SMEPOC- a computer program for the automatic generation of trial structural models for inorganic compounds with symmetry restriction
A new structure modelling algorithm that can automatically generate trial structure models based on a prior knowledge of the unit‐cell content and space‐group information is proposed. It can enumerate all possible equivalent position combination (EPC) models and eliminate unreasonable ones with symm...
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| Published in | Journal of applied crystallography Vol. 42; no. 5; pp. 953 - 958 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
5 Abbey Square, Chester, Cheshire CH1 2HU, England
International Union of Crystallography
01.10.2009
Blackwell Publishing Ltd |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1600-5767 0021-8898 1600-5767 |
| DOI | 10.1107/S0021889809034062 |
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| Summary: | A new structure modelling algorithm that can automatically generate trial structure models based on a prior knowledge of the unit‐cell content and space‐group information is proposed. It can enumerate all possible equivalent position combination (EPC) models and eliminate unreasonable ones with symmetry restriction. Unlike other methods, it does not require the internal molecular connectivity or coordination polyhedron information and is mostly suitable for modelling inorganic crystals with independent atoms. Therefore, these EPC models can be used as input to global optimization procedures for inorganic crystal structure determination using powder diffraction data by the direct‐space method. The efficiency of the direct‐space method can be greatly improved using this EPC method because the global optimization problem in a 3N‐parameter space can be divided into a set of simpler ones. A program, SMEPOC, that can generate all possible EPC models for further global optimization procedures has been developed and is now available from the authors upon request. |
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| Bibliography: | ark:/67375/WNG-606DFBBD-1 ArticleID:JCRDB5062 istex:FDF70BC8A4A776D6D93C58BF9C7F5275C73F15C5 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-2 content type line 23 |
| ISSN: | 1600-5767 0021-8898 1600-5767 |
| DOI: | 10.1107/S0021889809034062 |