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  Optimising coatings formulations using artificial intelligence


   Department of Materials Engineering

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  Dr I Martin-Fabiani, Dr D Zhou  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

To improve the performance of a wide range of liquid-formulated products – such as paints, coatings, inks, and adhesives – it is key to tune the distribution of the different ingredients in their final dried configuration.

We have made significant advances in understanding the assembly process that takes place during drying, but the complexity of the formulations used (up to 20 ingredients) has limited our ability to optimise full formulations based on science rather than trial and error approaches.

Here is where artificial intelligence (AI) can make a difference. AI has vast potential to serve as a predictive tool to guide materials design, reducing the number of experiments needed to optimise a certain formulation while introducing evidence-based biases.

In this project, you will develop and implement artificial intelligence methods which will guide your own experiments to achieve the final coating properties desired. You will perform advanced coatings characterisation (e.g. atomic force and fluorescence microscopy, solvent-relaxation NMR) as well as develop Bayesian optimisation and image analysis methods. Therefore, the successful completion of this PhD project will provide you with excellent career prospects both in academia and industry.

This PhD position is integrated within a large UKRI-funded project on soft materials within a world-class research environment and will be held in the research group of Dr Ignacio Martin-Fabiani at the Department of Materials, Loughborough University. You will work as part of a broader team including Dr Diwei Zou’s group in the Department of Mathematics and be included in a dynamic and supportive environment. This project will offer you the possibility of collaborating with internationally leading academic and industrial project partners.

Please see the Martin-Fabiana Group website for further details about the group including our research interests, publications and group members.

Supervisors

Primary supervisor: Ignacio Martin-Fabiani

Secondary supervisor: Diwei Zhou

Entry requirements for United Kingdom

Applicants should have or expect to achieve, at least a 2:1 Honours degree (or equivalent) in a relevant subject. Experience with programming (e.g. Matlab/Python) is required.

English language requirements

Applicants must meet the minimum English language requirements. Further details are available on the International website.

Find out more about research degree funding

How to apply

All applications should be made online and must include a research proposal. Under the programme name, select 'Materials'. Please quote the advertised reference number AACME-23-018 in your application.

To avoid delays in processing your application, please ensure that you submit the minimum supporting documents.

Apply now


Materials Science (24)

Funding Notes

UK fee
£4,596 full-time degree per annum
International fee
£25,100 full-time degree per annum
Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Fees are reviewed annually and are likely to increase to take into account inflationary pressures.

Where will I study?