Three Approaches for Representing the Statistical Uncertainty on Atom-Counting Results in Quantitative ADF STEM

Microsc Microanal. 2022 Sep 19:1-9. doi: 10.1017/S1431927622012284. Online ahead of print.

Abstract

A decade ago, a statistics-based method was introduced to count the number of atoms from annular dark-field scanning transmission electron microscopy (ADF STEM) images. In the past years, this method was successfully applied to nanocrystals of arbitrary shape, size, and composition (and its high accuracy and precision has been demonstrated). However, the counting results obtained from this statistical framework are so far presented without a visualization of the actual uncertainty about this estimate. In this paper, we present three approaches that can be used to represent counting results together with their statistical error, and discuss which approach is most suited for further use based on simulations and an experimental ADF STEM image.

Keywords: model averaging; quantitative electron microscopy; scanning transmission electron microscopy; statistical parameter estimation theory; statistical uncertainty.