| Title |
Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting
|
|---|---|
| Published in |
Advanced Structural and Chemical Imaging, February 2017
|
| DOI | 10.1186/s40679-017-0042-5 |
| Pubmed ID | |
| Authors |
Magnus Nord, Per Erik Vullum, Ian MacLaren, Thomas Tybell, Randi Holmestad |
| Abstract |
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. |
Mendeley readers
The data shown below were compiled from readership statistics for 172 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 172 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 60 | 35% |
| Researcher | 29 | 17% |
| Student > Master | 16 | 9% |
| Student > Doctoral Student | 13 | 8% |
| Other | 7 | 4% |
| Other | 14 | 8% |
| Unknown | 33 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Materials Science | 77 | 45% |
| Physics and Astronomy | 23 | 13% |
| Engineering | 9 | 5% |
| Chemistry | 5 | 3% |
| Agricultural and Biological Sciences | 2 | 1% |
| Other | 14 | 8% |
| Unknown | 42 | 24% |