Pixelated
STEM
detectors: opportunities and challenges
Authors: MacLaren Ian , Nord Magnus , Ross Andrew , Krajnak Matus , Hart Martin , Doye Alastair , McGrouther Damien , Bali Rantej , Banerjee Archan , Hadfield Robert 
Published: December 2016

Conventionally, imaging in Scanning Transmission Electron Microscopy (STEM) has been performed using annular detectors that integrate up large fractions of the scattered electrons into a single value for each position in a scan, leading to a loss of information. Recently, advances in counting detection have enabled the development of fast 2‐D pixelated detectors, such as the Medipix‐3 detector used in this work. These can be used to collect a large fraction of the scattered electrons in the back focal plane yielding a STEM diffraction pattern (Fig. 1a) for every scan position. The end result is a 4‐D dataset, with two spatial sample positions and two reciprocal detector positions. This diffraction pattern contains a wealth of information, and being able acquire them at Ångström spatial resolutions enables many exciting applications, however there are many challenges in how to use and analyse these large datasets. In this presentation we focus on recent progress at University of Glasgow on pixelated STEM imaging, and how analysing different aspects of the diffraction images can yield information about the material properties.
In standard STEM imaging, one usually gets information about the spatial dimensions orthogonal to the electron beam. By using a pixelated STEM detector, the lattice parameter parallel to the electron beam can also be extracted. This is achieved by looking using the higher order Laue zone rings (arrow in Fig. 1a). When this is combined with conventional atomic resolution STEM images, information of 3‐D crystallography can be determined from just one projection. Examples will be given on how the 3‐D structure of perovskite oxides has been determined.
The magnetic induction of a sample can be imaged in Lorentz mode, where the objective lens is usually turned off. In STEM mode, magnetic induction in the sample causes the electron beam to deflect through a typically small angle, 1‐100μrads, which can be seen as a shift in the bright field disc. This has conventionally been mapped using the Differential Phase Contrast Technique with a split detector (e.g. into quadrants), but this suffers from additional contrast due to diffraction effects which affect intensity distribution within the bright field disc. Pixelated detection allows an improved methodology accurate disc‐shift measurements using edge‐detection of the disc, which separates these disc shifts from diffraction contrast more robustly. The resulting imaged magnetic induction in a patterned FeAl film is shown in Fig. 1b, which visualizes ferromagnetic domains in a nanostructure created using focused ion beam nanopatterning.
Since the 4‐D datasets contain the full diffraction patterns, it is possible to create virtual apertures in post‐processing. This allows the construction of arbitrary shaped “detectors”. Making it possible to get HAADF, MAADF, LAADF, ABF and BF from the same dataset. Such a virtual ADF‐aperture is shown in Fig. 1c, for gold deposited on a carbon film.

We will also describe how this detector can be used to determine ordering in amorphous materials using a fluctuation electron microscopy based method, and Figure 1d shows one diffraction pattern from a series of ∼ 2000 diffraction patterns taken on a thin ∼5 nm film of amorphous MoSi
x
for use in a superconducting nanowire single‐photon detector (SNSPD). The use of the Medipix detector has significant advantages over earlier CCD detectors, due to the absence of electronic detection noise, meaning that the statistics are much cleaner and more interpretable at lower beam doses, and thus higher acquisition rates. The resulting variance plots and conclusions about short‐ and medium‐range ordering in the material will be briefly summarised.

In conclusion, we will demonstrate a range of new and interesting applications for pixelated detectors in STEM, which allow new or improved imaging modes and the improved extraction of information relevant to the understanding of the nanoscale or atomic scale structure of materials, nanostructures and devices.