A Practical Guide to Scanning and Transmission Electron Microscopy Simulations

Abstract

Transmission electron microscopy (TEM) is one of the most powerful tools for characterizing a wide variety of materials. Rapid developments in instrumentation are allowing additional information to be gleaned from advanced imaging techniques and bringing many new people into the field. At the same time, open-source code has become an indispensable tool for research and teaching, and as in many other fields, the Python programming language has become the standard choice for TEM practitioners. Although traditional textbooks continue to play an important role in training the next geneeration of TEM researchers, these concurrent developments in computing are enabling new kinds of educational resources. In this work, we provide a practical and self-contained guide to scanning and transmission electron microscopy image simulations, giving learners a theoretical basis from which to develop an intuitive appreciation of how different imaging modalities work and how the choice of parameters affect the resulting images. Our interactive examples are based on fully open-source software packages, most notably the abTEM code that is becoming the standard in the field, with all the code provided alongside the article. Our aim is to help both newcomers and more experienced microscopists who may not yet be familiar with simulations to build understanding towards making image simulations a routine part of their learning and research.

Keywords:Transmission electron microscopyScanning transmission electron microscopyMultislice simulationsOpen source

Declaration of Competing Interest

The authors declare that they have no known competing interests.

Acknowledgments

We are heavily indebted to the various excellent textbooks on electron microscopy, in particular Advanced Computing in Electron Microscopy by Earl Kirkland. Work at the Molecular Foundry was supported by the Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, and at the University of Vienna by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 756277-ATMEN).

References
  1. Kirkland, E. J. (2020). Advanced Computing in Electron Microscopy. Springer International Publishing. 10.1007/978-3-030-33260-0