Developing Biosensors using Photonic Crystal Fibres and Surface Plasmon Resonance (SPR)

Dr Sanjeev Mani Yadav, Assistant Professor from the Department of Electronics and Communication Engineering, has published a cutting-edge research paper titled “Au-Al2O3 Coated Highly Sensitive Broad Range Refractive Index Sensor for Detecting Malaria Disease in Human Blood” in the IEEE Sensors Journal with an impact factor of 4.3. This research focuses on developing a highly sensitive biosensor using photonic crystal fibres and a technique called surface plasmon resonance (SPR) to detect changes in the refractive index, which is how much light bends when it enters a material. This biosensor can also detect malaria in the human body.

Abstract

The paper represents the photonic crystal fibre-based surface plasmon resonance (SPR) biosensor for broad-range refractive index sensors along with the detection of malaria disease in the human body. α-Al2O3-Au dielectric-metal interface has been proposed to stimulate the free electron on the metal surface via evanescent to result in an SPR phenomenon. The proposed sensor shows a sufficient shift in resonance wavelength for the change in external RI from 1.32 to 1.40 for an optimised Al2O3/Au thickness of 50nm/12nm. The broad-range sensing applicability of the designed sensor shows a maximum sensitivity of 6000 nm/RIU when the external RI changes from 1.38 to 1.40. The detection accuracy of the designed sensor is reported to be 1.66×10-5 (RIU) and reported compatible in comparison to broad RI sensors. The proposed SPR sensor has been utilised to sense the malaria diseases in the human body by filling infected RBC samples on the dielectric-metal surface. The proposed study aids in detecting various stages of malaria-infected RBCs, including the Ring phase, Trophozoite phase, and Schizont phase, by measuring the shift in resonance wavelength. The sensor’s wavelength sensitivity varies across the phases: 5714.28 nm/RIU for the Ring phase, 5263.15 nm/RIU for the Trophozoite phase, and 5931 nm/RIU for the Schizont phase. The sensor exhibits the highest reported sensitivity among other biological sensors in this category. The proposed sensor fulfils all the requirements for a diagnosis of early malaria disease in the human body, along with its high sensitivity, low detection limit, and capability of sensing broad RI.

How does the sensor work?

1. Biosensor Basics: The sensor uses a combination of a special crystal fibre and a metal surface (a mix of aluminium oxide and gold) to create a reaction when light hits it. This reaction is called SPR and it helps in detecting tiny changes.

2. Detecting Changes: When the external refractive index (a measure of how light bends in a substance) changes, the sensor detects this by a shift in the wavelength (colour) of the light. The study found that the sensor is very sensitive to changes in the refractive index between 1.32 and 1.40.

3. Sensitivity: The sensor is incredibly sensitive, with a maximum sensitivity of 6000 nm/RIU (nanometres per refractive index unit). This means it can detect very small changes very accurately.

4. Malaria Detection: The sensor can also detect malaria by analysing infected red blood cells. Different stages of malaria infection (Ring, Trophozoite, and Schizont) cause different shifts in the wavelength, which the sensor can measure. The sensor’s sensitivity varies slightly with each stage but is consistently high.

5. High Performance: This sensor is reported to have the highest sensitivity compared to other similar sensors and meets all the requirements for early malaria diagnosis due to its high sensitivity, low detection limit, and ability to detect a wide range of refractive indices.

In essence, this sensor is a powerful tool for detecting both refractive index changes and malaria in the human body with high accuracy and sensitivity.

Practical implementation/Social implications of the research

The photonic crystal fibre-based SPR biosensor represents a significant advancement in medical diagnostics with wide-ranging practical applications and social implications. Its high sensitivity and accuracy in detecting malaria and potentially other diseases can lead to better health outcomes, economic benefits, and improved access to healthcare, particularly in regions that need it the most.

Dr Sanjeev Mani Yadav acknowledges Dr Amritanshu Pandey, Electronics Engineering Department, IIT (BHU) Varanasi, for his continuous support and guidance throughout this research.

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