Investigation of Static and Dynamic Reaction Mechanisms at Interfaces and Surfaces Using Density Functional Theory and Kinetic Monte Carlo Simulations

The following dissertation is divided into two parts. Part I deals with the modeling of helium trapping at oxide-iron interfaces in nanostructured ferritic alloys (NFAs) using density functional theory (DFT). The modelling that has been performed serves to increase the knowledge and understanding of the theory underlying the prevention of helium embrittlement in materials. Although the focus is for nuclear reactor materials, the theory can be applied to any material that may be in an environment where helium embrittlement is of concern. In addition to an improved theoretical understanding of helium embrittlement, the following DFT models will provide valuable thermodynamic and kinetic information. This information can be utilized in the development of large-scale models (such as kinetic Monte Carlo simulations) of the microstructural evolution of reactor components. Accurate modelling is an essential tool for the development of new reactor materials, as experiments for components can span decades for the lifetime of the reactor.

Part II of this dissertation deals with the development, and use of, kinetic Monte Carlo (KMC) simulations for improved efficiency in investigating catalytic chemical reactions on surfaces. An essential technique for the predictive development and discovery of catalysts relies on modelling of large-scale chemical reactions. This requires multi-scale modelling where a common sequence of techniques would require parameterization obtained from DFT, simulation of the chemical reactions for millions of conditions using KMC (requiring millions of separate simulations), and finally simulation of the large scale reactor environment using computational fluid dynamics. The tools that have been developed will aid in the predictive discovery, development and modelling of catalysts through the use of KMC simulations. The algorithms that have been developed are versatile and thus, they can be applied to nearly any KMC simulation that would seek to overcome similar challenges as those posed by investigating catalysis (such as the need for millions of simulations, long simulation time and large discrepancies in transition probabilities).