PhD defence by Giulia Zappalà

On Wednesday 25 September, Giulia Zappalà  will defend her PhD thesis "Detection of nerve agents, organophosphorus pesticides and explosives using SERS-integrated centrifugal microfluidics and SERS substrate modification".

Time: 13:00
Place: Building 341, auditorium 21 &
zoom: https://dtudk.zoom.us/meeting/register/u5Yqce-upzsjGNN7u8mRvH3eTefKI4i9kR1M
Please be aware that the PhD defense may be recorded - This will also be informed at the beginning of the PhD defense.

Main supervisor:Professor Anja Boisen
Co-supervisor: Postdoc Elodie Dumont
Co-supervisor: Academic Employee Roman Slipets

Assessment committee:
Professor Anders Kristensen, DTU Health Tech
Professor Naomi J. Halas, Rice University
Associate Professor Alois Bonifacio, University of Trieste

Chairperson:
Senior researcher Tomas Rindzevicius, DTU Health Tech

Abstract:
In the past century, many harmful chemicals have been developed, some of which can be used as weapons, like explosives and nuclear, chemical, biological, and radiological weapons. These weapons are a global threat, particularly due to chemical terrorism. Detecting these threats is essential for safety and for preparing against potential terrorist attacks, and new technologies need to be tested for better identification and measurement of these compounds.

This Ph.D. project aimed to use Surface-Enhanced Raman Spectroscopy (SERS) to detect nerve agents, organophosphate pesticides, and explosives, demonstrating its potential in real-world scenarios.SERS is an analysis method based on the interaction of a laser light source with a compound on a nanostructured metal surface, which greatly amplifies the light signals, allowing for the detection and identification of tiny amounts of the compound. The project also explored methods to automate the analysis using microfluidic devices and improve the reproducibility and stability of measurements by optimizing the SERS substrates.

We investigated SERS-based methods for detecting nerve agents in complex mixtures, achieving successful low-concentration detection with handheld Raman systems suitable for on-site testing. We developed a centrifugal microfluidic (CM) platform that integrates SERS substrates to automate analysis and improve measurement reproducibility. By combining SERS with CM platforms and using machine learning methods, we achieved robust quantification of nerve agents in single-component solutions and mixtures.

Various substrate modifications were tested to enhance SERS performance, including surface functionalization, ultra-thin HfO2 coatings on Ag substrates, and thermal annealing. These modifications
significantly improved the stability and sensitivity of SERS performances for detecting nitroaromatic explosives and OP pesticides. 

In conclusion, this project demonstrated the applicability of SERS for detecting chemical hazards at low concentrations in liquid phases in various environments, contributing to chemical protection.
Additionally, it developed automated analysis techniques using microfluidic devices, enhancing the reproducibility and stability of measurements by optimizing the sensors used in the analysis.