title: An adaptive genetic algorithm for crystal structure prediction.
abstract: We present a genetic algorithm (GA) for structural search that combines the speed of structure exploration by classical potentials with the accuracy of density functional theory (DFT) calculations in an adaptive and iterative way. This strategy increases the efficiency of the DFT-based GA by several orders of magnitude. This gain allows a considerable increase in the size and complexity of systems that can be studied by first principles. The performance of the method is illustrated by successful structure identifications of complex binary and ternary intermetallic compounds with 36 and 54 atoms per cell, respectively. The discovery of a multi-TPa Mg-silicate phase with unit cell containing up to 56 atoms is also reported. Such a phase is likely to be an essential component of terrestrial exoplanetary mantles.
authors.affiliation: Department of Physics, Xiamen University, Xiamen 361005, People's Republic of China. Ames Laboratory-US DOE and Department of Physics and Astronomy, Iowa State University, Ames, IA 50011, USA.
authors.forename: S Q
authors.initials: SQ
authors.lastname: Wu
authors.forename: M
authors.initials: M
authors.lastname: Ji
authors.forename: C Z
authors.initials: CZ
authors.lastname: Wang
authors.forename: M C
authors.initials: MC
authors.lastname: Nguyen
authors.forename: X
authors.initials: X
authors.lastname: Zhao
authors.forename: K
authors.initials: K
authors.lastname: Umemoto
authors.forename: R M
authors.initials: RM
authors.lastname: Wentzcovitch
authors.forename: K M
authors.initials: KM
authors.lastname: Ho