The programme has been divided into work packages which highlight key areas of development. These are led by individual researchers, who drive the work forward. These packages will be expanded on as the project develops.


Assurance is the ability to provide credible proof that the expected level of performance will be achieved by a material. Going beyond quality, assurance relies on the value of a property that you can not only routinely expect but can actually demonstrate. This may be achieved through indirect means and judgement, ascribing numeric values based on understanding of materials processing and behaviour.


Digitised representations of physical systems or manufacturing processes, digital twins, can accelerate innovation, by improving efficiency, encourage collaborative work and enhance accessibility. The landscape of digitisation has recently been extended to replicate the climate, construction, social life and even the human physiology in virtual reality to improve the understanding of these systems and their interactions.
digital integration
An image showing the layers of metallurgical characterisation. They start with an image layer on top, followed by a chemistry layer, crystallographic layer, orientation layer, and finally a microstructure layer.


The bulk microstructure of components is an essential determinant of the mechanical properties and performance in its service application. Interrogating the microstructure and understanding the relationships with the mechanical properties are key to ensuring the long-term stability and safety of a structural component. With access to many different types of data and image analysis of microstructures, collating these methods for a more comprehensive prediction of the mechanical performance of regions of microstructure could be obtained.


Advanced characterisation integrated with material modelling are very powerful tools to understand the relationship between process, structure and property (PSP). Knowing this correlation enables us to understand and predict material behaviour. Thus, driving important processes such as alloy design, process design and the creation of digital twins.


Require overview