*This project is based at the University of Southampton*
Background
Joining dissimilar metals though welding can be traced back to the Bronze age. Five millennia of development has led to the creation of a plethora of joining techniques, which are deployed to successfully manufacture technologies that enable our modern lives. However, history has also deemed a range of systems to be unweldable, owing to differences in their physical properties (e.g. melting points). Intriguingly, it is precisely such differences that can make joining such systems attractive, so that they can serve multiple engineering functions in a component. Indeed, there are many advanced technologies (e.g., those being developed for fusion plants) where there is a significant desire to use unweldable systems, but no methods are available. Modern manufacturing technologies, such as powder-based additive manufacturing (AM), are a form of welding where materials are joined in layers. When dealing with unweldable systems, the addition of a third metal or alloy can produce elemental multi-diffusion; this creates a transitional alloy system akin to joining the otherwise unweldable alloys. In welding, the third element can be a coating added to one of the alloys, whereas in powder-based AM, this can be a transitional layer leading to a functionally graded component.
Aims and Objectives
This project will find the third-alloy multi- diffusion alloys to join systems conventionally considered unweldable. The new alloys will mainly be applied with powder-based AM technologies, but traditional welding will be considered too. Our main application will be in the nuclear sector, but the generality of our approach will permit application to several other industries where property gradients are required; these will include automotive, aerospace, and chemical industries. Our method is iterative and data-driven, with a strong emphasis on optimisation for attaining desired engineering properties. The project will combine physical modelling, experimental data, and machine learning to create a feedback loop that refines the material properties and manufacturing processes, aiming to meet engineering property requirements considered unattainable at present. The process will start by setting out a property objective, e.g., maximise the temperature gradient withstood by the alloy system. Then, choices of best alloys to serve this purpose will be made, with a focus on those considered unweldable. Data will be extracted from literature reports on unsuccessful attempts to join such alloys. More data will be obtained from modelling the alloy joint, including mixing it with a third alloy or element; the modelling will employ thermodynamics, to predict the formation of desired and undesired phases, as well as temperature distributions. Then, experimental trials to produce the new system will start, from which more data will be generated, together with the advanced characterisation of the resulting builds. The loop ends with the selection of the best candidates based on deep learning predictions, which are then validated through experiments. Our ambition, however, goes well beyond specific alloys and engineering properties. This project aims to discover the entire space of unweldable alloys enabled by a third element.
A mixture of physical modelling, characterisation, and deep learning will allow the discovery of systems for which applications cannot even be foreseen today.
The successful applicant will be based at the University of Southampton.
Funding notes
This project is part-funded by a Community Studentship provided by the Fusion Engineering CDT, and hence the student will be based at the University of Southampton, but should expect to engage fully with the 3-month full-time training programme in the Fusion Engineering CDT at the start of the course (October to December inclusive). CDT training will be delivered across the CDT partner universities at Sheffield, Manchester, Birmingham and Liverpool. The training course requires weekly travel to attend in-person training at these universities - with one-night of accommodation (typically a wednesday night) provided by the CDT. For further information about the CDT programme, please visit the CDT website at www.fusion-engineering-cdt.ac.uk or send an email to hello@fusion-engineering-cdt.ac.uk.
Candidate requirements: 1st or 2:1 academic qualification in Engineering or Physical Sciences or a related discipline,.
How to apply: please email the supervisor Prof Perdro Rivera to apply at P.Rivera@soton.ac.uk
fusion_cdt