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An adaptive genetic algorithm for crystal structure prediction

TitleAn adaptive genetic algorithm for crystal structure prediction
Publication TypeJournal Article
Year of Publication2014
AuthorsWu, SQ, Ji, M, Wang, CZ, Nguyen, MC, Zhao, X, Umemoto, K, Wentzcovitch, RM, Ho, KM
JournalJournal of Physics-Condensed Matter
Date Published01
Type of ArticleArticle
ISBN Number0953-8984
Accession NumberWOS:000329525500010
Keywordsab-initio data, dissociation, effective potentials, high-pressure, mgo, mgsio3, optimization, post-perovskite phase, total-energy calculations, wave basis-set

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.

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