Discovering New Materials via A Priori Crystal Structure Prediction

The computational prediction of new materials for specific applications hinges on the ability to prophesize their crystal structures prior to their synthesis. This is just one of the reasons for the growing interest in a priori crystal structure prediction (CSP). This chapter first discusses the properties of potential energy landscapes, and outlines computational techniques employed to calculate the energies and optimize the geometries of crystalline materials. This is followed by a description of some of the methods most widely used for CSP of inorganic solids. Calculations of the phonons, or vibrational normal modes, are required to verify that the structures found via the automated search techniques are local minima. The chapter focuses on the evolutionary algorithms (EAs). It presents examples of recent original research where the XtalOpt EA was employed to predict the structure of crystalline solids.