Radioactive Aerosols in Wall-bounded Turbulent Flow

Nuclear energy production is set to expand as one of the means for reliable energy output, as we curb CO2 emissions. This project employs advanced mathematical and computational models to develop an understanding of the complex interaction of radioactive aerosols, as these are transported and deposit in ventilation systems.

PhD student: Gregory Marsden
Cohort: 4
Lead supervisor: Alberto Gambaruto
Institution: University of Bristol

This project is an industry funded studentship supported by National Nuclear Laboratory.

Digital Microfluidic Lab-on-a-chip for multiplex detection of biomarkers in exhaled breath

Exhaled aerosols contain precious information on lung health, which could inform diagnosis and therapies and help saving lives. This project will combine emerging microfluidic and lab-on-a-chip technologies to create a portable and fully automated Lab-on-a-chip for detection of multiple disease biomarkers in exhaled aerosols.

PhD student: Daisy Ashton
Cohort: 4
Lead supervisors: Dr Loic Coudron, Dr Laura Urbano and Dr Ian Johnston
Institution: University of Hertfordshire

Airborne microplastic detection and quantification – developing, evaluating, and applying novel laboratory and field-based approaches

Microplastic particles are emitted from a range of sources but remain a poorly understood fraction of airborne particulate matter, with potential health impacts. This project will use cutting-edge laboratory and online analytical techniques to identify chemical and optical markers in different environments and better understand microplastic emissions.

PhD student: Henry Blake
Cohort: 4
Lead supervisor: Dr Stephanie Wright
Institution: Imperial College London

This project is an industry funded studentship supported by LECO Corporation.

Developing and deploying new sensors for in-situ monitoring of clouds

Clouds form a crucial component of the Earth system, reflecting large amounts of incoming sunlight back into space. Low-cost sensors are needed to allow long-term monitoring of climatically relevant cloud properties, but to-date no such sensor exists. This project will develop and test new sensors for cloud monitoring.

PhD student: Charlie Stainton-Bygrave
Cohort: 4
Lead supervisor: Dr Jonathan Crosier
Institution: The University of Manchester

Airborne particle collection into single droplets to analyse and identify harmful aerosol constituents

Aerosols are a primary mechanism for spreading harmful particles and diseases. It is crucial to improve the speed and accuracy of detection by concentrating the material during collection. This project aims to achieve this by investigating techniques for collecting aerosols directly into droplets using prototyping, experimental and modelling approaches.

PhD student: Priya Chopra
Cohort: 3
Lead supervisors: Dr Ian Johnston and Dr Loic Coudron
Institution: University of Hertfordshire

Improving Evaporative Light Scattering detector performance using experiments and modelling

Evaporative Light Scattering detectors are used with high performance liquid chromatography by collecting light scattered by droplets formed from separate analytes. The project will combine experiments with modelling and simulations for the nebulisation and evaporation process to allow the sensitivity of the detector to be improved.

PhD student: Frederick Bertani
Cohort: 2
Lead supervisor: Prof Simone Hochgreb
Institution: University of Cambridge

This project is an industry funded studentship supported by Agilent Technologies.

Low-cost sensing of ultrafine aerosols: Sensor development and integration for first and second moment measurements

Sub-micron particulates are important pollutants, but difficult to measure with inexpensive methods. This project will use and further develop two low-cost sensors developed by the group to measure total particle area (nd²) or total particle length (nd) and thus diameter (d) in the atmosphere.

PhD student: Joshua Hassim
Cohort: 2
Lead supervisor: Prof Simone Hochgreb
Institution: University of Cambridge

This project is an industry funded studentship supported by Cambustion.

Modelling the impact of soot fractal aggregate structures on the aerodynamic and mobility diameters of particles in the transition regime

The ageing process, i.e. soot maturing in the atmosphere, usually involves partial or total coating by water or organic compounds. This added material drastically changes the radiative transfer to/from the in-flight particles and their overall morphology and dynamics.

PhD student: Cyprien Jourdain
Cohort: 2
Lead supervisor: Dr Adam Boies
Institution: University of Cambridge

Smart filtration of aerosols in ventilation systems

Aerosols in ventilation systems of energy efficient buildings affect indoor air quality. The experimental and computational project examines the influence of flow speed, level of turbulence and aerosol size on aerosol tendency to concentrate and deposit in typical ventilation ducts. Findings will guide active and passive control for efficient filtering.

PhD student: George Downing
Cohort: 2
Lead supervisor: Prof Yannis Hardalupas
Institution: Imperial College London

Dynamic Surface Properties of Atmospheric Aerosol and Resulting Climate Impacts

The surface tension of atmospheric aerosols impacts their ability to serve as cloud droplet seeds and affect climate. This project will develop approaches to measure droplet surface tensions and better resolve dynamics at the particle surface, working closely with modellers.

PhD student: Josh Harrison
Cohort: 1
Supervisors: Dr Bryan Bzdek (Bristol) and Dr Matthew Watson (Bristol)
Institution: University of Bristol

Investigating the charge states of ambient and indoor aerosols

Conveying and generation of powders can lead to very high levels of charge on particles, affecting their transport agglomeration and ultimate removal from the environment. Through modelling and experiments this project seeks to optimize collection of particles in filtration processes accounting for and manipulating electrostatic charge.

PhD student: Peter Knapp
Cohort: 1
Supervisors: Dr Marc Stettler (Imperial), Dr Adam Boies (Cambridge) and Prof. Jonathan Reid (Bristol)
Institution: Imperial College London

This project is an industry funded studentship supported by Dyson.

Building flexible biological particle detection algorithms for traditional and emerging real-time instrumentation 

Whilst the importance of biological particles in the environment, human health and as a potential security threat is known, development of robust detection technologies remains a challenge. This project will apply and evaluate a range of machine learning techniques to to convert multidimensional signatures from new and emerging detection techniques into distinct PBA types.

PhD student: Maxamilian Moss
Cohort: 1
Supervisors: Dr David Topping (Manchester)  and Dr Chris Stopford (Hertfordshire)
Institution: The University of Manchester

This project is an industry funded studentship supported by Droplet Measurement Technologies.