Newer
Older
# Measuring Volumetric Strain from 4D-STEM Data
The aim of this project is to measure the _volumetric strain_ of platinum-cobalt core-shell nanoparticles using 4D-STEM. Unlike previous works in 4D-STEM strain mapping, where the nanoparticles are oriented along a low-index crystallographic zone axis, we have here developed an **automated mapping** techique, that uses particle picking techniques to identify particles and measure the volumetric strain.
Mukherjee, Debangshu
committed
All the work here is in Python, performed on a x64 based processor workstation, running Ubuntu Linux 22.04. However, none of the packages here have Linux as a dependency, so this should run in Windows/Mac environments too -- just the path commands may be a bit different.
Create a separate environment, for the project, and then run in the folder:
Mukherjee, Debangshu
committed
pip install -e .
This will install the package as `proclib`, which is the package that all the codes are.
And that's all you need to run all the notebooks and codes, as everything else is self-contained.
The codes themselves are in the _src_ directory, following the modern toml convention as the _proclib_ folder.
All the data in this project is organized into the following subfolders, inside the _data_ folder:
* _Binned_Data_: This is the experimental data folder, where the naming convention is `062_0nn_binX.npy` or `062_0nn_binX.zarr`, where `nn` is the dataset number, and `X` is the binning factor. If the bin factor is 1, this means that the data is unbinned.
* _GeneratedFigures_: .pdf and .png files for the figures, which are used in the manuscript.
* _Processed_Data_: For the individual processed data, this is in the format of `062_0nn.npy`, where `nn` is the dataset number.
* _SimultaneousADF_: .tif and .jpg files for the simultaneously collected ADF-STEM data, while collecting the 4D-STEM data. We use this data for particle picking.
All the processing in this paper was done on Jupyter notebooks, which are stored in the _notebooks_ folder. The processing notebooks for the data. The subfolder `Single_Particle` has the analysis notebooks for the single particle datasets.