Understanding phase decomposition in SMART-W alloys in a fusion power plant environment

Tungsten alloys have been selected as potential first wall materials for STEP and other near-term fusion reactors. The first wall experiences one of the most severe environments in a fusion reactor, including high temperatures and high neutron fluxes. Tungsten is a good candidate due to its high melting point, low sputtering by plasma particles, relatively short-term activation, low tritium retention, and high thermal conductivity. However, pure tungsten behaves poorly in loss-of-coolant accident environments, where contact with the surrounding atmosphere causes volatile oxides to form.

To tackle this, self-passivating tungsten-based alloys (SMART-W alloys) have been suggested that incorporate additions of Cr, Zr, and Y that, under accident conditions, will preferentially form protective scales of their own oxides on the surface, inhibiting the tungsten oxide formation. However, the tungsten alloys that have been designed and prototyped for fusion applications as yet have unknown performance in real engineering applications.

The goal of this project is to begin to understand the real engineering performance of such alloys under application conditions. This project will use computational methods based on both first-principles and machine-learning based interatomic potentials, to systematically explore the phase stability of SMART-W alloys within the W-Cr-Y-Zr system under various thermal, oxidation and irradiation conditions.

This project is a theoretical development that runs alongside an experimental project supervised by Dr. Tamsin Whitfield at the University of Oxford. Experimental work will be used to validate theoretical modelling, while modelling can be used to guide experimental investigation to accelerate understanding of these materials. Through this work, the mechanism driving the thermal decomposition of these alloys will be exposed, giving insights about expected phases and microstructure evolution across the composition range.

This will drive our understanding of the real engineering performance of this class of tungsten alloys, highlighting areas that are needed to further development to enable practical use of such alloys. The goal of this project will be to use the knowledge gained towards the design of optimised compositions and/or thermal processing routes.

The selected candidate will have an opportunity to join a Bangor-Oxford-UKAEA collaboration that combines simulation and experimental studies to work towards designing future fusion reactors. The selected candidate will be part of a UKAEA PhD network, gaining insights into the fusion industry and visiting UKAEA facilities. Opportunities to work at the Culham Campus near Oxford are available.

The PhD candidate will develop advanced computational materials and fusion engineering knowledge, along with transferrable skills. Applicants should have an interest in high-performance computing, effective communication skills, and a relevant degree in materials, physics, computer science, chemistry, engineering, or a related field.

This PhD studentship is part of the Fusion Engineering Centre for Doctoral Training.