Quantum Dot synthesis in Continuous Flow via Self-Optimising Nanoscale Manufacturing Platforms

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This project will build platform technologies, comprising advanced chemical reactors underpinned by computational intelligence, which can scale up production of advanced nanoparticle products (quantum dots) without loss in the precise control over structural dimensions which are achieved in research laboratories. It will build laboratory reactors which can be programmed to monitor the nanoparticle formation process in real time and relate formation conditions to the final product particle's properties. It will incorporate and optimise machine learning algorithms which will direct the reactors towards achieving the desired specification through 'self-optimisation' of conditions. The optimised laboratory nanoparticle formation processes will be transferred to several manufacturing environments, including R&D process laboratories and manufacturing facilities at industrial sites and scale up will be demonstrated. The position will be based at the School of Chemistry and the Institute of Process Research and Development at Leeds. It aligns directly with the EPSRC Digital Manufacturing theme and there will be interaction with partners of the EPSRC grant NanoMan, DeepMatter and CPI, to develop automated reactor platforms for quantum dot generation and work with collaborators at the University of Sheffield in the integration of machine learning algorithms.