Perovskite based solar cells have the advantages of highly efficient conversion of sunlight into electricity. However, at present there are challenges in making solar cells from these materials. This project aims to develop methods to optimise the continuous manufacture of these solar cells, via a “roll to roll” film coating process. One key aim will be to develop methods to reliably optimise and control the crystalline structure of the active Perovskite layer. This will be achieved by deploying a combination of sensors that can report on the quality of the coated layers, together with sophisticated optimisation and control algorithms, including machine learning methods. Sensors that will be developed will include those based optical microscopy, which can observe the crystal structure, providing images that can in turn be analysed to give “live” measures of the coatings’ performance as a solar cell. The PhD student will be responsible for developing these sensors and conducting trial experiments to demonstrate their ability to optimise solar cell performance. This will be assisted by close collaboration with experts in state of the art control and optimisation methods within the Dept. of Automatic Control and Systems Engineering. The PhD student will also conduct characterisation of the produced solar cells, using state of the art instrumentation, as well as testing the performance of the solar cells directly. In this way the project has the potential to deliver a new route to manufacture solar cells that can play a significant role in addressing the pressing societal challenge of the requirement for renewable energy.
Full training will be provided, including hands-on training on all instrumentation and methods, mentoring in relevant software skills by experienced researchers, and significant opportunities for training in transferable skills such as project management, communication, and presentation skills.
The prospects for employment in the renewable energy materials manufacturing area are significant, and the skills provided by this PhD, in state of the art manufacturing and characterisation methods, together with experience of machine learning process optimisation and control will make the PhD student very attractive to employers.
The studentship will be conducted in well-equipped labs, with instrumentation to make and test solar cell devices, a bespoke roll-to-toll coating platform dedicated to this project, and a wide range of relevant characterisation methods. The student will be part of a larger interdisciplinary team all focused on generating advances in renewable energy materials and will consequently be conducted in a stimulating and vibrant community of scientists and engineers.
Please see this link for information on how to apply: https://www.sheffield.ac.uk/cbe/postgraduate/phd/how-apply. Please include the name of your proposed supervisor and the title of the PhD project within your application.
Applicants should have a degree in a relevant Engineering or Physical Science discipline. If English is not your first language then you must have an International English Language Testing System (IELTS) average of 6.5 or above with at least 6.0 in each component, or equivalent. Please see this link for further information: https://www.sheffield.ac.uk/postgraduate/phd/apply/english-language.
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