Atomic-scale three-dimensional irradiation-induced defect kinetics models for bcc Fe-based alloys

Abstract

The interaction between irradiation defects and dislocations could lead to macroscopic hardening and embrittlement. In this study, molecular dynamics (MD) and machine learning were conducted to study three-dimensional void- and Cu-cluster-induced kinetics models under interaction with dislocations in body-centered cubic Fe-based alloys. MD Results show that dislocation climb and shear are two types of interaction mechanism based on the defect size. Combined MD results and machine learning, it was found that the dislocation length increased linearly with an increase in the size of the defects after the interaction. In addition, the number of atoms in the Cu-rich cluster and the reduced number of vacancies in the voids had a square relationship with the defect size where 0.85D2 is for Cu-rich cluster and 0.50D2 is for void. Furthermore, atomic-scale three-dimensional irradiation-induced defect kinetics models were developed and incorporated into the crystal plasticity finite element model (CPFEM). We also analyzed the contributions of various defects to the increase in the yield stress during CPFEM simulation. Compared with DBH model, the prediction of MD data-driven CPFEM matches better with the experimental data. Cluster contributed the most to hardening with low obstacle strength due to the higher number density compared with dislocation loops and voids. The loops also contributed to hardening; however, their contribution was smaller than that of the clusters. Although the number density and size of voids were minimized, they may have contributed because of the high obstacle strengths. This work can indeed deepen the understanding of irradiation effect in Fe-based alloys.

Keywords

• Void
• Cu cluster
• Molecular dynamics
• Machine learning
• Kinetics model