Prof. Giles Richardson is a Professor of Applied Mathematics
Giles has a number of PhD projects to offer in the area of renewable energy generation and storage (outline below). Driven by the pressure to develop technologies to reduce carbon emissions this is a fast growing and exciting area in which to work.
- Modelling the operation of perovskite solar cells.
Perovskite solar cells are a very recent photovoltaic technology that has shown an extraordinary growth in efficiency over the past 10 years, to the extent that they are now comparable with the best silicon cells. Nevertheless, their physics is still not fully understood and there remain issues of cell stability that need to be resolved before they are commercially viable.
- Modelling of Li-ion battery operation and manufacture.
Li-ion batteries are central to the future of the automotive industry. Since they comprise much of the cost (and weight) of an electrical vehicle, and limit its range and lifetime, there is a strong drive to improve their performance and reduce their cost. Accurate mathematical modelling will play a central role in this technological imperative.
- Modelling photo-electrochemical water splitting to produce hydrogen as a fuel. Large-scale zero-carbon energy storage is a key unsolved problem of the renewable energy transition. One potential method of accomplishing this is by using a modified solar cell to generate hydrogen by photo-electrochemical water splitting. However, there remain significant issues, related to the degradation of the photo-electrochemical cells and their low efficiency, that need to be resolved before this becomes a commercially viable technology. It is envisaged that mathematical modelling will play a key role in furthering the understanding of, and optimising, the complex physicochemical processes that underpin water splitting.
- Redox flow cells have the potential to revolutionise large-scale energy storage. Whilst they have a much lower energy density than Li-ion batteries, and so are not suitable for electric vehicles, they have many potential advantages including scalability, much greater ease of recycling, ability to store energy over long periods and cost. In collaboration with coleagues in Engineering, we are interested in developing accurate models of these devices and using a combination of asymptotic and numerical methods to solve them.
- Modelling renewable energy storage and generation
- Modelling in biomedicine
Giles' current research focusses on two broad areas of application: modelling renewable energy storage and generation, and modelling in biomedicine.
In the former, Giles has interests in modelling lithium-ion battery performance and manufacture, redox flow batteries, perovskite solar cells and photo-electrochemical water splitting. In the latter, his interests are divided into models of magnetically targeted drug/gene/virus delivery and the effects of the failure of cerebral drainage mechanisms on the development of Alzheimer’s disease.
He is a co-founder of DandeLiion (https://www.dandeliion.com), which provides fast and powerful software simulation tools for physics-based models of Li-ion battery performance. DandeLiion is licenced to About:Energy (https://www.aboutenergy.io) who tailor the software to particular battery systems.
Giles has taught on a number of modules, including:
MATH3018/6141 - Numerical Methods
MATH6149 - Modelling with Differential Equations
MATH2047 - Mathematics for Electronics & Electrical Engineering Part II
BSc. Mathematics (Bristol)
MSc. Mathematical Modelling and Numerical Analysis (Oxford)
D.Phil. in Applied Mathematics (Oxford)
Thesis title: Vortex Motion in Type-II Superconductors
- John Ockendon Prize 2018 (2018)
- John Ockendon Prize 2020 (2020)