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Active STUDENTSHIP UKRI Gateway to Research

Accelerated Discovery of Next Generation Polymers Using Artificially Intelligent Reactor Platforms


Funder Engineering and Physical Sciences Research Council
Recipient Organization University of Sheffield
Country United Kingdom
Start Date Sep 30, 2024
End Date Sep 29, 2028
Duration 1,460 days
Number of Grantees 2
Roles Student; Supervisor
Data Source UKRI Gateway to Research
Grant ID 2928690
Grant Description

Research has already developed state-of-the art polymer synthesis platforms which can generate libraries of new polymers. These systems include sophisticated machine learning guided reactor platforms which integrate experiment, analysis and computational control in a closed loop which can implement algorithms which self-optimise the reaction conditions.

In the context of product development, these processes 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.

The aim of this PhD is to further optimise a state-of-the-art automated flow reactor platform for artificially intelligent high throughput optimisation of polymer synthesis. Sustainability will be embedded into the proposal through both targeting polymers with sustainable or degradable credentials, and for minimising environmental impact of the synthetic process.

Rather than manufacturing, these reactors intend to accelerate R&D, with opportunities for rapid prototyping of potential products.

The reactor platform will be programmed to conduct screens or machine learning directed experimental campaigns which include online characterisation of the product (molecular weight, particle size, reaction conversion). This will generate sufficient data to build models relating synthetic conditions to polymer composition. By collaborating with industry, experts in materials science and characterisation, we anticipate subsequent generation of performance-conditions models which can be used for high-throughput discovery.

The student will gain a unique multidisciplinary skill-set encompassing polymer synthesis, flow chemistry, machine learning and computational control. These will be highly valuable and relevant skills for a career in the chemical industry, particularly with the emergence of AI.

All Grantees

University of Sheffield

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