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Prof Tim Burnett

Supervisor

This PhD project is in collaboration with a company Xnovotech (https://xnovotech.com/) and will develop sophisticated data analysis workflows to effectively gain insights from large multidimensional data. It will use novel time lapse X-ray diffraction contrast tomography (DCT) which non-destructively captures the 3D shape, crystallography and grain structure over time. This will be applied to the phenomenon of Hydrogen Embrittlement (HE) of dual phase stainless steel and high strength aluminium both of which have important applications in sustainable futures using H as an energy source for net zero targets and developing new high performance materials which are resilient to extreme environments. XRD spectra are routinely utilised to observe phase evolution over time but this is spatially unresolved. EBSD can be applied in 3D statically or in 2D over time. DCT offers to overcome both of these barriers. Currently there is limited software available to track time evolution of crystallography (phases, grain orientation etc.), the workflows developed here will especially novel in that they will build on software that allows for analysis of static 3D crystallography and extend it to enable quantification and tracking of the changes taking place over time by creating data analysis workflows of 3D+crystallography+time (5D+!). The impact of this work will be to provide effective ways of processing complex data and new insights into important engineering materials.

Host Institution: University of Manchester

Prof Ping Xiao

Supervisor

This PhD project will accelerate the development of novel environmental barrier coatings required for ceramic matrix composite components for the next generation of higher temperature aero-engines in collaboration with Rolls-Royce through machine learning. Silicon carbide-based ceramic matrix composites (SiC-SiC CMCs) are being developed to transform aeroengine design by replacing nickel-based superalloys in the hot section of an aero-engine, due to their superior high-temperature mechanical properties and lower density e.g. density of CMCs is about one third density of superalloys. The use of the lighter weight CMCs would allow engine operating at higher temperature, using less cooling air, and therefore fuel. However, environmental barrier coatings (EBCs) are required to protect SiC-SiC CMCs from steam corrosion in engine environment. Without EBCs, the underlying substrates rapidly degrade in the hostile gas-turbine environment, so the failure of the EBCs is life limiting for the entire component. To introduce EBCs into aero-engine service, extensive research on manufacture, characterization and testing of EBCs has been carried out over decades. A range of materials have been investigated, but the current state-of-the art EBCs are based on ytterbium disilicate deposited via the air plasma spraying (APS) process.

Host Institution: University of Manchester

Prof John Liggat

Supervisor

Industry has expressed a clear need for better understanding of polymer quenching, particularly the physics and chemistry of polymer interactions with hot metal surfaces. From this will come predictive tools for modelling cooling rates in industrial scale parts, set-ups and conditions, to achieve desired microstructures and mechanical properties, whilst controlling residual stress. Experimental and modelling techniques will generate a wealth of data and provide robust predictive models.

Host Institution: University of Strathclyde

Dr Robert Menzel

Supervisor

The studentship will investigate advanced microfluidic techniques to create unique functional aerogel materials, in close collaboration with our industrial partner AWE. The project will follow-on from a previous PhD studentship that successfully developed a microfluidics-based platform for the synthesis of polymer foams with highly controlled internal structures. This studentship will translate the microfluidics synthesis technology to the fabrication of metal aerogels (gold, silver, copper), metal oxide aerogels (tantalum oxide, titanium oxide) and related core-shell materials. The aim of the project is to utilise the high level of control provided by the microfluidic synthesis to produce aerogel materials with unique, bespoke internal microstructures, currently not accessible by other fabrication approaches.

This opportunity is open to UK nationals only.

Host Institution: University of Leeds

Dr Andrew Leach

Supervisor

The goal is to discover new corrosion inhibitors that can be added to coatings for protection of metallic infrastructure. Initially, you will quantify two key performance indicators for candidate molecules, i.e., corrosion reduction and diffusion through the coating matrix. Subsequently, you will use these data, combined with interfacial analysis results, as input for computational methods, including artificial intelligence (AI), that will allow identification of new high-performance species.

Materials 4.0 Themes: Data-centric approaches coupled with modelling and simulation; Novel coupling of experiment and simulation; Development of materials-aware digital twins; Materials informatics, data-focused approaches and AI for materials discovery;

Royce Research Areas: Materials Systems for Demanding Environments; Imaging and Characterisation; Modelling and Simulation;

Host Institution: University of Manchester

Prof Chris Race

CDT Co-Director

In fusion reactors, materials experience extreme temperatures, stresses, and radiation damage. Safe operation requires identification of deformation patterns that are early warning signs of materials failure. These characteristic patterns result from the interaction of deformation mechanisms across multiple scales making detection via traditional analytical methods extremely challenging. This project will apply pattern recognition and machine learning techniques to a large database of experimental data to reveal early-stage fingerprints for damage hidden in the data.

Materials 4.0 Theme: Data-informed metrology for materials science; Materials informatics, data-focused approaches and AI for materials discovery; “Smart” characterisation methods, e.g.

Royce Research Areas: Advanced Metals Processing;

Host Institution: University of Sheffield

Prof Emilio Martínez-Pañeda

Supervisor

Hydrogen will play a major role in decarbonising energy-intensive industries worldwide and we need to develop materials-based solutions to enable safe and reliable hydrogen adoption. This PhD project will develop new, physically-based models to better understand and predict the behaviour of metallic alloys exposed to cyclic loading and hydrogen-containing environments. Commercial or open-source finite element codes will be used to conduct coupled deformation diffusion-fracture simulations that resolve the material physics of the rich problem which is hydrogen-assisted fatigue.

Materials 4.0 Themes: Data-centric approaches coupled with modelling and simulation

Royce Research Areas: Materials Systems for Demanding Environments

Host Institution: University of Oxford

Dr Anuradha R. Pallipurath

Supervisor

Controlling particle properties is key to achieving desired material properties. The stability, downstream processability and bioavailability of a drug is dependent on the particle morphology, and surface characteristics, while electronic and photonic properties of crystals are anisotropic and are dependent on both particle size and the dominant crystal facets. Process control can help achieve property control to some extent, however, it is heavily dependent on the chemical environment and the crystallisability of the material. Hence, being able to predict such properties from big data can minimize experimental needs and can prove to be a more sustainable means to materials discovery.

Materials 4.0 Themes: Data curation, and standards for digital storage of materials-related data; Materials informatics, data-focused approaches and AI for materials discovery; Data-centric approaches coupled with modelling and simulation;

Royce Research Areas: Chemical Materials Design; Imaging and Characterisation; Modelling and Simulation

Host Institution: University of Leeds

Dr Artur Gower

Supervisor

Ultra-thin membranes are produced in many high tech industries. They are the basis of flexible solar panels and electronics, as well as biosensors for medical diagnostics. To automate the production of these membranes we need a real-time virtual representation of them. The focus of this project is to create this virtual representation by transmitting small elastic waves along them, and then measuring these waves with lasers. The speed and amplitude of the waves are key to creating a virtual representation of the membranes.

Materials 4.0 Themes: High-throughput making, characterising and testing of materials; “Smart” characterisation methods, e.g. exploiting online processing and rapid feedback or multi-fidelity approaches; Data-informed metrology for materials science; Data-centric approaches coupled with modelling and simulation; Novel coupling of experiment and simulation; Digitalisation in materials manufacturing;

Royce Research Areas: Imaging and Characterisation; Modelling and Simulation; Chemical Materials Design; Electrochemical Systems;

Host Institution: University of Sheffield

Dr Theodosia Stratoudaki

Supervisor

This PhD study aims to develop the world’s first laser ultrasound array system for real-time, remote and couplant-free ultrasonic microstructural characterisation of metallic parts using Artificial Intelligence (AI). This system will enable the development, deployment and experimental validation of real-time, in-process, microstructural monitoring of manufacturing processes, a key step towards sustainable and reliable manufacturing of high-value, safety-critical components. In the long term, this material characterisation capability will form the basis of a feedback loop with manufacturing parameters, enhancing control over material properties of parts and enabling bespoke material microstructures.

Host Institution: University of Strathclyde