The application of digital technologies is transforming the discovery and manufacturing process within materials science. This therefore represents perhaps the only opportunity to address the urgent need for new sustainable, high performing materials to facilitate more efficient processes in a circular economy (e.g. better, longer lasting and recyclable lubricants for electric cars). However, these discovery tools are only just emerging within the polymer science, which remains reliant on traditional laboratory techniques R&D. This is a big problem given polymers are ubiquitous in everyday life, ranging from plastics to polymer additives in nearly all liquid formulations.

This project will exploit the latest developments in polymer chemistry, reactor technologies and artificial intelligence to generate libraries of new polymers. Systems will be developed which include sophisticated machine learning guided reactor platforms which integrate experiment, analysis and computational control in a closed loop. These will then be used to implement closed-loop self-optimisation of reaction conditions and product properties. In the context of product development, these processes will offer a means of significantly streamlining the development of new generations of high-performance and sustainable polymer materials. However, there exist numerous technical challenges which have thus far prevented wide utility in the polymer industry.