Modeling of Cu Precipitation in Fe–Cu and Fe–Cu–Mn Alloys Under Neutron and Electron Irradiation

• Published in: Metallurgical and materials transactions. A, Physical metallurgy and materials science Physical metallurgy and materials science, 2024-06, Vol.55 (6), p.1849-1866
• Main Author: Cui, Senlin
• Format: Article
• Language: English
• Subjects: Characterization and Evaluation of Materials; Chemistry and Materials Science; Clusters; Copper; Electron irradiation; Enhanced diffusion; Ferrous alloys; Kinetics; Low temperature; Materials Science; Metallic Materials; Modelling; Nanotechnology; Original Research Article; Parameter sensitivity; Precipitates; Pressure vessels; Radiation; Radiation damage; Structural Materials; Structural steels; Surfaces and Interfaces; Thin Films
• ISSN: 1073-5623; 1543-1940
• DOI: 10.1007/s11661-024-07357-0

Irradiation-induced formation of Cu-rich precipitates embrittles reactor pressure vessel steels. In the present work, a cluster dynamics model is used to model the precipitation of Cu-rich precipitates in Fe–Cu and Fe–Cu–Mn model alloys under neutron and electron irradiation at about 300 °C (573 K). The model includes radiation-enhanced diffusion and mobile Cu-rich clusters, which have been suggested to play important roles in Cu precipitation kinetics in Fe-based alloys. Precipitation at low temperatures is accelerated by radiation-enhanced diffusion, due to excess vacancies produced by displacement damages. Previous modeling work of thermal precipitation in Fe–Cu alloys at higher temperatures suggests that Cu clusters are mobile, and that this mobility must be accounted for to predict the observed precipitation kinetics. Here, the present work extends the mobile cluster model to treat precipitation in Fe–Cu and Fe–Cu–Mn alloys under neutron and electron irradiation. Comparison of the properly parameterized model predictions with the experimental observations shows that treating radiation-enhanced cluster mobility is necessary to predict Cu precipitation kinetics under irradiation. The developed precipitation model can reasonably describe the selected reliable experimental data. The model parameter determination for the physically based model includes extensive sensitivity studies, and suggests that the present approach still needs refinement to provide an accurate model that is fully consistent with the known microscopic measurements.