Automated Bayesian Optimisation of Mechanochemistry

Project ID: 2531ad1577

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Research Theme: Manufacturing The Future

UCL Lead department: School of Pharmacy

Department Website

Lead Supervisor: Duncan Browne

Project Summary:

In order to improve food security, human health and quality of life, society depends on access to new and improved drugs, food protection agents, flavours, fragrances and materials. The provision of these chemicals to society is extremely wasteful from the point of chemical manufacturing. There is approximately 50 tonnes of waste for every tonne of desired material, the majority of this waste is solvent – this practice is unsustainable and is having an irreparable impact on our planet. This project will explore a promising technique, called ball-milling, that has the potential to complement existing research and manufacturing methods, and reduce waste generation and our dependence on fossil-fuel-derived solvents. Specifically, the project will focus on developing automated, parallel, small-scale chemical reactions by the technique of ball-milling. A machine learning approach, called Bayesian optimisation, will be explored to streamline the reaction optimisation of this sustainable chemistry.