Surface Plasmon Resonance [SPR]-Based Biosensor for Sugar Monitoring via Urine Samples
| dc.contributor.author | Archana Yadav, Anil Kumar | |
| dc.date.accessioned | 2025-10-10T09:01:32Z | |
| dc.date.issued | 2025 | |
| dc.description | Photonic Sensors for Biomedical Applications Edited ByPreeta Sharan, Ranjith B. Gowda, Aryan Chaudhary | |
| dc.description.abstract | The surface plasmon resonance (SPR) phenomenon has become an acclaimed technique for the real-time and label-free investigation of diverse biological interactions. This chapter encompasses the design and operational principles of SPR device, along with the pivotal role of material selection in achieving enhanced sensitivity and specificity for sugar detection. The SPR device’s core working principle involves the interaction of light with surface plasmons, resulting in a drip in the intensity of reflected light recorded at a particular angle. This angle is extremely sensitive to changes in refractive index (RI) close to sensor’s surface, allowing for detection of molecular binding events. In the context of sugar monitoring, the binding interactions between sugar molecules and specific receptors immobilized on the sensor surface induce RI changes that can be quantified in real time. Material selection plays a critical role in optimizing the device’s performance for sugar detection. The choice of materials for the sensor surface and immobilized receptors determines the device’s sensitivity, selectivity, and stability. Various materials, such as gold and silver, are commonly employed due to their strong plasmonic properties. Additionally, advanced surface functionalization techniques ensure the stable attachment of receptors, enabling specific sugar recognition. | |
| dc.identifier.isbn | 9781003638025 | |
| dc.identifier.uri | http://136.232.12.194:4000/handle/123456789/1449 | |
| dc.language.iso | en_US | |
| dc.publisher | Apple Academic Press | |
| dc.subject | Engineering & Technology | |
| dc.title | Surface Plasmon Resonance [SPR]-Based Biosensor for Sugar Monitoring via Urine Samples | |
| dc.type | Book chapter |
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