WS2/CuO-based non-enzymatic sensor for the detection of glucose in sweat.

Dujuan Li, Mingzhu Yang, Wenhui Li, Ao Wang, Xinyi Wang, Liang Hong, Linxi Dong, Hong Xu, Gaofeng Wang

Journal: Analytica chimica acta 2025;1378():344696

PMID: 41135996

Abstract

BACKGROUND

Traditional blood glucose monitoring requires piercing the skin to obtain blood samples, which brings inconvenience and discomfort to diabetic patients. Sweat glucose content has been proven to be related to blood glucose concentration, so sweat glucose detection shows significant advantages in non-invasive blood glucose monitoring. The performance of enzyme-based glucose sensors is easily affected by external environments such as temperature and pH. Therefore, there is an urgent need to develop non-enzymatic glucose sensors with good stability, low cost and high performance for sweat glucose detection.

RESULTS

In this study, a non-enzymatic glucose sensor had been successfully fabricated by integrating copper oxide (CuO) nanoparticles with tungsten disulfide (WS2) nanosheets obtained via a liquid-phase exfoliation method. The sensor was characterized using scanning electron microscopy (SEM) and electrochemical measurements, showing that WS2/CuO nanocomposites formed a honeycombed-like surface improving the catalytic ability of glucose. The fabricated non-enzymatic amperometric glucose sensor is capable of detecting a wide range of target concentrations, from 0.1 mM to 20 mM. The experiment found that the sensor response signal has a linear relationship with the target concentration in the range of 0.1 mM-2 mM and 2 mM-20 mM, respectively, and the corresponding detection sensitivities are 311.23 μA mM-1 cm-2 and 238.3 μA mM-1 cm-2 under optimized experimental conditions. The sensor has a detection limit as low as 0.65 μM. The sensor also has good selectivity, repeatability, reproducibility and stability. Finally, the fabricated sensor was applied to the detection of glucose in artificial sweat and human sweat.

SIGNIFICANCE

The experimental results compared with the spectrophotometric method illustrate the excellent accuracy of the non-enzymatic glucose sensor proposed in this study in detecting real sweat sample analysis, highlighting its great potential for future practical applications.

Copyright © 2025 Elsevier B.V. All rights reserved.

Address: Ministry of Education Engineering Research Center of Smart Microsensors and Microsystems, School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, 310018, China. Electronic address: [email protected].; Ministry of Education Engineering Research Center of Smart Microsensors and Microsystems, School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, 310018, China.; Ministry of Education Engineering Research Center of Smart Microsensors and Microsystems, School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, 310018, China. Electronic address: [email protected].; Department of Infectious Diseases, The Third Affiliated Hospital of Wenzhou Medical University (Ruian People's Hospital), Ruian, 325200, China. Electronic address: [email protected].; Guangdong Technology Research Center for Marine Algal Bioengineering, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, 518060, China.
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