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GIDInd: an automated indexing software for grazing-incidence X-ray diffraction data
Grazing-incidence X-ray diffraction (GIXD) is a widely used technique for the crystallographic characterization of thin films. The identification of a specific phase or the discovery of an unknown polymorph always requires indexing of the associated diffraction pattern. However, despite the importan...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Union of Crystallography
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8366425/ https://www.ncbi.nlm.nih.gov/pubmed/34429726 http://dx.doi.org/10.1107/S1600576721006609 |
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author | Kainz, Manuel Peter Legenstein, Lukas Holzer, Valentin Hofer, Sebastian Kaltenegger, Martin Resel, Roland Simbrunner, Josef |
author_facet | Kainz, Manuel Peter Legenstein, Lukas Holzer, Valentin Hofer, Sebastian Kaltenegger, Martin Resel, Roland Simbrunner, Josef |
author_sort | Kainz, Manuel Peter |
collection | PubMed |
description | Grazing-incidence X-ray diffraction (GIXD) is a widely used technique for the crystallographic characterization of thin films. The identification of a specific phase or the discovery of an unknown polymorph always requires indexing of the associated diffraction pattern. However, despite the importance of this procedure, only a few approaches have been developed so far. Recently, an advanced mathematical framework for indexing of these specific diffraction patterns has been developed. Here, the successful implementation of this framework in the form of an automated indexing software, named GIDInd, is introduced. GIDInd is based on the assumption of a triclinic unit cell with six lattice constants and a distinct contact plane parallel to the substrate surface. Two approaches are chosen: (i) using only diffraction peaks of the GIXD pattern and (ii) combining the GIXD pattern with a specular diffraction peak. In the first approach the six unknown lattice parameters have to be determined by a single fitting procedure, while in the second approach two successive fitting procedures are used with three unknown parameters each. The output unit cells are reduced cells according to approved crystallographic conventions. Unit-cell solutions are additionally numerically optimized. The computational toolkit is compiled in the form of a MATLAB executable and presented within a user-friendly graphical user interface. The program is demonstrated by application on two independent examples of thin organic films. |
format | Online Article Text |
id | pubmed-8366425 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | International Union of Crystallography |
record_format | MEDLINE/PubMed |
spelling | pubmed-83664252021-08-23 GIDInd: an automated indexing software for grazing-incidence X-ray diffraction data Kainz, Manuel Peter Legenstein, Lukas Holzer, Valentin Hofer, Sebastian Kaltenegger, Martin Resel, Roland Simbrunner, Josef J Appl Crystallogr Computer Programs Grazing-incidence X-ray diffraction (GIXD) is a widely used technique for the crystallographic characterization of thin films. The identification of a specific phase or the discovery of an unknown polymorph always requires indexing of the associated diffraction pattern. However, despite the importance of this procedure, only a few approaches have been developed so far. Recently, an advanced mathematical framework for indexing of these specific diffraction patterns has been developed. Here, the successful implementation of this framework in the form of an automated indexing software, named GIDInd, is introduced. GIDInd is based on the assumption of a triclinic unit cell with six lattice constants and a distinct contact plane parallel to the substrate surface. Two approaches are chosen: (i) using only diffraction peaks of the GIXD pattern and (ii) combining the GIXD pattern with a specular diffraction peak. In the first approach the six unknown lattice parameters have to be determined by a single fitting procedure, while in the second approach two successive fitting procedures are used with three unknown parameters each. The output unit cells are reduced cells according to approved crystallographic conventions. Unit-cell solutions are additionally numerically optimized. The computational toolkit is compiled in the form of a MATLAB executable and presented within a user-friendly graphical user interface. The program is demonstrated by application on two independent examples of thin organic films. International Union of Crystallography 2021-07-30 /pmc/articles/PMC8366425/ /pubmed/34429726 http://dx.doi.org/10.1107/S1600576721006609 Text en © Manuel Peter Kainz et al. 2021 https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution (CC-BY) Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited. |
spellingShingle | Computer Programs Kainz, Manuel Peter Legenstein, Lukas Holzer, Valentin Hofer, Sebastian Kaltenegger, Martin Resel, Roland Simbrunner, Josef GIDInd: an automated indexing software for grazing-incidence X-ray diffraction data |
title | GIDInd: an automated indexing software for grazing-incidence X-ray diffraction data |
title_full | GIDInd: an automated indexing software for grazing-incidence X-ray diffraction data |
title_fullStr | GIDInd: an automated indexing software for grazing-incidence X-ray diffraction data |
title_full_unstemmed | GIDInd: an automated indexing software for grazing-incidence X-ray diffraction data |
title_short | GIDInd: an automated indexing software for grazing-incidence X-ray diffraction data |
title_sort | gidind: an automated indexing software for grazing-incidence x-ray diffraction data |
topic | Computer Programs |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8366425/ https://www.ncbi.nlm.nih.gov/pubmed/34429726 http://dx.doi.org/10.1107/S1600576721006609 |
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