Automated Data Acquisition and Indexing of Electron Channeling Patterns us- ing the Dictionary Approach

Defect analysis using a Scanning Electron Microscope (SEM), commonly known as Electron Channeling Contrast Imaging (ECCI), has received much attention in the recent past. Traditional defect analysis has for decades relied on Transmission Electron Microscopy (TEM) modalities, such as the bright field-dark field and weak beam imaging, and Scanning Transmission Electron Microcopy (STEM) diffraction contrast imaging methods. While the spatial resolution of ECCI is somewhat lower than that of the TEM based methods, ECCI provides more flexibility in sample preparation and data acquisition from bulk samples. The method relies on the variation of backscatter yield near lattice defects. However, to achieve quantitative defect analysis, the exact diffraction conditions need to be known, which, in turn, requires accurate determination of the crystal orientation. Electron Channeling Patterns (ECP), the diffraction modality associated with ECCI, are somewhat challenging to index. The method of the Hough transform, used for indexing EBSD patterns, does not always work with ECPs due to the limited angular range of the channeling pattern. In the absence of a general method to index ECPs, there is a lack of commercial and open source software packages to automate this process. While there have been efforts to integrate ECCI with the Electron Backscatter Diffraction (EBSD) method [1] for orientation mapping, it would be convenient if the orientation determination could be performed without the use of extra hardware and in an automated fashion. Furthermore, with the advent of fully scriptable microscopes for stage control and data acquisition, it has become possible to automate the data collection process for rapid ECCI-based defect characterization and analysis.