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BDA: A novel method for identifying defects in body-centered cubic crystals

The accurate and fast identification of crystallographic defects plays a key role for the analysis of atomistic simulation output data. For face-centered cubic (fcc) metals, most existing structure analysis tools allow for the direct distinction of common defects, such as stacking faults or certain...

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Autores principales: Möller, Johannes J., Bitzek, Erik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4831984/
https://www.ncbi.nlm.nih.gov/pubmed/27114926
http://dx.doi.org/10.1016/j.mex.2016.03.013
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author Möller, Johannes J.
Bitzek, Erik
author_facet Möller, Johannes J.
Bitzek, Erik
author_sort Möller, Johannes J.
collection PubMed
description The accurate and fast identification of crystallographic defects plays a key role for the analysis of atomistic simulation output data. For face-centered cubic (fcc) metals, most existing structure analysis tools allow for the direct distinction of common defects, such as stacking faults or certain low-index surfaces. For body-centered cubic (bcc) metals, on the other hand, a robust way to identify such defects is currently not easily available. We therefore introduce a new method for analyzing atomistic configurations of bcc metals, the BCC Defect Analysis (BDA). It uses existing structure analysis algorithms and combines their results to uniquely distinguish between typical defects in bcc metals. In essence, the BDA method offers the following features: • Identification of typical defect structures in bcc metals. • Reduction of erroneously identified defects by iterative comparison to the defects in the atom's neighborhood. • Availability as ready-to-use Python script for the widespread visualization tool OVITO [http://ovito.org].
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spelling pubmed-48319842016-04-25 BDA: A novel method for identifying defects in body-centered cubic crystals Möller, Johannes J. Bitzek, Erik MethodsX Materials Science The accurate and fast identification of crystallographic defects plays a key role for the analysis of atomistic simulation output data. For face-centered cubic (fcc) metals, most existing structure analysis tools allow for the direct distinction of common defects, such as stacking faults or certain low-index surfaces. For body-centered cubic (bcc) metals, on the other hand, a robust way to identify such defects is currently not easily available. We therefore introduce a new method for analyzing atomistic configurations of bcc metals, the BCC Defect Analysis (BDA). It uses existing structure analysis algorithms and combines their results to uniquely distinguish between typical defects in bcc metals. In essence, the BDA method offers the following features: • Identification of typical defect structures in bcc metals. • Reduction of erroneously identified defects by iterative comparison to the defects in the atom's neighborhood. • Availability as ready-to-use Python script for the widespread visualization tool OVITO [http://ovito.org]. Elsevier 2016-03-31 /pmc/articles/PMC4831984/ /pubmed/27114926 http://dx.doi.org/10.1016/j.mex.2016.03.013 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Materials Science
Möller, Johannes J.
Bitzek, Erik
BDA: A novel method for identifying defects in body-centered cubic crystals
title BDA: A novel method for identifying defects in body-centered cubic crystals
title_full BDA: A novel method for identifying defects in body-centered cubic crystals
title_fullStr BDA: A novel method for identifying defects in body-centered cubic crystals
title_full_unstemmed BDA: A novel method for identifying defects in body-centered cubic crystals
title_short BDA: A novel method for identifying defects in body-centered cubic crystals
title_sort bda: a novel method for identifying defects in body-centered cubic crystals
topic Materials Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4831984/
https://www.ncbi.nlm.nih.gov/pubmed/27114926
http://dx.doi.org/10.1016/j.mex.2016.03.013
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