Respirable Fibre Measurement from Light Scattering Patterns

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Current detection methods regarding aerosolised fibres can be readily achieved however the level of detail concerning morphology is currently lacking. This project aims to use a blend of computational modelling to emulate the light scattering patterns of airborne, respirable fibres, and empirical data from detectors in an attempt to develop a system of fibre detection and categorisation. Modelled predictions of the scattered light from potentially harmful fibres will be computed through the exploitation of the materials' physical and optical properties for a greater comprehension of the behaviour of light interacting with fibres. The modelled data will be compared with empirical results of categorised fibres with known morphological data collected from the available instrumentation at the University of Hertfordshire, such as the Phase Particle Discriminator (PPD) or the Aerosol Ice Interface Transmission Spectrometer (AIITS) with the morphological information of the material later confirmed via optical or electron microscopy. Comparisons of the predicted and empirical data will then be used to further improve any models for more accurate predictions. As pathogenicity is often related to aspect ratio when regarding fibrous material within the lungs, the initial focus will be to form a relationship between the scattered light and the dimensions of the fibre (most importantly aspect ratio), leading to considerations of more complex morphologies.