied for glucose in whole blood from 4 volunteers, with results that correlated well with those obtained using an Accucheck glucometer at a 95% confidence level. Given its low cost, high accuracy, and ease of use, the blood glucose sensor holds significant potential for clinical use and broadens the area of future noninvasive sensor development.

Graphical abstract: A sensitive and facile electrochemical paper-based sensor for glucose detection in whole blood using the Pd/CB-Ni@rGO modified electrode

Supplementary files

Article information

Article type
Paper
Submitted
31 May 2023
Accepted
01 Aug 2023
First published
17 Aug 2023

Analyst, 2023,148, 4753-4761

A sensitive and facile electrochemical paper-based sensor for glucose detection in whole blood using the Pd/CB-Ni@rGO modified electrode

C. Math, K. Income, K. Khachornsakkul, P. Duenchay and W. Dungchai, Analyst, 2023, 148, 4753 DOI: 10.1039/D3AN00879G

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