Modeling Helium Segregation to the Surfaces of Plasma-Exposed Tungsten as a Function of Temperature and Surface Orientation

Abstract

We provide a description of the dependence on surface crystallographic orientation and temperature of the segregation of helium implanted with energies consistent with low-energy plasma exposure to tungsten surfaces. Here, we describe multiscale modeling results based on a hierarchical approach to scale bridging that incorporates atomistic studies based on a reliable interatomic potential to parameterize a spatially dependent drift-diffusion-reaction cluster-dynamics code. An extensive set of molecular dynamics (MD) simulations has been performed at 933 K and/or 1200 K to determine the probabilities of desorption and modified trap mutation that occurs as small, mobile He_n (1 ≤ n ≤ 7) clusters diffuse from the near-surface region toward surfaces of varying crystallographic orientation due to an elastic interaction force that provides the thermodynamic driving force for surface segregation. These near-surface cluster dynamics have significant effects on the surface morphology, the near-surface defect structures, and the amount of helium retained in the material upon plasma exposure, for which we have developed an extensive MD database of cumulative evolution during high-flux helium implantation at 933 K, which we compare to our properly parameterized cluster-dynamics model. This validated model is then used to evaluate the effects of temperature on helium retention and subsurface helium clustering.

• Helium clustering
• multiscale modeling
• plasma-surface interactions

Acknowledgments

This work was supported by the U.S. Department of Energy, Office of Fusion Energy Sciences and Office of Advanced Scientific Computing Research through the Scientific Discovery through Advanced Computing (SciDAC) Project on Plasma-Surface Interactions and involved award DE-SC0008875 at the University of Massachusetts, Amherst. Significant computing resources were used by this project at the National Energy Research Scientific Computing facility at Lawrence Berkeley National Laboratory and at the Argonne Leadership Computing Facility at Argonne National Laboratory, which are supported by the Office of Science of the U.S. Department of Energy under contracts DE-AC02-06CH11231 and DE-AC02-06CH11357, respectively. The use of the facilities of the Massachusetts Green High-Performance Computing Center also is gratefully acknowledged.