Automated Electron Backscatter Diffraction (EBSD) has become a well-accepted technique for characterizing the crystallographic orientation aspects of polycrystalline microstructures. At the advent of this technique, it was observed that patterns obtained from grains in certain crystallographic orientations were more difficult for the automated indexing algorithms to accurately identify than patterns from other orientations. The origin of this problem is often similarities between the EBSD pattern of the correct orientation and patterns from other orientations or phases. While practical solutions have been found and implemented, the identification of these problem orientations generally occurs only after running an automated scan, as problem orientations are often readily apparent in the resulting orientation maps. However, such an approach only finds those problem orientations that are present in the scan area. It would be advantageous to identify all regions of orientation space that may present problems for automated indexing prior to initiating an automated scan, and to minimize this space through the optimization of acquisition and indexing parameters. This work presents new methods for identifying regions in orientation space where the reliability of the automated indexing is suspect prior to performing a scan. This methodology is used to characterize the impact of various parameters on the indexing algorithm.
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