In-Situ Mass Spectrometry Analysis Under Ambient Conditions

Mass Spectrometry (MS) is an important analytical tool in the identification and quantification of a wide range of samples, primarily because of its speed, sensitivity, selectivity and versatility in analysing, gases, solids and liquids. MS is an interdisciplinary analytical tool, impacting many areas of science from physics, through chemistry, to biology. However MS is mainly limited to laboratory settings due to the high vacuum requirement needed for ion generation and processing. The main theme of this work is the development of ionisation methods that enable ion generation and processing under ambient conditions in the open air outside of the laboratory for in-situ applications. To that end, it is also important that ions are generated and processed with little or no extensive sample preparation steps required. In this work the development of two ambient ionisation methods: desorption atmospheric pressure chemical ionisation (DAPCI) and paper spray (PS) ionisation and their application for in-situ MS analysis is demonstrated. A DAPCI handheld ion source version based on DAPCI was developed to ignite a corona discharge in air and operates for up to 12 h continuously using only 12 V battery. Both DAPCI and PS ambient ionisation methods were implemented for in-situ MS analysis and were used to detect trace amounts (< ng) of different classes of chemical compounds (i.e hydrocarbons, explosives corrosion inhibitors and metaldehyde in waters samples); this was achieved rapidly (i.e. less than 1 minute) with little or no sample preparation in the open air. Both ambient ionisation methods (i.e., DAPCI and PS) were used with either a commercial instrument or with a custom miniature mass spectrometer to identify and characterize traces amounts of petroleum oil hydrocarbons and additives (e.g. quaternary ammonium corrosion inhibitors), and water pollutants (e.g. metaldehyde) with high sensitivity and selectivity. The handheld DAPCI and PS methods were also applied to the in-situ direct analysis of explosives. Good performance was achieved with the miniaturised instrument giving detection limits within an order of magnitude to those achieved using a benchtop commercial instrument. The results reported in this thesis should be of importance to those interested in ambient ionisation mass spectrometry, miniature mass spectrometry, in-situ MS analysis, oilfield chemical analysis, homeland and border security agencies and environmental monitoring

Artificial Odour-Vision Syneasthesia via Olfactory Sensory Argumentation

The phenomenology of synaesthesia provides numerous cognitive benefits, which could be used towards augmenting interactive experiences with more refined multisensorial capabilities leading to more engaging and enriched experiences, better designs, and more transparent human-machine interfaces. In this study, we report a novel framework for the transformation of odours into the visual domain by applying the ideology from synaesthesia, to a low cost, portable, augmented reality/virtual reality system. The benefits of generating an artificial form of synesthesia are outlined and implemented using a custom made electronic nose to gather information about odour sources which is then sent to a mobile computing engine for characterisation, classification, and visualisation. The odours are visualised in the form of coloured 2D abstract shapes in real-time. Our results show that our affordable system has the potential to increase human odour discrimination comparable to that of natural syneasthesia highlighting the prospects for augmenting human-machine interfaces with an artificial form of this phenomenon

FluNet: An AI-Enabled Influenza-like Warning System

Influenza is an acute viral respiratory disease that is currently causing severe financial and resource strains worldwide. With the COVID-19 pandemic exceeding 153 million cases worldwide, there is a need for a low-cost and contactless surveillance system to detect symptomatic individuals. The objective of this study was to develop FluNet, a novel, proof-of-concept, low-cost and contactless device for the detection of high-risk individuals. The system conducts face detection in the LWIR with a precision rating of 0.98, a recall of 0.91, an F-score of 0.96, and a mean intersection over union of 0.74 while sequentially taking the temperature trend of faces with a thermal accuracy of &#x00B1; 1 K. While in parallel determining if someone is coughing by using a custom lightweight deep convolutional neural network with a precision rating of 0.95, a recall of 0.92, an F score of 0.94 and an AUC of 0.98. We concluded this study by testing the accuracy of the direction of arrival estimation for the cough detection revealing an error of &#x00B1; 4.78&#x00B0;. If a subject is symptomatic, a photo is taken with a specified region of interest using a visible light camera. Two datasets have been constructed, one for face detection in the LWIR consisting of 250 images of 20 participants&#x2019; faces at various rotations and coverings, including face masks. The other for the real-time detection of coughs comprised of 40,482 cough / not cough sounds. These findings could be helpful for future low-cost edge computing applications for influenza-like monitoring

Analysis of non-conjugated steroids in water using paper spray mass spectrometry

A novel strategy for the direct analysis of non-conjugated steroids in water using paper spray mass spectrometry (PS-MS) has been developed. PS-MS was used in the identification and quantification of non-conjugated (free) steroids in fish tank water samples. Data shown herein indicates that individual amounts of free steroids can be detected in aqua as low as; 0.17 ng/µL, 0.039 ng/µL, 0.43 ng/µL, 0.0076 ng/µL for aldosterone, corticosterone, cortisol, and β-estrone, respectively, and with an average relative standard deviation of ca. < 10% in the positive ion mode using PS-MS/MS. Direct detection of free steroids in a raw water mixture, from aquaculture, without prior sample preparation is demonstrated. The presence of free steroids released in fish water samples was confirmed via tandem mass spectrometry using collision-induced dissociation. This approach shows promise for rapid and direct water quality monitoring to provide a holistic assessment of non-conjugated steroids in aqua