A Fast Algorithm for Scanning Transmission Electron Microscopy (STEM) Imaging and 4D-STEM Diffraction Simulations

TL;DR

This paper introduces a novel partitioned PRISM algorithm for faster and more memory-efficient STEM simulations, especially beneficial for large 4D-STEM fields, enhancing the capabilities of electron scattering studies.

Contribution

The paper presents a new partitioning method for the PRISM algorithm that improves simulation speed and reduces memory usage for large-scale STEM and 4D-STEM simulations.

Findings

Partitioned PRISM significantly reduces computation time.

The method requires less computer RAM.

Effective for large 4D-STEM field simulations.

Abstract

Scanning transmission electron microscopy (STEM) is an extremely versatile method for studying materials on the atomic scale. Many STEM experiments are supported or validated with electron scattering simulations. However, using the conventional multislice algorithm to perform these simulations can require extremely large calculation times, particularly for experiments with millions of probe positions as each probe position must be simulated independently. Recently, the PRISM algorithm was developed to reduce calculation times for large STEM simulations. Here, we introduce a new method for STEM simulation: partitioning of the STEM probe into "beamlets," given by a natural neighbor interpolation of the parent beams. This idea is compatible with PRISM simulations and can lead to even larger improvements in simulation time, as well requiring significantly less computer RAM. We have performed various simulations to demonstrate the advantages and disadvantages of partitioned PRISM STEM simulations. We find that this new algorithm is particularly useful for 4D-STEM simulations of large fields of view. We also provide a reference implementation of the multislice, PRISM and partitioned PRISM algorithms.