Application of Real-Time Single Particle Integrated AI-Optoelectronic Techniques for Detection and Discrimination of Airborne Biogenic Aerosols in Diverse Atmospheric Environments

Bioaerosols represent the most complex aerosols in the atmosphere. You will work with international collaborators and a major instrument manufacturer to test and characterise a new instrument incorporating physics based digital holography, fluorescence spectroscopy, fluorescence-lifetime and polarisation techniques, all melded into one to detect and classify airborne bioaerosols and non-bioaerosols in real-time. You will conduct laboratory and field experiments with the instrument at a range of locations across the globe (from the Arctic to Antarctica) supported by international co-supervisors providing you with unique supervision training and data support to generate data to expand the scientific community’s knowledge of airborne biomes.

PhD student: Eve Kerr
Cohort: 6
Lead supervisor: Prof. Martin Gallagher
Institution: University of Manchester

The Impacts of Phase Separation and Particle Shape on Aerosol Optical Properties Measured using Single Particle Cavity Ring-Down Spectroscopy

The interactions of light with aerosol particles of varying shape and internal structure are understood poorly, yet knowledge and predictions of these interactions are critical in areas such as preventing respiratory disease transmission and improving predictions of climate change. This project will utilise recently developed state-of-the-science spectroscopy instrumentation, involving the interrogation of single levitated aerosol particles via cavity ring-down spectroscopy. The resulting accurate characterisations of aerosol optical properties, as single particles undergo liquid-liquid phase separation in response to changing ambient conditions or crystallisation to form particles of complex shape, will be used to challenge electromagnetic models of aerosol-light interactions.

PhD student: Ruaridh Davidson
Cohort: 5
Lead supervisor: Dr Michael Cotterell, Prof. Jonathan Reid and Prof. Andrew J Orr-Ewing
Institution: University of Bristol

Photoinitiated Chemistry in Single Levitated Aerosol Droplets using Cavity Ring-Down Spectroscopy

Photochemistry in atmospheric aerosols represents one of the largest uncertainties in climate models, while understanding the enhanced rates of in-aerosol reactions could transform green approaches to chemical synthesis. This project will utilise recently developed state-of-the-art spectroscopy instrumentation to improve understanding of photoinitiated processes in aerosols.

PhD student: Xu Zhang
Cohort: 4
Lead supervisor: Dr Michael Cotterell
Institution: University of Bristol

Novel measurements of aerosol thermodynamic and optical properties using phase shift photoacoustic spectroscopy

This studentship develops a state-of-the-art spectroscopic approach to enable measurements of light absorption and volatility distributions for aerosols containing volatile species. The outcomes of this project will transform UK and international research capability in observations of aerosol properties that remain among the largest uncertainties in climate science.

PhD student: Gwen Lawson
Cohort: 3
Lead supervisor: Dr Michael Cotterell
Institution: University of Bristol

Classification of microparticles using two-dimensional scattering data and machine learning techniques

Two-dimensional light scattering patterns contain information regarding the size, shape, and orientation of micro-scale aerosol particulates. However, these have proven difficult to classify using traditional algorithms. You will develop a machine-learning classifier to classify such particles as cirrus ice, bioaerosol, pollution, and other respirable hazards thereby providing hitherto unavailable real-time data analysis.

PhD student: Skhathisomusa Mthembu
Cohort: 3
Lead supervisor: Dr Chris Stopford 
Institution: University of Hertfordshire

This project is an industry funded studentship supported by Alphasense.

Deep learning based classification of aerosol particles from holographic imagery

The impacts aerosol particles have are linked to their origin. Very few experiments are able to record the information to make that distinction in real time [e.g. volcanic ash detection]. However, digital holography combined with deep learning algorithms offer an exciting new potential to make that distinction.

PhD student: Hao Zhang
Cohort: 3
Lead supervisor: Dr David Topping
Institution: The University of Manchester

Respirable Fibre Measurement from Light Scattering Patterns

Fibrous particle inhalation can cause a range of respiratory diseases.  Current detection methods require filtration and manual counting under a microscope.  You will work with state-of-the-art optical instrumentation to develop a technique for the real-time detection and measurement of airborne fibres. 

PhD student: Robert Lewis
Cohort: 2
Lead supervisor: Dr Chris Stopford and Dr Richard Greenaway
Institution: University of Hertfordshire

Extinction Cross Section Measurements for Single Aerosol Particles Confined to a Linear Electrodynamic Quadrupole Trap

The contribution of organic aerosol to the warming of the Earth’s atmosphere remains uncertain because particle composition and morphology affect the absorption of sunlight. Using a recently developed spectroscopic apparatus, this project will measure precise optical properties of single, trapped aerosol particles.

PhD student: Jamie Knight
Cohort: 1
Supervisors: Prof Andrew Orr-Ewing (Bristol) and Dr Adam Squires (Bath)
Institution: University of Bristol