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Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting
Scanning transmission electron microscopy (STEM) data with atomic resolution can contain a large amount of information about the structure of a crystalline material. Often, this information is hard to extract, due to the large number of atomic columns and large differences in intensity from sublatti...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5306439/ https://www.ncbi.nlm.nih.gov/pubmed/28251043 http://dx.doi.org/10.1186/s40679-017-0042-5 |
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author | Nord, Magnus Vullum, Per Erik MacLaren, Ian Tybell, Thomas Holmestad, Randi |
author_facet | Nord, Magnus Vullum, Per Erik MacLaren, Ian Tybell, Thomas Holmestad, Randi |
author_sort | Nord, Magnus |
collection | PubMed |
description | Scanning transmission electron microscopy (STEM) data with atomic resolution can contain a large amount of information about the structure of a crystalline material. Often, this information is hard to extract, due to the large number of atomic columns and large differences in intensity from sublattices consisting of different elements. In this work, we present a free and open source software tool for analysing both the position and shapes of atomic columns in STEM-images, using 2-D elliptical Gaussian distributions. The software is tested on variants of the perovskite oxide structure. By first fitting the most intense atomic columns and then subtracting them, information on all the projected sublattices can be obtained. From this, we can extract changes in the lattice parameters and shape of A-cation columns from annular dark field images of perovskite oxide heterostructures. Using annular bright field images, shifts in oxygen column positions are also quantified in the same heterostructure. The precision of determining the position of atomic columns is compared between STEM data acquired using standard acquisition, and STEM-images obtained as an image stack averaged after using non-rigid registration. |
format | Online Article Text |
id | pubmed-5306439 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-53064392017-02-27 Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting Nord, Magnus Vullum, Per Erik MacLaren, Ian Tybell, Thomas Holmestad, Randi Adv Struct Chem Imaging Research Scanning transmission electron microscopy (STEM) data with atomic resolution can contain a large amount of information about the structure of a crystalline material. Often, this information is hard to extract, due to the large number of atomic columns and large differences in intensity from sublattices consisting of different elements. In this work, we present a free and open source software tool for analysing both the position and shapes of atomic columns in STEM-images, using 2-D elliptical Gaussian distributions. The software is tested on variants of the perovskite oxide structure. By first fitting the most intense atomic columns and then subtracting them, information on all the projected sublattices can be obtained. From this, we can extract changes in the lattice parameters and shape of A-cation columns from annular dark field images of perovskite oxide heterostructures. Using annular bright field images, shifts in oxygen column positions are also quantified in the same heterostructure. The precision of determining the position of atomic columns is compared between STEM data acquired using standard acquisition, and STEM-images obtained as an image stack averaged after using non-rigid registration. Springer International Publishing 2017-02-13 2017 /pmc/articles/PMC5306439/ /pubmed/28251043 http://dx.doi.org/10.1186/s40679-017-0042-5 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Nord, Magnus Vullum, Per Erik MacLaren, Ian Tybell, Thomas Holmestad, Randi Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting |
title | Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting |
title_full | Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting |
title_fullStr | Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting |
title_full_unstemmed | Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting |
title_short | Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting |
title_sort | atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional gaussian fitting |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5306439/ https://www.ncbi.nlm.nih.gov/pubmed/28251043 http://dx.doi.org/10.1186/s40679-017-0042-5 |
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