The DIALS software for the processing of X-ray diffraction data is presented, with an emphasis on how the suite may be used as a toolkit for data processing. The description starts with an overview of the history and intent of the toolkit, usage as an automated system, command-line use, and ultimately how new tools can be written using the API to perform bespoke analysis. Consideration is also made to the application of DIALS to techniques outside of macromolecular X-ray crystallography.

The scanning electron microscopy techniques of electron backscatter diffraction (EBSD), electron channelling contrast imaging (ECCI) and cathodoluminescence (CL) hyperspectral imaging provide complementary information on the structural and luminescence properties of materials rapidly and non-destructively, with a spatial resolution of tens of nanometres. EBSD provides crystal orientation, crystal phase and strain analysis, whilst ECCI is used to determine the planar distribution of extended defects over a large area of a given sample. CL reveals the influence of crystal structure, composition and strain on intrinsic luminescence and/or reveals defect-related luminescence. Dark features are also observed in CL images where carrier recombination at defects is non-radiative. The combination of these techniques is a powerful approach to clarifying the role of crystallography and extended defects on a material’s light emission properties. Here we describe the EBSD, ECCI and CL techniques and illustrate their use for investigating the structural and light emitting properties of UV-emitting nitride semiconductor structures. We discuss our investigations of the type, density and distribution of defects in GaN, AlN and AlGaN thin films and also discuss the determination of the polarity of GaN nanowires.

The diffraction based scanning electron microscopy (SEM) technique of electron channeling contrast imaging (ECCI) provides rapid and non-destructive information on defects on length scales from tens of nanometres to tens of micrometres. ECCI may be complemented by electron backscatter diffraction (EBSD) and hyperspectral cathodoluminescence imaging (CL). EBSD provides orientation, phase, polarity and strain information, whilst CL reveals the influence of phase, composition, strain and defects on luminescence. I will discuss our recent investigations of phase, composition and polarity, the type, density and distribution of defects and the distribution of strain in a range of nitride semiconductor structures.

In this article we describe the scanning electron microscopy (SEM) techniques of electron channelling contrast imaging and electron backscatter diffraction. These techniques provide information on crystal structure, crystal misorientation, grain boundaries, strain and structural defects on length scales from tens of nanometres to tens of micrometres. Here we report on the imaging and analysis of dislocations and sub-grains in nitride semiconductor thin films (GaN and AlN) and tungsten carbide-cobalt (WC-Co) hard metals. Our aim is to illustrate the capability of these techniques for investigating structural defects in the SEM and the benefits of combining these diffraction-based imaging techniques.

Accurate indexing of EBSD patterns presents a challenging problem. We propose a new convolutional neural network (EBSD-CNN) to realize real-time indexing of EBSD patterns; we implement a disorientation loss function to adapt a standard CNN model for crystallographic orientation indexing. The indexing accuracy, rate, and robustness against noise are evaluated using both simulated and experimental data, and compared with other indexing methods (Hough-based indexing, dictionary indexing, and spherical indexing). The results suggest that a CNN can provide an alternative to commercial Hough-transform-based indexing with comparative accuracy and rate. We obtain insight into the network functionality by visualization of selected filters.

Dictionary indexing of electron back-scatter patterns was recently proposed as an alternative to the commercially available indexing packages. In this tutorial paper, we describe in detail the various steps that need to be taken to successfully complete an indexing run on an arbitrary data set. We provide three toy data sets for the reader to experiment with: poly-crystalline nickel with several different acquisition conditions, orthorhombic forsterite, and a single slice from a large serial sectioning experiment on a Ni-based superalloy. The data files and all files produced by the indexing routine are made available as Supplementary Material (https://doi.org/10.1184/R1/7792505).

In this paper we describe the scanning electron microscopy techniques of electron backscatter diffraction, electron channeling contrast imaging, wavelength dispersive X-ray spectroscopy, and cathodoluminescence hyperspectral imaging. We present our recent results on the use of these non-destructive techniques to obtain information on the topography, crystal misorientation, defect distributions, composition, doping, and light emission from a range of UV-emitting nitride semiconductor structures. We aim to illustrate the developing capability of each of these techniques for understanding the properties of UV-emitting nitride semiconductors, and the benefits were appropriate, in combining the techniques.

Dislocation contrast in the SEM, as observed though electron channelling contrast imaging (ECCI), is commonly treated analogously to the contrast in the TEM. This perception is based on early studies done for dislocations parallel with the surface where the surface relaxation is negligible. However, for threading dislocations (TD) that interact with the surface (normal or inclined), as is the case for nitrides materials, g b type invisibility criteria are no longer fully applicable to ECCI, especially in forward geometry [1]. Dislocations change locally the lattice curvature and Bragg diffraction conditions in the crystal, affecting the form and diffracting behaviour of the electron wavefunction in that region. More explicitly, Howie and Whelan [2] had shown that dislocation contrast is the result of interband transitions between Bloch waves states which, in turn, are caused by the change in the displacement field, u(r), around the dislocation or local “strain”. Dynamical models have been used successfully to both predict and characterise dislocations in ECCI [3]. Nevertheless, the behaviour of dislocation contrast in ECCI in particular and diffraction contrast in the SEM in general remains somewhat opaque. In the work we investigate the behaviour of contrast causing strain as a means of insight into this problem.

The forward scattering geometry in the scanning electron microscope enables the acquisition of electron channelling contrast imaging (ECCI) micrographs. These images contain diffraction information from the beam of electrons "channelling in" to the sample. Since small, localised strains strongly affect the electron diffraction, defects which introduce lattice displacement in the region of the surface the electron beam is interacting with will be revealed as distinct variation in backscattered electron intensity. By acquiring multiple images from the same area in different diffraction conditions and comparing them against modelled predictions of defect strain sampled by diffraction, it is possible to characterise these defects. Here we discuss the relation between the elastic strain introduced by a threading dislocation intersecting the surface and the contrast features observed in the electron channelling contrast image of that region. Preliminary simulated channelling contrast images are shown for dislocations with known line direction and Burgers vectors using a two-beam dynamical diffraction model. These are demonstrated to be in qualitative agreement with measured images of dislocated polar wurtzite GaN acquired with two different diffraction conditions. (C) 2017 The Authors. Published by Elsevier Ltd.

Transmission Kikuchi diffraction (TKD) has been gaining momentum as a high resolution alternative to electron back-scattered diffraction (EBSD), adding to the existing electron diffraction modalities in the scanning electron microscope (SEM). The image simulation of any of these measurement techniques requires an energy dependent diffraction model for which, in turn, knowledge of electron energies and diffraction distances distributions is required. We identify the sample-detector geometry and the effect of inelastic events on the diffracting electron beam as the important factors to be considered when predicting these distributions. However, tractable models taking into account inelastic scattering explicitly are lacking. In this study, we expand the Monte Carlo (MC) energy-weighting dynamical simulations models used for EBSD [1] and ECP [2] to the TKD case. We show that the foil thickness in TKD can be used as a means of energy filtering and compare band sharpness in the different modalities. The current model is shown to correctly predict TKD patterns and, through the dictionary indexing approach, to produce higher quality indexed TKD maps than conventional Hough transform approach, especially close to grain boundaries.

Journal Article Dynamical Simulations of Transmission Kikuchi Diffraction (TKD) Patterns Get access Elena Pascal, Elena Pascal Dept. of Physics, SUPA, University of Strathclyde, Glasgow, G4 0NG, UK Search for other works by this author on: Oxford Academic Google Scholar Saransh Singh, Saransh Singh Dept. of Materials Science and Engineering, Carnegie Mellon Univ., Pittsburgh PA 15213, USA Search for other works by this author on: Oxford Academic Google Scholar Ben Hourahine, Ben Hourahine Dept. of Physics, SUPA, University of Strathclyde, Glasgow, G4 0NG, UK Search for other works by this author on: Oxford Academic Google Scholar Carol Trager-Cowan, Carol Trager-Cowan Dept. of Physics, SUPA, University of Strathclyde, Glasgow, G4 0NG, UK Search for other works by this author on: Oxford Academic Google Scholar Marc De Graef Marc De Graef Dept. of Materials Science and Engineering, Carnegie Mellon Univ., Pittsburgh PA 15213, USA Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 23, Issue S1, 1 July 2017, Pages 540–541, https://doi.org/10.1017/S1431927617003385 Published: 04 August 2017