PhD Studentship: Computational and ML Modelling of Low Temperature Plasmas PhD (CoFunded with Industry)

The University of Exeter and Oxford Instruments Plasma Technologies are offering a jointly funded PhD position in computational and machine learning modelling of low temperature plasmas. Oxford Instruments (OI) develops and markets a range of manufacturing and scientific equipment using low temperature plasmas for etching and deposition. Plasma is a complex state of matter which can be considered as a fluid or as individual particles; moreover, complex chemical reactions can occur between species in the plasma. Modelling a plasma is accordingly a very complex and challenging task. The objective of the project is to optimise the hardware for the control of plasma in an atomic layer deposition chamber using various computational modelling approaches. This will require a hybrid fluid/particle model, which will be developed using the OpenFOAM toolkit. A modelling workflow will be created, and then used as the basis for the optimisation, potentially using tools such as Bayesian Optimisation. In addition, novel machine learning approaches will be investigated as a faster alternative for modelling the injector.

The technological impact of this work will be quite significant. Plasma etching is an important stage in manufacturing of microprocessors and other electronic devices, and any advance in this manufacturing is likely to have significant benefits. Computational modelling such as is investigated here can be the key to more efficient manufacturing and enable OI to push the envelope of what is possible. The modelling being developed here also have significant applications in other areas of plasma research. The project will involve computational modelling using physics- and machine learning-based methods and would suit a top student with a background in Physics, Engineering, Mathematics or similar disciplines with an interest in computer modelling.

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