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List of Contributors. 1. The Development of Automated Diffraction in Scanning and Transmission Electron Microscopy D.J. Dingley. 2. Theoretical Framework for Electron Backscatter Diffraction V. Randle. 3. Representation of Texture in Orientation Space K. Rajan. 4. Rodriques-Frank Representations of Crystallographic Texture K. Rajan. 5. Fundamentals of Automated EBSD S.I. Wright. 6. Studies on the Accuracy of Electron Backscatter Diffraction Measurements M.C. Demirel, B.S. El-Dasher, B.L. Adams, A.D. Rollett. 7. Phase Identification Using Electron Backscatter Diffraction in the Scanning Electron Microscope J.R. Michael. 8. Three-Dimensional Orientation Imaging D.J. Jensen. 9. Automated Electron Backscatter Diffraction: Present State and Prospects R.A. Schwarzer. 10. EBSD: Buying a Systems A. Eades. 11. Hardware and Software Optimization for Orientation Mapping and Phase Identification P.P. Camus. 12. An Automated EBSD Acquisition and Processing System P. Rolland, K.G. Dicks. 13. Advanced Software Capabilities for Automated EBSD S.I. Wright, D.P. Field, D.J. Dingley. 14. Strategies for Analysis of EBSD Datasets W.E. King, J.S. Stolken, M. Kumar, A.J. Schwartz. 15. Structure-Property Relations: EBSD-Based Materials-Sensitive Design B.L. Adams, B.L. Henrie, L.L. Howell, R.J. Balling. 16. Use of EBSD Data in Mesoscale Numerical Analyses R. Becker, H. Weiland. 17. Characterization of Deformed Microstructures D.P. Field, H. Weiland. 18. Anisotropic Plasticity Modeling Incorporating EBSD Characterization of Tantalum and Zirconium J.F. Bingert, G.C. Kaschner, T.A. Mason, P.J. Maudlin, G.T. Gray III. 19. Measuring Strains Using Electron Backscatter Diffraction A.J. Wilkinson. 20. Mapping Residual Plastic Strain in Materials Using Electron Backscatter Diffraction E.M. Lehockey, Yang-Pi Lin, O.E. Lepik. 21.EBSD Contra TEM Characterization of a Deformed Aluminum Single Crystal Xiaoxu Huang, D.J. Jensen. 22. Continuous Recrystallization and Grain Boundaries in a Superplastic Aluminum Alloy T.R. McNelley. 23. Analysis of Facets and Other Surfaces Using Electron Backscatter Diffraction V. Randle. 24. EBSD of Ceramic Materials J.K. Farrer, J.R. Michael, C.B. Carter. 25. Grain Boundary Character Based Design of Polycrystalline High Temperature Superconducting Wires A. Goyal. Index.

Most current scanning electron microscopes (SEMs) have the ability to analyze samples in a low vacuum mode, whereby a partial pressure of water vapor is introduced into the SEM chamber, allowing the characterization of nonconductive samples without any special preparation. Although the presence of water vapor in the chamber degrades electron backscatter diffraction (EBSD) patterns, the potential of this setup for EBSD characterization of nonconductive samples is immense. In this chapter we discuss the requirements, advantages and limitations of low vacuum EBSD (LV-EBSD), and present how this technique can be applied to a two-phase ceramic composite as well as hydrated biominerals as specific examples of when LV-EBSD can be invaluable.

Electron backscatter diffraction (EBSD), when employed as an additional characterization technique to a scanning electron microscope (SEM), enables individual grain orientations, local texture, point-to-point orientation correlations, and phase identification and distributions to be determined routinely on the surfaces of bulk polycrystals. The application has experienced rapid acceptance in metallurgical, materials, and geophysical laboratories within the past decade (Schwartz et al. 2000) due to the wide availability of SEMs, the ease of sample preparation from the bulk, the high speed of data acquisition, and the access to complementary information about the microstructure on a submicron scale. From the same specimen area, surface structure and morphology of the microstructure are characterized in great detail by the relief and orientation contrast in secondary and backscatter electron images, element distributions are accessed by energy dispersive spectroscopy (EDS), wavelength dispersive spectroscopy (WDS), or cathodoluminescence analysis, and the orientations of single grains and phases can now be determined, as a complement, by EBSD.

Automated orientation measurement on a local basis is now widely accepted for characterization of materials. The technique relies upon indexing of electron backscatter diffraction patterns in a scanning electron microscope. In order to exploit the available information, it is important to understand the limitations with respect to accuracy. Experiments were carried out to measure orientation fields from a silicon single crystal. The orientation dispersion was 1°. Disorientation correlation maps revealed anisotropy in the spatial variation in measured orientation.

Electron backscatter diffraction (EBSD), or more precisely backscatter Kikuchi diffraction (BKD), in the SEM enables individual grain orientations, local texture and point-to-point orientation correlations to be determined routinely on bulk surfaces of polycrystalline materials. The technique has found rapid acceptance in materials science within the last few years (Randle, 1992; Schwarzer, 1997a) due to the wide availability of SEMs, the ease of sample preparation from the bulk, and the access to complementary information about the microstructure on a submicron scale. The combination of several easy-to-use techniques makes the SEM a powerful and almost universal analytical instrument in the hands of the physical metallurgist as well as the earth scientist. From the same specimen area, surface configuration and morphology of micro structure are perceived in great detail by the relief and orientation contrast in secondary and backscatter electron images, element distributions are accessed by EDS or cathodoluminescence analysis, and the orientations of single grains and phases can now be determined, as a complement, by EBSD.

The ability to obtain microstructure-level orientation information, known generically as microtexture, requires that the probe size available from the exploring radiation must be smaller than the size of the microstructural units themselves. Electrons are ideal for such combined microstructural/crystallographic studies and indeed until the 1980s transmission electron microscopy (TEM) was the major technique used for such work, with some input from selected area channeling in a scanning electron microscope (SEM) and from Laue x-ray diffraction. Since that time an enhanced SEM-based technique for microtexture has been develop and is known as electron backscatter diffraction or EBSD (Venables and Harland, 1973; Dingley, 1984). EBSD is now the cornerstone of almost all microtexture research, and is also used for phase identification and strain measurement. EBSD or, as it is equivalently known, backscatter Kikuchi diffraction, BKD, is an add-on package to an SEM. The most attractive feature of the technique is its unique capability to perform concurrently rapid, (usually) automatic diffraction analysis to give crystallographic data and imaging with a spatial resolution of less than 0.5 iim, combined with the regular capabilities of an SEM such as capacity for large specimens, option of simultaneous chemical analysis, and the ability to image rough surfaces. The new generation of field emission gun SEMs (FEGSEM) offer much better resolution that now challenges that available by TEM.

The identification of unknown micrometer-sized phases in the scanning electron microscope (SEM) has been limited by the lack of a robust and simple way to obtain crystallographic information about the unknown while observing the microstructure or morphology of the specimen. Electron backscatter diffraction (EBSD) is a technique that can provide identification of unknown crystalline phases while exploiting the excellent imaging capabilities of the SEM. Previous to the development of EBSD for phase identification, the only applicable technique for the identification of micrometer-sized phases was electron diffraction in the transmission electron microscope (TEM). Convergent beam and selected area electron diffraction (CBED and SAED) can provide information from submicrometer sized phases, but require the preparation of electron transparent samples that is very difficult and time intensive. Phase identification using EBSD is a complementary technique to TEM methods.

The electron backscatter diffraction (EBSD) technique has undergone significant development in recent years. The technique is most widely used for crystal orientation measurement, however, it also provides a powerful tool for phase discrimination (identification) and strain analysis. This chapter reviews the application of EBSD to the analysis of local strains (plastic and elastic) in materials.

Residual strains that accrue from stresses imposed on materials during manufacturing, installation, and service often enhance the susceptibility to degenerative effects such as corrosion, cracking, and fatigue. Mapping strains in Alloy 600, a Ni-base non-age hardenable alloy, Steam Generator (SG) tubing used in boiler systems of CANadian Deuterium Uranium (CANDU) reactors is of particular interest to the nuclear industry. Interactions between residual strains from roller-expansion of the tubing during installation with prevailing environmental conditions during reactor operation (e.g., water chemistry and temperature) contribute to initiation and propagation of stress corrosion cracks (SCC), which can influence boiler reliability and service-life (Danko, 1996). Therefore, having a means of accurately characterizing the magnitude and spatial distribution of plastic deformation in relation to material defects including cracks, pits, and dents, is essential for identifying components at high risk of failure. Hardness measurements have traditionally been used to identify regions of high strain in SG tubes. However, obtaining a sufficient number of such measurements to infer details regarding the spatial distribution of complex strain fields is tedious and often impractical. Moreover, in so far as hardness indentations locally alter the strain distribution, these methods can be considered destructive.

A facet is defined as ‘one side of a many-sided body.’ With regard to grains in a polycrystal, a facet can be an intergranular or transgranular fracture surface (Field 1997; Randle and Hoile, 1998; Randle, 1999), or the surface of a grain or phase boundary (Randle, 1997). Figure 23.1 shows the appearance of intergranular fracture surfaces in an aluminium alloy revealed as a result of liquid metal embrittlement by gallium. This is, of course, an unusual view of grain boundaries; usually they are revealed by etching a polished surface to show the trace of the grain boundary network. Frequently, fracture surfaces and grain boundaries have very specific crystallographic identities. This is also true of other planar features in materials, such as intergranular or transgranular microcracks, (Liu et al., 1992) or slip traces (Blochwitz et al., 1996; Lin and Pope, 1996; Raabe et al., 1997). It is possible to extend the capabilities of EBSD to obtain the crystallographic indices of these flat surfaces (i.e., planes). Such a strategy is a precursor to a three-dimensional view of microtexture. This chapter gives an overview of the state-of-the-art of EBSD analysis of facets and surfaces.

Developing a quantitative understanding of ultrasonic beam propagation in engineering materials such as Ti-6A1-4V is important because flaw signals can be altered greatly by the macrostructure that the ultrasonic beam propagates through between the transducer and the flaw. Two consequences of the macrostructure are particularly important: 1) back scattered noise which competes with flaw signals and 2) forward scattered signals and the associated beam profile fluctuations which can modulate the strength of flaw signals [1,2,3], These effects are particularly important when ultrasonic beams are used to detect subtle defects such as unvoided, uncracked hard-alpha inclusions (regions with a high content of interstitial nitrogen or oxygen), because the flaw signal is inherently weak due to a small mismatch of acoustic impedance. Each of these effects is controlled by the inherently complex macrostructure which develops during routine processing. Current theories suggest that the most important physical feature which controls noise is the two-point correlation of elastic constants, which is in turn controlled by local variations in crystallographic orientation [4]. Therefore, in order to quantify the effects of the macrostructure on ultrasonic beam propagation, one must determine the elastic constants on a microscopic level with length scales less than the ultrasonic wavelength, approximately 600 μm at 10 MHz.

Silicon carbide is desirable for many nuclear applications, making it necessary to understand how it deforms after irradiation. Ion implantation combined with nanoindentation is commonly used to measure radiation-induced changes to mechanical properties; hardness and modulus can be calculated from load–displacement curves, and fracture toughness can be estimated from surface crack lengths. Further insight into indentation deformation and fracture is required to understand the observed changes to mechanical properties caused by irradiation. This paper investigates indentation deformation using high-resolution electron backscatter diffraction (HR-EBSD) and Raman spectroscopy. Significant differences exist after irradiation: fracture is suppressed by swelling-induced compressive residual stresses, and the plastically deformed region extends further from the indentation. During focused ion beam cross-sectioning, indentation cracks grow, and residual stresses are modified. The results clarify the mechanisms responsible for the modification of apparent hardness and apparent indentation toughness values caused by the compressive residual stresses in ion-implanted specimens. Supplementary Information The online version contains supplementary material available at 10.1007/s11837-021-04636-8.

High-temperature compression tests were performed on a Ni-base superalloy with a multi-phase microstructure. Particular attention was given on the influence of the η phase on recrystallization of ATI 718Plus®. The compression tests were performed at two temperatures over a variety of strains and strain rates. Meta-dynamic recrystallization was studied by exposing the samples to a set dwell time at the test temperature after deformation. Electron backscatter diffraction (EBSD) was used to investigate the microstructures after the tests. Secondary electron imaging (SEI) and scanning transmission electron microscopy (STEM) were utilized in order to investigate the deformation behavior of η and obtaining a detailed understanding of the recrystallization mechanism. The secondary η phase was found to increase the recrystallized fraction compared to η free tests. However, clusters of thin lamellar η inhibited recrystallization. The flow curve softening was distinctly stronger in the microstructure containing precipitates. It could be shown by SE images that this was due to the breakage and realignment of η. In addition, η was also found to accommodate the stresses by a remarkable deformation without breaking up. This was considered to be due to the composite nature of the precipitate as well as the ongoing recrystallization in the surrounding matrix.

In this work, a novel method is presented to track site-specific microstructure evolution in metallic materials deformed biaxially along proportional and complex strain paths. A miniaturized bulge test setup featuring a removable sample holder was designed to enable incremental measurements to be performed in a scanning electron microscope, by probing the same position on the sample at different deformation levels, with electron backscatter diffraction (EBSD), electron channeling contrast imaging (ECCI) and other imaging modes. Validation experiments were performed at room temperature on samples prepared from commercial sheet metal (dual-phase steel) and foils (stainless steel). Local strain measurements with the digital image correlation technique confirmed that proportional strain paths with a strain ratio up to 5 can be investigated using elliptical dies in the bulge test holder. It is also shown how complex strain paths can be obtained using a combination of overlapping elliptical dies. Incremental EBSD and ECCI were conducted in configurations relevant for the multi-scale investigation of localized plasticity and damage mechanisms in dual-phase steel. Quantitative information regarding microstructure evolution (phase fractions, orientation fields, dislocation structures, etc.) and regarding local strain distributions could be successfully obtained. This type of data sheds light on underlying deformation mechanisms and provides opportunities to calibrate crystal plasticity models.

Electron backscatter diffraction (EBSD) has emerged in recent years as a powerful tool for the characterization of micro- or meso-structure by measurements in orientation space. This is evident from the numerous examples of the applications of this technique given in other chapters of this volume. As discussed in the previous chapters, most EBSD acquisition software provide the x- and y-coordinates, the three Euler angles, and a number of other parameters including the quality of the electron backscatter diffraction pattern (EBSP) and the confidence in indexing. Commercially available software contains a myriad of functions to allow the investigator to analyze many aspects of the material micro structure. However, for certain problems in materials science, standard, commercially available software is unable to provide all the information that is required for the analysis. This chapter will explore additional representations of the EBSD dataseis and data processing software that have been developed to address particular problems encountered during investigations. Specific examples include: “clean-up” of dataseis; mapping of lattice rotations in deformed single crystals; three-dimensional reconstruction of the microstructure; and applications in the area of grain boundary engineering such as statistical information on the frequency of grain boundaries in deformed and annealed polycrystals, analysis of triple junction distributions, and mapping of the random grain boundary connectivity in the microstructure.

This introductory chapter traces the development of the automated detection and indexing of electron diffraction patterns in both the scanning and transmission electron microscopes. Though electron backscatter diffraction (EBSD) is the best known of these, the procedures have been extended recently to the transmission electron microscope and a review would not be complete without including this new work.

The term “ceramics” covers a very broad range of materials. By definition, ceramics include all nonmetallic inorganic solids, containing both nonmetallic and metallic constituents; the interatomic bonds thus usually have both ionic and covalent character. The usefulness of ceramics in a wide variety of applications stems from properties such as hardness and resistance to heat, corrosion, and electricity. Ceramics are sometimes divided into two groups known as “traditional ceramics” and “new ceramics” (Kingery et al., 1976). The traditional ceramics include those primarily in the silicate industries (e.g., whitewares) and refractories. The new ceramics include electro-optic ceramics, magnetic ceramics, single crystals used for thin-film substrates, those used in the nuclear industry, and pure oxide ceramics to name a few (Kingery et al., 1976). The study of ceramics using electron backscatter diffraction (EBSD) has not yet extended into all of these areas of ceramics. However, EBSD research of certain ceramics has received considerable attention, and this will be the focus of this review.

This chapter focuses on the automated determination of crystallographic orientation from electron backscatter diffraction (EBSD) patterns. Early systems required an operator skilled in crystallography to manually identify features in a captured pattern in order to determine the corresponding orientation. The computer would then determine the orientation from the manually supplied data. Modern automated systems use image-processing techniques to identify the features needed to determine the crystallographic orientation from diffraction patterns without any operator intervention. This chapter describes the different procedures used in achieving automated EBSD. Image processing techniques used to enhance the diffraction patterns will be briefly described; the manual zone axis indexing technique will be discussed for historical introduction; a description of the procedure for detecting the diffraction bands with a focus on the Hough transform will be given; methods for determining orientation using diffraction bands will be detailed; issues concerning automated indexing uncertainties will be discussed; a description of the relevant structural data needed by the computer to index the patterns will be given and finally methods for calibrating a system will described. Whereas this chapter will briefly introduce alternative approaches and give some reference material where applicable, the focus will be on those techniques most familiar to the author.

Venables (1973) coined the term electron backscatter diffraction (EBSD) to describe backscatter Kikuchi diffraction in the scanning electron microscope (SEM). The first commercial system was produced by Moon and Harris of Custom Camera Designs in 1984 and was an outgrowth of the system designed by Dingley at the University of Bristol. This design was later provided to both Oxford Instruments and Ris0 National Laboratory out of which the OPAL™ and HKL™ systems evolved. The first fully automated EBSD system capable of automatic indexing of EBSD patterns and subsequent mapping of the spatial distribution of crystallographic orientation was introduced by Wright (1992). The term Orientation Imaging Microscopy or OIM™ was coined to describe this automated technique for forming images by mapping orientation data obtained from automated EBSD (Adams et al., 1993). Dingley and Adams co-founded TSL (or TexSEM Laboratories) in 1994 to produce the first commercial automated EBSD system based on the system developed by the group at Yale University (Adams, Wright, and Kunze). TSL adopted the name OIM™ for its automated EBSD products. Much of what was included in the original TSL system has become a standard for modern EBSD systems.

In the three articles that follow, manufacturers of commercial electron backscatter diffraction (EBSD) units describe aspects of their systems. These articles provide a snapshot of the state-of-the-art hardware and software capabilities at the beginning of the year 2000. However, things are changing very rapidly in this new and exciting field. EBSD is very important. It will revolutionize scanning electron microscopy for all applications that involve crystalline material. More than that, EBSD will have a major impact on other fields. Many characterization experiments that would have been done using other techniques will now be done, and done better, using EBSD on the scanning electron microscope (SEM).

Electron backscatter diffraction (EBSD) as a technique has achieved a great deal of usage with the apparent ease by which one can associate grain specific diffraction information from a polycrystalline sample. This enabled a coupling of microstructural features within the diffraction based resolution volume of the electron beam with the local or microtexture characteristics. The development of the experimental technique of EBSD has been aided by image processing tools and automation techniques that has been significant in the establishment of orientation mapping. Using electron beam based diffraction techniques offers a distinct advantage over x-ray diffraction techniques in many cases. For example, one may be interested in characterizing texture gradients over small regions of the microstructure below the spatial resolution of x-ray diffraction techniques; or the sample dimension may be too small (such as thin films and nanostructures) to even contain many grains. Yet, while the issues of local texture are still important to assess and interpret in these cases, and while EBSD may provide an experimental means of obtaining texture information, the predominant means of representing texture is still through orientation space as discussed in the last chapter.

Three-dimensional (3D) characterization methods are required to completely determine microstructural descriptors such as the true shape and size of features, the number of features, and the connectivity between these features. Experimental methods to characterize microstructure in 3D have undergone dramatic improvements in the past decade, and there now exists a host of methodologies that are capable of determining 3D microstructural information, ranging from counting individual atoms to imaging macro-scale volumes. The state of the art for this field has been reviewed recently in a Viewpoint Set for Scripta Materialia (Spanos 2006). This chapter focuses on the specific topic of experimental interrogation and analysis of microstructural features such as grains or precipitates in 3D that includes crystallographic orientation data. Currently there are two main experimental pathways to collect such information. Serial sectioning experiments are more commonplace, but consume the sample as part of the experiment; while X-ray methods are nondestructive, but typically require the use of high-intensity X-ray sources. For the X-ray methods, there are a handful of groups world-wide that are working towards spatially-resolved crystallographic analyses of grain structures in 3D using high-intensity X-ray systems (Schmidt et al. 2004; Lauridsen et al. 2006; Budai et al. 2004, 2008; Lienert et al. 2007). These meth

When we discussed the variation of observable symmetry according to the nature of the examining probe, Sect. 1.4, we stated that one possible probe is a neutron beam. As an example, when the structure of elemental chromium is examined by X-ray diffraction, it shows a body-centered cubic arrangement, Fig. 11.1a. Elemental chromium has the electronic configuration (Ar 3d5 4s1); it is antiferromagnetic at room temperature, and its electron spins, arising from the unpaired electrons, give rise to the magnetic structure shown in Fig. 11.1b. The magnetic moment of the neutron interacts with the permanent dipole of chromium to form this structure, and consequently the diffraction record shows a primitive cubic structure.

Experimentation, theory, and modeling have all played vital roles in defining what is known about microstructural evolution and the effects of microstructure on material properties. Recently, technology has become an enabling factor, allowing significant advances to be made on several fronts. Experimental evidence of crystallographic slip and the basic theory of crystal plasticity were established in the early 20th century (Polanyi, 1922; Schmid, 1924; Taylor and Elam, 1925), and the theory and models evolved incrementally over the next 60 years (Taylor, 1938; Bishop and Hill, 1951; Hutchinson, 1964; Hill and Rice, 1972; Honneff and Mecking, 1978; Asaro, 1983a; Kocks et al., 1986). During this time, modeling was primarily concerned with the average response of polycrystalline aggregates. While some detailed finite element modeling (FEM) with crystal plasticity constitutive relations was performed in the early 1980’s (Peirce et al., 1982, 1983), such simulations over taxed the capacity of the available computer hardware. Advances in computer capabilities led to a flurry of activity in finite element modeling in the next 10 years (Harren et al., 1988; Havileck et al., 1990; Zikry and Nemat-Nasser, 1990; Becker et al., 1991; Kalidindi et al., 1992; Beaudoin et al., 1993; Saeedvafa and Rice, 1992; Mohan et al., 1992), thus increasing understanding of lattice orientation evolution and generating detailed predictions of spatial orientation distributions that could not be readily validated with existing experimental characterization methods.

Automated EBSD, also known as Orientation Imaging Microscopy (OIM™) (Adams et al., 1993), provides data on those aspects of the internal structure of polycrystalline materials that are described by the idealized aggregate function G(x) (Bunge, 1998): $$ G(x) = \left\{ {\phi (x),g(x)} \right\} $$ where Φ(x) and g(x) denote the crystal phase and orientation at position x within the material. G(x), it should be noted, does not directly describe the geometrical character of grain boundaries or interfaces, except in the sense that upon examining a finite neighborhood about any selected point, lying sufficiently close to an interface, from G(x) one can recover the five-parameter macroscopic description of the interface. (For simplicity, the discussion here will concern single-phase polycrystals where Φ(x) is constant.)

The application of automated EBSD techniques in the context of an overall predictive materials modeling effort incorporating anisotropic properties for tantalum and zirconium is covered in this chapter. The focus will be on the role of microtextural investigations as an integral tool supporting the development and validation of material models that incorporate anisotropic constitutive behavior. Continuum mechanics codes require accurate descriptions of materials behavior to adequately predict large-strain deformation response. The corresponding requirement of characterizing micro structure s after significant deformation places severe requirements on the EBSD system. In this work, a Philips XL30 SEM employing a warm Schottky FEG was used for all data collection; the combination of high resolution with adequate beam current was a necessity for analyzing fine detail amid heavily worked structures. The ability to spatially resolve orientation differences on the order of 100 nm is achievable. All EBSD data collection and analysis was performed with TSL’s OIM™ software, while the popLA code (Kallend et al., 1991) was used for x-ray texture analysis.

In recent years the development has been toward more and more microstructural characterization being done by automatic EBSD* measurements at the expense of TEM studies. This trend has been expressed very directly by Professor F.J. Humphreys: “Although I used to be a TEM-man, I now do everything I can to avoid doing TEM work” (Humphreys, 1999a). Reasons for this trend are the advances of the EBSD technique toward faster and easier measurements, more sophisticated data representations and (very importantly) better spatial resolution of the technique. In modern FEG-SEMs the spatial resolution is estimated to be three times better than in conventional W-filament SEMs (Humphreys, 1999b) and subgrain structures of dimensions down to 0.2 µm in aluminum are analyzed (Humphreys, 1999b). This means that characterization previously done by TEM is now being done by EBSD (Humphreys, 1999b; Terhune et al., 1999).

An automated EBSD system is a combination of hardware and software designed to operate in harmony. The hardware combines pattern acquisition using a specialized camera and electron image acquisition from the SEM. The software controls data acquisition and processing. The standard SEM image may be used as a reference image, or better, that produced by a dedicated forward scattered electron detector. Examples of the use of the camera, image and EBSD data are given to illustrate the Oxford Instruments EBSD system capabilities.

This chapter will set the stage for our discussion of imaging using diffraction contrast. Put simply, diffraction contrast arises because the intensity of the diffr3acted beams is different in different regions of the specimen. These variations may arise because of changing diffracting conditions or because of differences in specimen thickness. In our study of diffraction in the TEM, we will see spots—lots of them. Sometimes the ‘spots’ will be small faint points and other times they will be large disks, which themselves contain ‘structure’ and more information. Other patterns will contain lines that we will examine in Chapters 19–21.

The electron is a low mass, negatively charged particle. As such, it can easily be deflected by passing close to other electrons or the positive nucleus of an atom. These Coulomb (electrostatic) interactions cause the electron scattering which is the process that makes TEM feasible. We will also discuss how the wave nature of the electron gives rise to diffraction effects. What we can already say is that if the electrons didn’t scatter, then there would be no mechanism to create TEM images or diffraction patterns and no source of spectroscopic data. So it is essential to understand both the particle approach and the wave approach to electron scattering in order to be able to interpret all the information that comes from a TEM. Electron scattering from materials is a reasonably complex area of physics, but it isn’t necessary to develop a detailed comprehension of scattering theory to be a competent microscopist.

The dual beam incorporates both a focused ion beam (FIB) and a scanning electron microscope (SEM) in a single system. This combination offers several advantages over a single-beam FIB system, especially for sample preparation and microscopy applications, in which the ion beam can be used for site-specific material removal and the SEM for nondestructive imaging and analysis. Dual-beam system configurations are presented, along with a number of key techniques and applications. These include precision cross-sectioning, TEM sample preparation, and automated 3D process control.

X-rays are high-energy electromagnetic radiation. They have energies ranging from about 200 eV to 1 MeV, which puts them between γ-rays and ultraviolet (UV) radiation in the electromagnetic spectrum. It is important to realize that there are no sharp boundaries between different regions of the electromagnetic spectrum and that the assigned boundaries between regions are arbitrary.

The contribution of X-ray diffraction to conventional structural chemistry has been large. Much of our information about molecular geometry has come from this source, especially through its application to single crystals. As simple molecules become condensed into long chains, however, the resulting macromolecules rarely form good single crystals, and so the study of polymers by X rays involves mainly the study of fibres, or isotropic materials that are at best only partly crystalline, and are often totally amorphous. Less conventional mathematical formulae become involved in data analyses, and the information about structure becomes necessarily more limited and statistical. Despite this, however, the application of X-ray methods to polymeric materials is well established,1–3 and is a sophisticated, and highly productive, activity.

Over 600 surface structures have been determined during the 20 years before 1991 in terms of interlayer relaxations, bond lengths, bond angles and adsorption sites1,2. Over half of these were analyzed by low-energy electron diffraction (LEED), the oldest technique in this field. Compared to other techniques of surface structure determination, LEED gives the largest flexibility of application, being suitable for most materials (metals, semiconductors, intermetallic or ionic compounds, with or without atomic or molecular adsorbates of arbitrary kind, etc.) and most structural types (reconstructed or not, with adsorption as an overlayer or an underlayer, ordered or disordered, in submonolayer or multilayer amounts, etc.). This success results from the fact that the basic physics of the LEED process are well understood and have been harnessed to accurately reproduce experimental data3-5.

A knowledge of the atomic identities, positions, and bonding mechanisms within the first 3–5 layers of a surface is essential to any quantitative microscopic understanding of surface phenomena. This implies knowing bond directions, bond distances, site symmetries, coordination numbers, and the degree of both short-range and long-range order present in this selvedge region. A number of surface-structure probes have thus been developed in recent years in an attempt to provide this information.1 Each of these methods has certain unique advantages and disadvantages, and they are often complementary to one another.

This volume contains the papers presented at the NATO Advanced Research Workshop in "Reflection High Energy Electron Diffraction and Reflection Electron Imaging of Surfaces" held at the Koningshof conference center, Veldhoven, the Netherlands, June 15-19, 1987. The main topics of the workshop, Reflection High Energy Electron Diffraction (RHEED) and Reflection Electron Microscopy (REM), have a common basis in the diffraction processes which high energy electrons undergo when they interact with solid surfaces at grazing angles. However, while REM is a new technique developed on the basis of recent advances in transmission electron microscopy, RHEED is an old method in surface crystallography going back to the discovery of electron diffraction in 1927 by Davisson and Germer. Until the development of ultra high vacuum techniques in the 1960's made instruments using slow electrons more accessable, RHEED was the dominating electron diffraction technique. Since then and until recently the method of Low Energy Electron Diffraction (LEED) largely surpassed RHEED in popularity in surface studies. The two methods are closely related of course, each with its own specific advantages. The grazing angle geometry of RHEED has now become a very useful feature because this makes it ideally suited for combination with the thin growth technique of Molecular Beam Epitaxy (MBE). This combination allows in-situ studies of freshly grown and even growing surfaces, opening up new areas of research of both fundamental and technological importance.