Since the automation of the electron backscatter diffraction (EBSD) technique, EBSD systems have become commonplace in microscopy facilities within materials science and geology research laboratories around the world. The acceptance of the technique is primarily due to the capability of EBSD to aid the research scientist in understanding the crystallographic aspects of microstructure. There has been considerable interest in using EBSD to quantify strain at the submicron scale. To apply EBSD to the characterization of strain, it is important to understand what is practically possible and the underlying assumptions and limitations. This work reviews the current state of technology in terms of strain analysis using EBSD. First, the effects of both elastic and plastic strain on individual EBSD patterns will be considered. Second, the use of EBSD maps for characterizing plastic strain will be explored. Both the potential of the technique and its limitations will be discussed along with the sensitivity of various calculation and mapping parameters.
Image quality (IQ) maps constructed from electron backscatter diffraction data provide useful visualizations of microstructure. The contrast in these maps arises from a variety of sources, including phase, strain, topography, and grain boundaries. IQ maps constructed using various IQ metrics are compared to identify the most prominent contrast mechanism for each metric. The conventional IQ metric was found to provide the superior grain boundary and strain contrast, whereas an IQ metric based on the average overall intensity of the diffraction patterns was found to provide better topological and phase contrast.
Electron Backscatter Diffraction (EBSD) provides a useful means for characterizing microstructure. However, it can be difficult to obtain index-able diffraction patterns from some samples. This can lead to noisy maps reconstructed from the scan data. Various post-processing methodologies have been developed to improve the scan data generally based on correlating non-indexed or mis-indexed points with the orientations obtained at neighboring points in the scan grid. Two new approaches are introduced (1) a re-scanning approach using local pattern averaging and (2) using the multiple solutions obtained by the triplet indexing method. These methodologies are applied to samples with noise introduced into the patterns artificially and by the operational settings of the EBSD camera. They are also applied to a heavily deformed and a fine-grained sample. In all cases, both techniques provide an improvement in the resulting scan data, the local pattern averaging providing the most improvement of the two. However, the local pattern averaging is most helpful when the noise in the patterns is due to the camera operating conditions as opposed to inherent challenges in the sample itself. A byproduct of this study was insight into the validity of various indexing success rate metrics. A metric based given by the fraction of points with CI values greater than some tolerance value (0.1 in this case) was confirmed to provide an accurate assessment of the indexing success rate.
Electron Backscatter Diffraction (EBSD) has proven to be a useful tool for characterizing the crystallographic orientation aspects of microstructures at length scales ranging from tens of nanometers to millimeters in the scanning electron microscope (SEM). With the advent of high-speed digital cameras for EBSD use, it has become practical to use the EBSD detector as an imaging device similar to a backscatter (or forward-scatter) detector. Using the EBSD detector in this manner enables images exhibiting topographic, atomic density and orientation contrast to be obtained at rates similar to slow scanning in the conventional SEM manner. The high-speed acquisition is achieved through extreme binning of the camera-enough to result in a 5 × 5 pixel pattern. At such high binning, the captured patterns are not suitable for indexing. However, no indexing is required for using the detector as an imaging device. Rather, a 5 × 5 array of images is formed by essentially using each pixel in the 5 × 5 pixel pattern as an individual scattered electron detector. The images can also be formed at traditional EBSD scanning rates by recording the image data during a scan or can also be formed through post-processing of patterns recorded at each point in the scan. Such images lend themselves to correlative analysis of image data with the usual orientation data provided by and with chemical data obtained simultaneously via X-Ray Energy Dispersive Spectroscopy (XEDS).
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