This paper describes the dynamics of helium clustering behaviour within either a nanometer-sized tendril of fuzz, or a half-space domain, as predicted by a reaction–diffusion model. This analysis has identified a dimensionless parameter, PΔ, which is a balance of the reaction and diffusion actions of insoluble He in a metal matrix and which governs the self-trapping effects of He into growing bubbles within a tendril. The impact of He self-trapping, as well as trapping caused by pre-existing traps in the form of lattice defects or clusters of impurities, within a half-space domain results in the formation of a densely packed layer of nanometer-sized bubbles with high number density. This prediction is consistent with available experimental observations in which a dense zone of helium bubbles is observed in tungsten, which are compared to estimates of the layer characteristics. Direct numerical simulation of the reaction–diffusion cluster dynamics supports the analysis presented here.
In fusion reactors, plasma facing components (PFC) and, in particular, the divertor will be irradiated with high fluxes of lowenergy (∼100 eV) helium and hydrogen ions. Tungsten is one of the leading candidate divertor materials for ITER and DEMO fusion reactors. However, the behaviour of tungsten under high dose, coupled helium/hydrogen exposure remains to be fully understood. The PFC response and performance changes are intimately related to microstructural changes, such as the formation of point defect clusters, helium and hydrogen bubbles or dislocation loops. Computational materials' modelling results are described here that investigate the mechanisms controlling microstructural evolution in tungsten. The aim of this study is to understand and predict sub-surface helium bubble growth under high flux helium ion implantation (∼10 22 m −2 s −1 ) at high temperatures (>1000 K). We report results from a spatially dependent cluster dynamics model based on reaction-diffusion rate theory to describe the evolution of the microstructure under these conditions. The key input parameters to the model (diffusion coefficients, migration and binding energies, initial defect production) are determined from a combination of atomistic modelling and available experimental data. The results are in good agreement with results of an analytical model that is presented in a separate paper. In particular, it is found that the sub-surface evolution with respect to bubble size and concentration of the helium bubbles strongly depends on the flux and temperature.
In fusion reactors, plasma facing components (PFC) and in particular the divertor will be irradiated with high fluxes of low energy (∼100 eV) helium and hydrogen ions. Tungsten is one of the leading candidate divertor materials for ITER and DEMO fusion reactors. However, the behavior of tungsten under high dose, coupled helium/hydrogen exposure remains to be fully understood. The PFC response and performance changes are intimately related to microstructural changes, such as the formation of point defect clusters, helium and hydrogen bubbles or dislocation loops. Computational materials modeling has been used to investigate the mechanisms controlling microstructural evolution in tungsten following high dose, high temperature helium exposure. The aim of this study is to understand and predict helium implantation, primary defect production and defect diffusion, helium-defect clustering and interactions below a tungsten surface exposed to low energy helium irradiation. The important defects include interstitial clusters, vacancy clusters, helium interstitials and helium-vacancy clusters. We report results from a one-dimensional, spatially dependent cluster dynamics model based on the continuum reaction–diffusion rate theory to describe the evolution in space and time of all these defects. The key parameter inputs to the model (diffusion coefficients, migration and binding energies, initial defect production) are determined from a combination of atomistic materials modeling and available experimental data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.