Paterson Gary W, Webster Robert W H, Ross Andrew, Paton Kirsty A, Macgregor Thomas A, McGrouther Damien, MacLaren Ian, Nord Magnus
SUPA, School of Physics and Astronomy, University of Glasgow, GlasgowG12 8QQ, UK.
EMAT, Department of Physics, University of Antwerp, Antwerp2000, Belgium.
Microsc Microanal. 2020 Oct;26(5):944-963. doi: 10.1017/S1431927620024307.
Fast pixelated detectors incorporating direct electron detection (DED) technology are increasingly being regarded as universal detectors for scanning transmission electron microscopy (STEM), capable of imaging under multiple modes of operation. However, several issues remain around the post-acquisition processing and visualization of the often very large multidimensional STEM datasets produced by them. We discuss these issues and present open source software libraries to enable efficient processing and visualization of such datasets. Throughout, we provide examples of the analysis methodologies presented, utilizing data from a 256 × 256 pixel Medipix3 hybrid DED detector, with a particular focus on the STEM characterization of the structural properties of materials. These include the techniques of virtual detector imaging; higher-order Laue zone analysis; nanobeam electron diffraction; and scanning precession electron diffraction. In the latter, we demonstrate a nanoscale lattice parameter mapping with a fractional precision ≤6 × 10−4 (0.06%).
采用直接电子检测（DED）技术的快速像素化探测器越来越被视为扫描透射电子显微镜（STEM）的通用探测器，能够在多种操作模式下成像。然而，对于它们所产生的通常非常大的多维STEM数据集，在采集后处理和可视化方面仍存在一些问题。我们讨论这些问题，并展示开源软件库，以实现对此类数据集的高效处理和可视化。在整个过程中，我们提供了所介绍分析方法的示例，使用来自256×256像素的Medipix3混合DED探测器的数据，特别关注材料结构特性的STEM表征。这些技术包括虚拟探测器成像；高阶劳厄区分析；纳米束电子衍射；以及扫描进动电子衍射。在后者中，我们展示了分数精度≤6×10−4（0.06%）的纳米级晶格参数映射。
