Many materials science studies use scanning transmission electron microscopy (STEM) to characterize atomic-scale structure. Conventional STEM imaging experiments produce only a few intensity values at each probe position. However, modern high-speed detectors allow us to measure a full 2D diffraction pattern, over a grid of 2D probe positions, forming a four dimensional (4D)-STEM dataset. These...
We present the development of an open source tool within the Python library pyxem for automated crystal orientation mapping in the scanning transmission electron microscope (STEM). An efficient and flexible template matching algorithm is developed, where simulated electron diffraction patterns are compared to experimental patterns obtained from scanning precession nanobeam electron...
