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  • Title: 3D Carbon-Based Conductive Network Printed for Glucose Sensors on Curved and Flexible Substrates.
    Author: Cong C, Subramanian S, Bodkhe GA, Wang G, Li Z, Wang R, Li X, Kim M, Kim SH.
    Journal: ACS Appl Mater Interfaces; 2024 Feb 14; 16(6):7543-7553. PubMed ID: 38297812.
    Abstract:
    The rising prevalence of diabetes has led to an increased focus on real-time glucose monitoring. Wearable glucose sensor patches allow noninvasive, real-time monitoring, reducing patient discomfort compared to invasive sensors. However, most existing glucose sensor patches rely on complex and contaminating metal vapor deposition technologies, which pose limitations in practical production. In this study, we propose a novel approach for preparing graphite/multiwall carbon nanotubes (MWCNT)/reduced graphene oxide (rGO) using a high-viscosity ink, which can be easily obtained through simple mechanical stirring. To create intricate patterns and enable printing on curved substrates, we employed a 3D printer equipped with an infrared laser ranging system. The ink served as a working electrode, and we developed a three-electrode system patch with a concentric circle structure. Subsequently, the working electrode underwent enzymatic modification with glucose dehydrogenase with flavin adenine dinucleotide (GDH-FAD) using a polymer embedding method. The resulting wearable glucose sensor exhibited a sensitivity of 2.42 μA mM-1 and a linear detection range of 1-12 mM. In addition, the glucose sensor has excellent anti-interference capability and demonstrates good repeatability in simulated real human wear scenarios, which meets the requirements for accurate human detection. These findings provide valuable insights into the development of human health monitoring technologies.
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