Acetone gas sensor based on chitosan-metal-organic framework mixed matrix membranes for diabetes diagnosis
Detecting diabetes in its early stages through non-invasive methods remains a major challenge for researchers. One promising approach involves the development of a rapid and sensitive chemiresistive sensor to measure acetone levels in exhaled breath-a potential biomarker for diabetes. In this study,...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
|
| Series: | Carbohydrate Polymer Technologies and Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666893925000015 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Detecting diabetes in its early stages through non-invasive methods remains a major challenge for researchers. One promising approach involves the development of a rapid and sensitive chemiresistive sensor to measure acetone levels in exhaled breath-a potential biomarker for diabetes. In this study, we successfully fabricated a novel composite sensor comprising chitosan, a linear polysaccharide, combined with a metal-organic framework (UiO-66-NH2 MOF) and the ionic liquid glycerol. This combination enhances the film-forming properties of the material, leveraging the MOF's high surface area and selective adsorption capabilities for superior performance.The sensor was designed to detect acetone through chemiresistive sensing and demonstrated remarkable response to acetone concentrations as low as 1 ppm. Operating at a low temperature of 60 °C with a bias voltage of 4 V, the sensor exhibited excellent functionality even in high-humidity environments. Furthermore, it showed good repeatability, long-term stability, and fast response and recovery times of 23 ± 0.25 s and 18 ± 0.1 s, respectively.These characteristics make the sensor suitable for biomedical applications. Its flexibility and eco-friendly design further underscore its potential as a real-time breath analyzer for diabetes detection. The results of this study suggest a promising pathway for future clinical implementation of this technology. |
|---|---|
| ISSN: | 2666-8939 |