Advanced materials form the cornerstone of many emerging technologies, from next-generation energy production, transport and defence, to prosthetics and targeted drug delivery. Some of these eg. fusion energy require materials that do not yet exist, because the operating environment is so ferocious: high temperatures, corrosive environments and intense radiation mean no currently available material can be used. Theoretical modelling and predictive computer simulations are crucial steps in the development of new materials, since they can provide deeper understanding of the complex processes at work, and reduce lead times in product development. All modelling and simulation techniques are based on approximations, which limit their range of applicability. Whilst they have served well in the past, the extreme conditions mentioned above mean that some of these simplifying approximations no longer apply, and new techniques are required. The aims of this project are to develop new modelling approaches and simulation methods that are capable of handling the conditions, and apply them to unsolved problems in nuclear materials science.
The most precise simulation methods currently available track every atom in the system. Although they can be very accurate, the computer power required to run them means they can only model a few cubic nanometres of material for a few nanoseconds. This cannot capture the large-scale, long-time processes that control material performance, and eventually decide, for example, how many years a nuclear reactor can be safely run before it needs to be replaced. At the other end of the scale, computer-aided design programs simulate reactor-sized components, but base this on simple rules on how materials behave. Ideally, these would be derived from microscopic simulations, but there is a huge gap in length and time-scales between them. The mesoscale simulations that this project will develop aim to bridge that gap.
Over the last 60 years, particle physicists have developed powerful mathematical tools to understand quantum fluctuations. These tools can be modified to treat thermal fluctuations instead, and this will form the foundations of the new simulation methods. Instead of following every atom in the system, the new techniques will identify only the degrees of freedom that play important roles in the evolution of the material over time. These are the defects: impurity atoms, vacancies and self-interstitials (formed when atoms are knocked out of place in the regular lattice of eg. a metal) and dislocations (defect lines whose motion controls deformation).
Though the new methods will be widely applicable, this project will focus on 3 case studies. This will answer technologically important questions, as well as testing the new techniques. The first case study concerns the clustering of Re atoms in W. Under the intense radiation of a fusion reactor, up to 5% of W atoms will transmute into Re. According to currently available modelling, the Re atoms should disperse through the W, yet experiments show clusters form. These clusters cause the material to become brittle, limiting its useful lifetime. The first case study will apply the new simulations to understand this. The second concerns the behaviour of dislocations under irradiation. This can be very different from their usual behaviour, and will strongly affect the mechanical properties of reactor materials. Current simulation methods ignore the single-atom defects, but these are crucial for understanding radiation effects. The new methods will track both kinds of defect, and help provide the understanding needed to mitigate and control them. The final case study will investigate the interaction of C atoms with dislocations. This is the process that makes iron into steel, and its importance can hardly be overstated. Although identified decades ago, important unanswered questions remain, and the new tools this project aims to develop will answer them.
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