Simulating Next Generation Organic LEDs
Organic semiconductors have many properties which are not only ideal for existing applications of electronic devices such as organic light emitting diodes (OLEDs), but which could also lead to new technologies which cannot be realised using inorganic materials, such as flexible devices. However, there is a need to improve aspects such as device efficiency while using more environmentally friendly materials. To this end, OLED emitters based on a process called Thermally Activated Delayed Fluorescence (TADF) are gaining traction as a route to environmentally friendly, efficient OLEDs, and are therefore often referred to as next generation OLEDs.
Computational chemistry has an important role to play in understanding the underlying physical processes involved in TADF, and ultimately in helping to identify new and more efficient TADF emitters which could be used in devices. However, these materials are challenging to simulate using quantum mechanics (QM), as calculations of thousands of atoms are required to capture their disordered structure. This is beyond the capability of most existing QM models even when using supercomputers; there is therefore a need to develop software which can treat large systems without compromising on accuracy, while also integrating with high throughput workflows for identifying new materials.
This project will be based in the Ratcliff group in the School of Chemistry at the University of Bristol. You will develop and apply state of the art QM methods for modelling TADF-based OLEDs, using large scale density functional theory (DFT) simulations. You will exploit techniques for large systems, using supercomputers to run your simulations. There will also be opportunities for collaboration with experimentalists.
The successful candidate should hold or be predicted to achieve a First or Upper-second class degree in Chemistry, Physics, Chemical Physics or a related area. You should also have a strong interest in computational chemistry, and some experience with computer programming. Experience with computational chemistry or high performance computing is beneficial but not essential.
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