Light metals are the backbone of the modern and future zero-emission manufacturing and circular economy. However, one of the adverse consequences of excessive use of metallic materials is that there are currently thousands of grades of metallic materials in commercial use. Many of them differ only slightly in composition, processing conditions or origin of production, offering essentially the same performance. Unnecessary alloying elements and excessively tight alloy specifications increase production costs, reduce resource productivities, cause more environmental damage, and make the end-of-life products difficult (if not impossible) to recycle. This is not compatible with Circular Economy principles. Recycling can be improved significantly with materials rationalised and products engineered from the start for this purpose. For instance, the current over 400 grades of Al-alloys (IAA) can be reduced to 10-15 without compromising engineering applications. This project aims to apply most advanced methods of accelerated discovery (machine learning, artificial intelligence, optimisation) to the rationalisation of aluminium alloys to facilitate full metal circulation. The project contributes to slowing the resource loop by design for standardisation and compatibility. The specific research activities may include: (1) development of the techniques and algorithms for discovery of new optimised alloy compositions for simplification of alloy systems; (2) application of the developed approaches to standardisation of alloy compositions by using commonly available alloying elements and avoiding the recyclability-limiting elements; (3) validation of the developed approaches through specially designed experiments based on alloy compositions, thermomechanical history, levels of performance and fields of application. The funded studentship is £88,918 for up to 4 years duration. Studentship starts from the 1st of October 2021. The project will be aligned with the newly established Circular Metals Hub hosted by Brunel Centre for Advanced Solidification Technology (BCAST) at Brunel University London. You will be interacting daily with researchers and academics in BCAST, Brunel University London and in partner academic and industrials organisations. In this close collaboration lies the foundation for your promising career path.
Enquiries should be directed to Professor Dmitry Eskin at [Email Address Removed].
For non-UK nationals a proof of English proficiency (IELTS 6.5 and more) or the eligible proof of undergraduate education received in English is required. You should have or expect to receive by the beginning of this PhD study a first degree (BSc) at 2:1 or above in a suitable engineering and science discipline, e.g. materials science, mechanical engineering, physics or applied mathematics. A MSc level qualification is desirable. A strong background in materials science and applied mathematics is desirable as the project includes mathematical modelling and optimisation.
Please email the following to [Email Address Removed] by the 30th of June 2021:
• Your up-to-date CV.
• Your single A4 statement on why would you like to do this project and why do you believe you qualify to do so.
• Copies of your degree(s) certificates(s) and transcripts. • Evidence of your English proficiency (if applicable).
• Names and contact info of three academic referees