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      \(\textit{ab initio}\) electrostatic potentials for transmission electron microscopy

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          Abstract

          The simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret their contrast and extract specimen features. This is especially true for high-resolution phase-contrast imaging of materials, but model-based reconstructions in TEM are widely used across the physical and biological sciences. Since electron scattering is dominated by the nuclear cores, the scattering potential is typically described by the widely applied independent atom model. This approximation is fast and accurate, especially for annular dark-field contrast, but it completely neglects valence bonding and its effect on the transmitting electrons. However, an emerging trend in electron microscopy is to use new instrumentation and methods to extract the maximum amount of information from each electron. This is evident in the increasing popularity of techniques such as 4D-STEM combined with ptychography in materials science, and cryogenic microcrystal electron diffraction in structural biology, where subtle differences in the scattering potential may be both measurable and contain additional insights. Thus, there is increasing interest in electron scattering simulations based on electrostatic potentials obtained from first principles, mainly via density functional theory. In this Review, we discuss the motivation and basis for these developments, survey the pioneering work that has been published thus far, and give our outlook for the future. We argue that a physically better justified \(\textit{ab initio}\) description of the scattering potential is both useful and viable for an increasing number of systems, and we expect such simulations to steadily gain in popularity and importance.

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          Author and article information

          Journal
          14 October 2020
          Article
          2010.07145
          d0694b38-7273-41b4-af3b-e5b66b783a1c

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Custom metadata
          27 pages, 3 figures, 3 tables
          cond-mat.mtrl-sci

          Condensed matter
          Condensed matter

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