The prediction of inorganic crystal structures using a genetic algorithm and energy minimisation

A genetic algorithm has been used to generate plausible crystal structures from the knowledge of only the unit cell dimensions and constituent element s. We successfully generate 38 known binary oxides and various known ternar y oxides with the Perovskite, Pyrochlore and Spinel structures, from starti ng configurations which include no knowledge of the atomic arrangement in t he unit cell. The quality of the structures is initially assessed using a c ost function which is based on the bond valence model with a number of refi nements. The lattice energy, based on the Born model of a solid, is minimis ed using a local optimiser for the more plausible candidate structures. The method has been implemented within the computational package GULP. An exte nsive collection of Buckingham potential parameters for use in such simulat ions on metal oxides is also tabulated.