DOI: 10.5281/zenodo.2652906
title: Data for "Nano-scale characterisation of sheared β'' precipitates in a deformed Al-Mg-Si alloy"

description: This dataset contains data used in the publication entitled "<strong>Nano-scale characterisation of sheared β'' precipitates in a deformed Al-Mg-Si alloy</strong>". This publication concerns how β'' precipitates are sheared by dislocations during deformation. The data contained in this repository are data acquired on various transmission electron microscopes of specimens of the aluminium alloy AA6060 in peak aged condition after uniaxial compression to 5%, 10%, and 20%, in addition to the undeformed reference alloy. There are five main types of data: Transmission electron microscopy (TEM) images High-resolution TEM images High angle annular dark field (HAADF) scanning TEM (STEM) images Scanning precession electron diffraction (SPED) data. Cross-sectional data of precipitates in undeformed and 20% compressed conditions. Data for the TEM, HRTEM, and STEM images are kept in zipped folders due to the large number of images (several hundreds for each compression condition). Folders are named following the format of "&lt;alloy&gt;_&lt;compression&gt;_&lt;technique&gt;", where technique refers to TEM, HRTEM, or STEM. Images are provided in both .hdf format and .jpg format (to aid in navigating the data). Please see HDF Group for more information regarding the HDF file format, and HDF View for softaware to read and show HDF data. The Python package HyperSpy, is also useful for loading the HDF data for inspection, analysis, and presentation. For some STEM images, a stack of short-exposure STEM images acquired and analysed using the <em>SmartAlign</em> plugin to <em>Gatan Digital Micrograph</em> is available. SmartAlign offers the possibility of rigidly and non-rigidly aligning the STEM images in the stack in order to reduce effect of specimen drift and scan noise during acquisition. The conventional STEM images are found in the zip archive labelled "STEM". When the filenames of the STEM images include "SAstack" and/or "SAimage", a STEM SmartAlign stack or the average through a non-rigidly aligned stack is available of the same field of view. In such cases, both the SmartAlign stack and the through-stack image is provided in the metadata in the .hdf file (note that not all stacks have been aligned, and in such cases no through-stack image is available). In addition, the SmartAlign stacks themselves are available in the subfolder "STEM\SmartAlign\" within each STEM folder. The through-stack images of the smart align stacks are also provided separately in the subfolder "STEM\SmartAlign\Aligned\". For the 20% compressed case, a lowloss electron energy loss spectroscopy (EELS) spectrum and thickness maps of the imaged areas are also provided, in the subfolder "STEM\EELS\". The SPED data, acquired using the <em>ASTAR</em> system of <em>NanoMegas</em>, is provided as .hdf5 files in the root directory of the repository. They should be read using and pyXem. The attached Jupyter Notebook "SPED_data_inspection.ipynb" can be used to access the SPED datasets. These datasets are 4D datasets, with two spatial and two reciprocal dimensions. They have been decomposed using the non-negative matrix factorization algorithm (NMF) used in HyperSpy. These decomposition results are included in the .hdf5 files. In addition, parameters used in the preprocessing of the datasets are attached in the metadata in these files. The metadata of these files are also provided separately as .txt files. Finally, measurements of the precipitate cross-sectional area and circularity is available as .csv files with the first column being the row index, the second the cross-sectional areas of precipitates measured in nanometers squared, the third column is the perimeters of the precipitates measured in nanometers, and column four is the circularity of the precipitates.
description: {"references": ["Pe\u00f1a, F. d. l. et al. (2018). HyperSpy \u2013 1.4.1, DOI: 10.5281/ZENODO.1469364.", "Johnstone, D. N. et al. (2019). pyXem \u20130.7.1, DOI: 10.5281/ZENODO.2650296."]}