A Fully Automated Synthesis Machine for Optimising the Sustainable Manufacture of Selective Organic Reactions

This project will leverage a fully automated synthesis platform, based on a novel flow chemistry concept developed by Dr. Chatterjee, for the multi-step synthesis of complex organic molecules with a focus on selective organic reactions. The aim is to use this bespoke automation technology as a rapid optimization tool to 'green up' synthetic routes, adhering to the 12 principles of green chemistry, such as avoiding toxic reagents/solvents and minimizing waste by-products. The platform will integrate technologies like photochemistry and online/in-line reaction monitoring (e.g., UV-Vis, NMR, HPLC), enabling the use of cutting-edge photoredox catalysis methods and algorithm-driven self-optimization of key steps.
Dr. Chatterjee's recently published concept of a "radial synthesizer" will play a central role in this project. This system arranges individually accessible reaction modules around a central hub (switching station), allowing the sequencing of modules in the flow path to be reconfigured as needed. Reactors can be reused multiple times within a single route, and intermediates can be 'parked' on standby for later reintroduction. Modules can also temporarily operate in batch mode (stopped flow), decoupled from the main flow stream. This approach reduces manual intervention and eliminates the need to customize the synthesizer for specific synthetic routes.
Machine learning will be applied to accelerate reaction development, optimization, and discovery by rapidly interpreting data patterns. This project will focus on developing selective organic reactions (e.g., glycations) that will be optimized for a flow chemistry setup, automated to generate data sets, and used to train machine learning algorithms capable of self-optimizing analogues. The radial synthesizer will streamline reaction steps and enhance throughput, promoting waste reduction in industry and increasing accessibility to selective reactions.
Data collection will be conducted at the University of Bath using a combination of spectroscopy techniques (NMR, UV-Vis, infrared, HPLC), through off-line (external analytical instruments), in-line (connected directly to the flow apparatus), and on-line (connected to the apparatus with sample collection on a separate path) methods.