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Hayder Ashelaish

Developing a novel biosensor for medical detection and diagnosis.

Email: h.q.m.ashelaish@ncl.ac.uk

Project supervisors

Dr John Hedley

Project description

This research presents a novel biosensor based on a microwave transmission line network. The biosensor consists of a high radio frequency microstrip filter and microfluidic channel. I will design, analyse and fabricate biosensors able to perform non-invasive and label-free detection of biological species. They will have applications in care monitoring and rapid diagnosis.

I modelled and computationally verified the biosensor design by scattering matrix analysis. I used two different fabrication methods to manufacture the biosensors. I used a printed circuit board approach and a clean room evaporation approach. Materials used are TR-4 and quartz for the dielectric substrates and gold for the microstrips. I produced both macro and miniaturised versions of the microstrip filters.

The fabricated microstrip filters underwent a thorough characterisation process by vector network analyser (VNA). The results are in good agreement with modelling.

I integrated microstrip filters with microchamber and microfluidics to produce the biosensors. I quantified sensitivity to prostate specific antigens (PSA) to assess functionality.

I initially functionalised the biosensor by coating it with antibody receptors of PSA. Then I assessed the repeatability of detecting captured PSA by immobilising it on the treated golden surface. This also allowed me to assess sensitivity. I took real time measurements at each stage of coating and capturing. Characteristic dips in the reflection signal parameter (S11) all showed both an amplitude and frequency shift. This reveals the ability of the biosensor to immobilise and detect nano-concentrations of PSA analyte. We can attribute variability in results to the surface quality of the biosensor. Results show a minimum detection limit of 6.25ng/ml. They confirm the potential application of this type of new biosensor in medical detection and diagnosis applications.

Publications

Interests

Mechatronics, sensors

Qualifications

PhD in Mechanical Engineering, Master of Science, LabView