Improving magnetic STEM-differential phase contrast imaging using precession

Scanning transmission electron microscopy datasets and processing files used in the journal publication "Improving Magnetic STEM-Differential Phase Contrast Imaging using Precession".

DOI link to publication: https://doi.org/10.1093/micmic/ozad001

Prerequisites

To run the scripts necessary to process the files, the open source packages JupyterLab, HyperSpy, pyXem, and fpd need to be installed. These notebooks were created with these package versions:

hyperspy 1.6.4

pyxem 0.13.3

fpd 0.2.0

jupyterlab 3.2.0

Data files and processing scripts

Data files are collected in .zip folders and have names that start with "d00..", while processing scripts are in the Jupyter Notebook .ipynb data format whose names start with "p00..". These files are divided into three main processing steps, outlined as follows:

Processing of raw data: Raw data files can be found in the d001_scans.zip folder. These are processed with the p002_get_dpc_raw.ipynb script which uses either the center of mass or phase correlation methods.

D-scan correction: The processed files from the previous step are saved in the d002_dpc_raw.zip folder. The p003_get_dpc_cor.ipynb script performs a d-scan correction on these files and saves the output in the d003_dpc_cor.zip folder.

Virtual segmented detector algorithm: For comparison purposes to the other processing algorithms, a virtual segmented detector algorithm was developed and can be found in the p004_segmented_detector.ipynb script. This algorithm extracts a linear d-scan plane from already processed phase correlation files found in d002_dpc_raw.zip, subtracts it from the raw data files found in d001_scans.zip, and finally performs the processing algorithm.

Plotting files: The p005_plot_dpc_images.ipynb script creates the figures as seen in the journal publication. The input files are those found in d003_dpc_cor.zip from the previous processing step.