Abstract

First-principles structure prediction of crystalline solids is now routinely performed, however the field of predicting the atomic structure of interfaces and extended defects from first-principles is still in its infancy. A detailed understanding of and ability to predict the atomic structure of interfaces is however of crucial importance for many technologies. Interfaces are very hard to predict due to the complicated geometries, crystal orientations and possible non-stoichiometric conditions involved and provide a major challenge to structure prediction. I will present here how the ab initio random structure searching (AIRSS) method can be used to predict the atomic structure of interfaces. Our method relies on generating random structures in the vicinity of the interface and relaxing them within the framework of density functional theory. The method is simple, requiring only a small set of parameters, and can be efficiently run on modern parallel computer architectures. Examples of several interfaces in technologically important materials will be presented, including grain boundaries in 2D materials (graphene), as well as much more complex 3D systems such as grain boundaries in metals and transition metal oxides (SrTiO3, TiO2). Direct comparison to experimental results will be made.