Structure and energetics of oxidic nanoclusters in bcc-iron

Nanostructured ferritic alloys (NFA) or Oxide Dispersion Strengthened (ODS) steels consist of an iron-based matrix with dispersed nanometer-size oxide particles. Compared to conventional steels these materials exhibit two remarkable properties that are not fully understood yet: (i) Stability: Up to rather high temperatures the number and size of the oxygen-rich nanoparticles do not change significantly. (ii) Tolerance: The nanoclusters act as sinks for transmutation helium, vacancies and self-interstitial. The first property is the reason for the improved creep strength at high temperature, whereas the second property is related to the radiation resistance of these materials. Therefore, NFA or ODS are promising candidates for applications as structural materials in extreme environments, i.e. at high temperature and intense particle irradiation, such as in advanced nuclear fission and fusion reactors.
The detailed structure and composition of the oxidic nanoclusters containing Y, Ti, O along with other minor alloying and impurity elements is still under discussion. In this work simulated annealing (SA) based on the Metropolis Monte Carlo method is used in order to determine the structure of the oxidic nanoclusters with the lowest formation energy. Since cluster sizes up to a few nm are of interest, first-principle methods cannot be used throughout since they are computationally too expensive. In contrast to previous theoretical investigations both pair and triple interactions between the different atomic species are employed in the SA method. The corresponding interaction parameters are obtained from comprehensive first-principle calculations on the structure and energetics of point defects and small clusters. SA is performed for various oxidic clusters and the results are compared with available experimental and theoretical data from literature. The binding energy of the nanoclusters obtained in this work can be used as input parameters of coarse-grained method such as Object Kinetic Monte Carlo simulations and Rate Theory.