DocumentCode :
3415931
Title :
Crystal structures classifier for an evolutionary algorithm structure predictor
Author :
Valle, Mario ; Oganov, Artem R.
Author_Institution :
Data Anal. & Visualization Services, Swiss Nat. Supercomput. Centre (CSCS)
fYear :
2008
fDate :
19-24 Oct. 2008
Firstpage :
11
Lastpage :
18
Abstract :
USPEX is a crystal structure predictor based on an evolutionary algorithm. Every USPEX run produces hundreds or thousands of crystal structures, some of which may be identical. To ease the extraction of unique and potentially interesting structures we applied usual high-dimensional classification concepts to the unusual field of crystallography. We experimented with various crystal structure descriptors, distinct distance measures and tried different clustering methods to identify groups of similar structures. These methods are already applied in combinatorial chemistry to organic molecules for a different goal and in somewhat different forms, but are not widely used for crystal structures classification. We adopted a visual design and validation method in the development of a library (CrystalFp) and an end-user application to select and validate method choices, to gain userspsila acceptance and to tap into their domain expertise. The use of the classifier has already accelerated the analysis of USPEX output by at least one order of magnitude, promoting some new crystallographic insight and discovery. Furthermore the visual display of key algorithm indicators has led to diverse, unexpected discoveries that will improve the USPEX algorithms.
Keywords :
chemistry computing; crystal structure; crystallography; evolutionary computation; USPEX; clustering methods; combinatorial chemistry; crystal structure classifier; crystallography; evolutionary algorithm structure predictor; Acceleration; Chemistry; Clustering methods; Crystalline materials; Crystallography; Design methodology; Electronic mail; Evolutionary computation; Libraries; Multidimensional systems; I.5.2 [Pattern Recognition]: Design Methodology—Classifier design and evaluation; J.2 [Physical Sciences and Engineering]: Chemistry;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Visual Analytics Science and Technology, 2008. VAST '08. IEEE Symposium on
Conference_Location :
Columbus, OH
Print_ISBN :
978-1-4244-2935-6
Type :
conf
DOI :
10.1109/VAST.2008.4677351
Filename :
4677351
Link To Document :
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