A passive Lab-on-PCB microsystem for non-enzymatic quantification of glucose
This paper presents and successfully demonstrates a new form of passive Lab-on-printed circuit board (PCB) diagnostic platform for the quantification of glucose, as required for pumpless applications such as wearable diagnostic patches. The platform exploits copper oxide (CuO) nanoparticles for non-...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-10-01
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| Series: | Biosensors and Bioelectronics: X |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590137025000974 |
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| Summary: | This paper presents and successfully demonstrates a new form of passive Lab-on-printed circuit board (PCB) diagnostic platform for the quantification of glucose, as required for pumpless applications such as wearable diagnostic patches. The platform exploits copper oxide (CuO) nanoparticles for non-enzymatic, electrochemical glucose quantification, to achieve the high sensitivity and linear range of operation that is necessary for sweat or interstitial fluid sample analysis. As a result, the platform exhibits a low limit of detection (LoD) of 2.1 μM and a high sensitivity of 456 μA mM−1·cm−2, coupled with an excellent specificity against common glucose interfering species. The seamless integration of passive microfluidics and an electrochemical glucose biosensor is firstly outlined, and is fabricated using standard photolithography techniques in an up-scalable glucose quantification platform. The detection of glucose under two sample flow conditions is investigated in detail, including both static and dynamic conditions, revealing that when subject to a continuous flow the microsystem demonstrates an increase in sensitivity and a reduced linear range. This work demonstrates that our new passive Lab-on-printed circuit board (PCB) diagnostic platform can be successfully implemented under continuous sample flow conditions, and is therefore ideally suited to wearable diagnostic patch applications. In addition, the measured performance exceeds static flow approaches that have reported to date, including paper-based approaches. |
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| ISSN: | 2590-1370 |