|Funding for:||UK Students, EU Students|
|Funding amount:||£15,009 stipend in line with the RCUK rate|
|Placed On:||18th April 2019|
|Closes:||30th June 2019|
Applications are invited for a fully-funded three year PhD to commence in October 2019.
Successful applicants will receive a bursary to cover tuition fees for three years and a stipend in line with the RCUK rate (£15,009 for 2019/2020). The Faculty of Technology may fund project costs/consumables up to £1,500 p.a.
The work on this project will carry out the mathematical modelling and analysis required to underpin and inform changes in the current design of perovskite solar cells to increase their usable lifetime.
This is an opportunity to work in an extremely active area; and one that is forecast to experience significant growth over the coming decades. As such, this is an excellent opportunity to make a strong start in pursuing a career in research. It is expected that the candidate will graduate with publications in high-impact journals and will therefore be well-placed to continue their upward trajectory in science.
Developing efficient means of renewable energy capture is key to the low-carbon economy. The past few years have seen an explosion of interest in perovskite-based solar cells (PSCs). This young technology recently surpassed market-leading silicon technology by achieving an efficiency of 23%. They are also made from cheap and clean materials. The largest roadblock that remains to PSC commercialisation is their long-term durability. At present, PSCs can maintain usable performance for several months, but in order to compete at market this needs to be extended.
The aims of this project are to carry out the mathematical modelling and analysis required to inform changes in the cell design to mitigate processes associated cell degradation. Models must be coarse enough to capture the important phenomena occurring throughout the device, yet must retain sufficient detail so that the underlying physics can be interrogated. Drift-diffusion models provide this middle-ground and will be the central approach used in the project.
Models will be solved using a combination of asymptotic and numerical techniques. They will then be iteratively refined, by comparison with real-world data provided by experimental collaborators, until reliable predictive power is established. Ultimately, they will be used to identify optimal designs for cells that not only give rise to high initial efficiencies, but ones that are able to maintain this performance in the long-term.
You'll need a good first degree from an internationally recognised university (minimum second class or equivalent, depending on your chosen course) or a Master’s degree in an appropriate subject.
We’d welcome applications from candidates with some knowledge of the physics of semiconductors as well as some familiarity with asymptotic methods and scientific computing/numerical methods.
How to Apply
We’d encourage you to contact Dr Jamie Foster (firstname.lastname@example.org) to discuss your interest before you apply, quoting the project code.
Our ‘How to Apply’ page offers further guidance on the PhD application process. If you want to be considered for this funded PhD opportunity, you must quote project code MPHY4440219 when applying.
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