A New Paradigm for Selective Bromination in Flow

Lead Research Organisation: Imperial College London
Department Name: Dept of Chemistry


Bromination is a common starting point in the synthesis of complex organic molecules to be used as actives in agrochemicals or pharmaceuticals. However, it entails two key challenges: (i) handling elemental bromine is difficult, as it is toxic, corrosive and hazardous and is difficult to handle and store; (ii) controlling selectivity of the reaction is difficult and yet crucial for producing the desired product.

The approach to overcome these challenges is to use flow chemistry to generate bromination reagents 'on-demand' and utilise them directly in a reaction with the substrate to yield the desired product with good selectivity, e.g. controlling chemoselective and regioselective bromination of an aromatic ring. The benefits of flow chemistry are threefold: (i) unstableintermediates can be generated in-situ and deployed immediately in the reaction; thus minimizing hazardous inventory, (ii) larger amounts (in the process is easy to scale up, and (iii) the kinetic product can be favoured by controlling residence time and better heat management.

In the project the following aspects will be developed:
- In-situ generation of the brominating species from non-hazardous precursor. This can be achieved by chemical means, electrochemical, or photochemical activation.
- Design and setup of a suitable flow chemistry methodology taking into consideration aspects relating to the reaction kinetics, mass and heat transfer, the selected reactor type and other unit operations, their sequence, safety, corrosion, and process control.
- Operation of the setup to produce research amounts of material and its characterization regarding selectivity and yield.
- Scale up of the reactor/operation over longer periods to deliver several kg of desired component.
- Digital aspects of the project involve modelling and design of the reactor, and optimization of compositional and processing parameters, through machine learning or design-of-experiment approaches, for example.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S023232/1 31/03/2019 29/09/2027
2606062 Studentship EP/S023232/1 30/09/2021 29/09/2025 Jeremy Jubb