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Strategies for fast and reliable 4D-STEM orientation and phase mapping of nanomaterials and devices

The development of fast electron detectors has significantly improved the speed of acquisition and the field of view in scanning electron nanodiffraction (SEND) or 4D scanning transmission electron microscopy (4D-STEM) for crystallographic orientation and phase imaging. Such imaging requires fast and robust diffraction pattern (DP) indexing and identification of crystal orientation and/or phases. However, a major difficulty is electron dynamical scattering, which renders the diffraction intensity highly dependent on the crystal thickness and orientation. The other difficulty is the large amount of data, where fast analysis is critical. Automatic DP indexing is usually achieved by comparing an experiment DP with a set of simulated DPs and by searching for the best pattern match [1, 2] Several algorithms have been reported for spot DP matching. These algorithms can be broadly separated into the intensity and the diffraction vector based approaches [2]. The difficulty with dynamical scattering is removed in the vector-based approach, where indexing is based on the DP geometry alone. However, the use of this method is also limited when the crystal orientation is far away from the zone axis, where there are only a few of diffraction spots. Precession electron diffraction (PED) helps reducing the dynamical effect and increases the number of diffraction spots recorded in a single pattern; both are beneficial for DP indexing[3]. But PED does not render diffraction intensity entirely kinematical, and precession also reduces the sensitivity of diffraction spots to orientation. Using calculated dynamical intensities, for example using the Bloch wave method, could also help with the reliability of DP indexing. But crystal thickness often varies in a nanocrystalline sample, such variations increase the complexity of DP matching and thus the speed of analysis. To