STATSTEM is an open source user friendly software (Github repository) to quantify scanning transmission electron microscopy (STEM) images by using model based fitting. This provides an accurate and precise way of extracting quantitative information from STEM images. The software is described in this publication: 10.1016/j.ultramic.2016.08.018
– The maximum a posteriori (MAP) probability rule, which has been proposed as an objective, and the quantitative method to detect atom columns and even single atoms from STEM images, have been implemented as an extra plugin in the freely available StatSTEM software. More details can be found in the corresponding publications 10.1103/PhysRevLett.121.056101 and 10.1016/j.ultramic.2019.02.003.
– The hidden Markov model, which can be used to measure atomic scale dynamics of nanoparticles from experimental high-resolution annular dark field STEM images, has been implemented as an extra plugin in the freely available StatSTEM software. More details can be found in the corresponding publications: 10.1016/j.ultramic.2020.113131 and 10.1103/PhysRevLett.124.106105.
MULTEM provides a collection of routines written in C++ with CUDA (Github repository) to perform accurate and fast multislice simulations for different TEM experiments as: HRTEM, STEM, ISTEM, ED, PED, CBED, ADF-TEM, ABF-HC, EFTEM and EELS. The software is developed by Dr. Ivan Lobato and can be found on Github. The software is described these publications: 10.1016/j.ultramic.2015.04.016, 10.1016/j.ultramic.2016.06.003
The Github repository of Thomas Friedrich contains development level contributions to software relevant to the project: https://github.com/ThFriedrich