Evolution of cavities in BCC-Fe with coexisting H and He under fusion environments
Source abstract
Abstract
In the fusion environment, understanding the synergistic effects of transmutation-produced hydrogen (H), helium (He), and irradiation-induced displacement damage in iron-based alloys is crucial for the development of structural materials for fusion reactors. When H and He atoms are simultaneously introduced into the matrix, the interaction between irradiation-induced cavity defects (voids and bubbles) with H and He, along with their evolutionary behavior remains poorly understood. In this study, the evolutionary behavior of cavities in body-centered cubic (BCC) iron (Fe) with H and He atoms is systematically investigated through a combination of molecular dynamics (MD) calculations and statistical thermodynamics. First, an efficient and suitable set of Fe-H-He ternary potential functions for describing interatomic interactions is established. Based on the newly developed MD model, the evolutionary behavior of H/He atoms and cavities is systematically investigated under various temperature and cavity structure conditions. Specifically, the kinetic process of H/He capture by cavities is elucidated for different scenarios. Additionally, thermodynamic analyses are employed to assess the feasibility of cavity trapping of H under varying conditions. The results exhibit strong consistency with experimental results and provide significant evidence supporting the formation of the core-shell structure (where He is confined at the cavity center while H accumulates at the surface) from both kinetic and thermodynamic perspectives. This work provides mechanistic insights into the nucleation and growth of cavities over extended temporal and spatial scales in the presence of H-He synergies.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Fusion materials and technologies · Nuclear Materials and Properties · High-pressure geophysics and materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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