Generating derivative structures at a fixed concentration
► An order-N algorithm for generating large derivative structures is developed. ► The algorithm is useful for bulk and surface alloys, oxides, hydrogen storage, etc. ► The algorithm extends previous work to much larger cases. We present an algorithm for generating derivative superstructures for larg...
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Published in | Computational materials science Vol. 59; pp. 101 - 107 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Elsevier B.V
01.06.2012
Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | ► An order-N algorithm for generating large derivative structures is developed. ► The algorithm is useful for bulk and surface alloys, oxides, hydrogen storage, etc. ► The algorithm extends previous work to much larger cases.
We present an algorithm for generating derivative superstructures for large unit cells at a fixed concentration. The algorithm is useful when partial crystallographic information of an ordered phase is known. This work builds on the previous work of Hart and Forcade [Phys. Rev. B 77 224115, 2008; Phys. Rev. B 80 014120, 2009]. This extension of the original algorithm provides a mapping from atomic configurations to consecutive integers when only a subset (fixed concentration) of all possible configurations is under consideration. As in the earlier algorithm, this mapping results in a minimal hash table and perfect hash function that enables an efficient method for enumerating the configurations of large unit cells; the run time scales linearly with the number of symmetrically-distinct configurations. We demonstrate the algorithm for a proposed structure in the Ag–Pt system comprising 32 atoms, with stoichiometry 15:17, a configuration space of ∼400,000. |
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ISSN: | 0927-0256 1879-0801 |
DOI: | 10.1016/j.commatsci.2012.02.015 |