STEMcl–A multi-GPU multislice algorithm for simulation of large structure and imaging parameter series

Radek Manuel, Tenberge Jan-Gerd, Hilke Sven, Wilde Gerhard, Peterlechner Martin

Research article (journal) | Peer reviewed

Abstract

Electron microscopy images are interference patterns and can generally not be interpreted in a straight forward manner. Typically, time consuming numerical simulations have to be employed to separate spec- imen features from imaging artifacts. Directly comparing numerical predictions to experimental results, realistic simulation box sizes and varying imaging parameters are needed. In this work, we introduce an accelerated multislice algorithm, named STEMcl , that is capable of simulating series of large super cells typical for defective and amorphous systems, in addition to parameter series using the massive par- allelization accessible in today's commercial PC-hardware, e.g. graphics processing units (GPUs). A new numerical approach is used to overcome the memory constraint limiting the maximum computable sys- tem size. This approach creates the possibility to study systematically the contrast formation arising by structural differences. STEM simulations of structure series of a crystalline Si and an amorphous CuZr system are presented and the contrast formation of vacancies/voids are studied. The detectability of va- cancies/voids in STEM experiments is discussed in terms of density changes.

Details about the publication

JournalUltramicroscopy
Volume188
Page range24-30
StatusPublished
Release year2018 (16/02/2018)
Language in which the publication is writtenEnglish
DOI10.1016/j.ultramic.2018.02.004
KeywordsSTEM; image simulation; multislice; Si; CuZr

Authors from the University of Münster

Hilke, Sven
Institute of Materials Physics
Peterlechner, Martin
Professorship of Materials Physics (Prof. Wilde)
Radek, Manuel
Institute of Materials Physics
Tenberge, Jan-Gerd
Department for Neurology
Wilde, Gerhard
Professorship of Materials Physics (Prof. Wilde)