Surface-enhanced Raman scattering substrates for biomedical sensing

Author

Hartley, Jennifer Sarah

Available versions

Abstract

This project characterised four potential SERS substrates and then developed these substrates further for application based uses. The first substrate (gold nanoparticles) was deemed unsuitable for most applications due to the strong bands originating from the cross-linker. The second substrate was chosen for suitability with optical fibres. Optical fibres are ideal for remote sensing in biomedical applications as they are biocompatible, minimally invasive, readily available and affordable. Optical fibres can be used as miniaturised probes suitable for in vivo applications. However optical fibres, when coupled with a Raman spectrometer, are a complex optical element which needs to be investigated and fully comprehended in order to determine the ideal parameters needed to address biomedical applications. This project determines those parameters so that future work can be undertaken to customise the probe to sense a specific biological compound of interest. Standard telecom fibres were investigated as they are readily available and affordable. Multiple fibre types with different numerical apertures (NA), core sizes, mode structure and core/cladding materials were compared as probes. All fibres used in the comparison were manufactured as probes using OAD and thiophenol as a test analyte. Cladding modes were removed by bending each fibre and placing index matching gel on the bend. This was done in an effort to ensure that the mode structure was repeatable for each fibre. Otherwise the cladding modes can interfere with the mode structure in unexpected and random ways, making comparison difficult. This work determined SMF28 had the largest signal to noise ratio when the spectrometer was operated at a wavelength of 514.5 nm with a slit width of 62.5 μ

Publication year

2015

Thesis supervisor

Paul Stoddart

Publication type

Thesis (Masters)

Copyright

Copyright © 2015 Jennifer Sarah Hartley.

Thesis note

Thesis submitted in fulfilment of the requirements for the degree of Master of Science (Research), Swinburne University of Technology, 2015.

Details