Accelerating mechanistic understanding in chemical synthesis: Design of Experiment, kinetic analysis and systems modelling

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The project fits squarely into EPSRC remit, aligning with the research areas: Catalysis, Syntheticorganic chemistry, Chemical reaction dynamics and mechanisms and Manufacturing technologiesand Robotics. The latter area is set as "Grow". Our project will employ a highly instrumented roboticplatform, complemented by rich reaction data analysis. Once several reaction datasets have beengenerated we will examine machine learning algorithms to predict reaction outcomes in new systems(e.g. substrates, conditions, catalyst changes). The project has the potential to fall into ArtificialIntelligence Technologies, which EPSRC has indicated as an area of importance. The Fairlambgroup's current grant, using automation and gathering rich mechanistic data, is supported by EPSRC(EP/S009965/1)