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PhD Studentship: Something in the Air: Predicting the Behaviour of Nanoparticle Aerosols

University of Warwick - Centre for Doctoral Training in the Modelling of Heterogeneous Materials (HetSys), Department of Engineering

Qualification Type: PhD
Location: Coventry
Funding for: UK Students, EU Students, International Students
Funding amount: Fully funded
Hours: Full Time
Placed On: 7th February 2024
Closes: 29th February 2024
Reference: HP2024-03

Supervisors:

Supervisors:  Prof. Duncan Lockerby (Engineering), Prof. Julian Gardner (Engineering), Dr. Radu Cimpeanu (Maths)

Summary:

 The World Health Organisation recently classified air pollution as “the single biggest environmental threat to human health”. The airborne particulate matter thought to be most harmful is at the nanoscale – particles so small that they can evade our respiratory defence systems. Evidence indicates that the shape of nanoparticles has a big influence on health outcomes, but currently there are no ways to detect this property in isolation. This project will combine continuum fluid-mechanics models with probabilistic particle simulators to train a predictive tool capable of inferring shape, and other properties, from measurable quantities and limited experimental data.

 

This project will, for the first time, incorporate nanoscale flow physics within a Brownian simulator of particle motion in channels. In this largely unexplored space we can expect that a complex interplay of multiscale physics will determine nanoparticle dynamics and deposition: gas-kinetic effects (e.g. velocity slip and kinetic boundary layers); translational and rotational diffusion (6-axis Brownian motion); and Brownian drift (an average migration towards particle positions and orientations having greater mobility).

The project will integrate a diverse range of simulation approaches and tools: stochastic simulation of Brownian motion (stochastic ODEs); continuum solutions to advection-diffusion equations; and boundary-element-type methods for solving linear PDEs. These models will feed into Machine Learning libraries to perform the inference task of assessing aerosol properties, with expressible certainty, from practically measurable quantities.

https://warwick.ac.uk/fac/sci/hetsys/themes/projectopportunities/

Additional Funding Information

Awards for both UK residents and international applicants pay a stipend to cover maintenance as well as paying the university fees and a research training support. The stipend is at the standard UKRI rate.

For more details visit: https://warwick.ac.uk/fac/sci/hetsys/apply/funding/

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