Building Symmetry During Crystal Structure Prediction

Unconstrained crystal structure prediction is difficult in large cells since the number of free variables increases rapidly with the number of atoms that are included. We describe a method that builds symmetry on the fly during crystal structure prediction and uses this symmetry to reduce the dimensionality of the search space. We apply this method to Monte Carlo-based crystal structure prediction and show that simulations that build symmetry greatly outperform those that do not, both in average and fastest times to find the ground state structure.