The Kinetics of Dislocation Loop Formation in Ferritic Alloys Through the Aggregation of Irradiation Induced Defects
The mechanical properties of materials are often degraded over time by exposure to irradiation environments, a phenomenon that has hindered the development of multiple nuclear reactor design concepts. Such property changes are the result of microstructural changes induced by the collision of high energy particles with the atoms in a material. The lattice defects generated in these recoil events migrate and interact to form extended damage structures.
This study has used theoretical models based on the mean field chemical reaction rate theory to analyze the aggregation of isolated lattice defects into larger microstructural features that are responsible for long term property changes, focusing on the development of black dot damage in ferritic iron based alloys. The purpose of such endeavors is two-fold. Primarily, such models explain and quantify the processes through which these microstructures form. Additionally, models provide insight into the behavior and properties of the point defects and defect clusters which drive general microstructural evolution processes.
The modeling effort presented in this work has focused on physical fidelity, drawing from a variety of sources of information to characterize the unobservable defect generation and agglomeration processes that give rise to the observable features reported in experimental data. As such, the models are based not solely on isolated point defect creation, as is the case with many older rate theory approaches, but instead on realistic estimates of the defect cluster population produced in high energy cascade damage events. Experimental assessments of the microstructural changes evident in transmission electron microscopy studies provide a means to measure the efficacy of the kinetic models. Using common assumptions of the mobility of defect clusters generated in cascade damage conditions, an unphysically high density of damage features develops at the temperatures of interest with a temperature dependence that is much too strong.
The so-called nucleation catastrophe motivates a re-examination of the properties of interstitial defect clusters in iron. The behavior of interstitial clusters in iron is a complex puzzle, with high mobility predicted by computational techniques, much lower thermal mobility observed in electron microscopes, and a series of discrete discontinuous motions seen during in situ ion irradiation performed in a transmission electron microscope. This work has combined these observations and presented a trap mediated concept of interstitial cluster motion that has been incorporated into a larger scale kinetic model. This superior description of interstitial mobility is crucial to realizing many aspects of black dot damage structures, from saturation behavior to temperature dependence.
Another focus of this work was to analyze the assumptions widely employed in rate theory models. Cluster dynamics, the rate theory method employed in this work, is usually invoked with a number of potentially dubious assumptions regarding the mobility and interaction characteristics of defect clusters. The effects of anisotropic reaction volumes and one dimensional diffusion have both been analyzed to determine the effect they have on the development of black dot microstructures. In the trap mediated system, one dimensional diffusion proved far more significant, and the cross section for interaction between one dimensionally diffusing interstitial clusters strongly influenced the size and density of visible damage structures. The validity of the reaction rate approach to determining cluster evolution in the trap mediated environment has been established by comparison with Monte Carlo methods.
In total, this work has demonstrated the ability of mean field models to capture the key characteristics of low temperature damage microstructures in irradiated ferritic alloys when incorporating the full knowledge of interstitial cluster properties in iron, and the legitimacy of the mean field assumptions by comparison to other methods.