The goal of achieving energy production by harnessing nuclear fusion is one of the most important scientific challenges of our time. Inside a fusion reactor structural materials are exposed to extreme doses of radiation, which over time alter their structural properties.
To design efficient thermal recovery procedures for structural materials in fusion energy applications it is important to characterise quantitatively the annealing timescales of radiation-induced defect clusters. The evolution of the defect microstructure in materials at high temperature is dominated by diffusion-mediated interactions between dislocations, cavities and surfaces. This gives rise to complex non-linear couplings between interstitial and vacancy-type dislocation loops, cavities and the field of diffusing vacancies that adiabatically follows the evolution of microstructure. In this work we present a novel approach inspired by the Green’s function formulation for the climb of curved dislocations, including in the same framework the evaporation and growth of cavities and the effects of free surfaces. The model makes use of boundary integral
equations to solve the steady-state vacancy diffusion problem, allowing a unified treatment of multiple microstructural features in a real-space picture.
After illustrating its main features, we then expand the formalism to include the treatment of a population of very small defects and dislocation loops that are below the experimental detection limit. These are taken into account through a mean field approach coupled with an
explicit real-space treatment of larger-scale discrete defect clusters. We find that randomly distributed small defects screen diffusive interactions between larger discrete clusters, modifying the free diffusion Green’s functions into Yukawa-type propagators. The evolution of the coupled system is modelled self-consistently, showing how the defect microstructure evolves through a non-monotonic variation of the distribution of sizes of dislocation loops and cavities, treated as discrete real-space objects.