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arXiv · 2604.22398

Accurate Nanoscale Mapping of Electric Fields across Random Grain Boundaries in Polycrystalline Oxides Using Precession-Assisted 4D-STEM

Sangjun Kang·Hyeyoung Cho·Maximilian Töllner·Anna Rose Nelson·Ziming Ding·Xiaoke Mu·Di Wang·Wolfgang Rheinheimer·Kai Wang·Bai-Xiang Xu·Jakob Konstantin Laux·Mahmoud Serour·Karsten Albe·Andreas Klein·Christian Kübel
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Abstract

Space charge layers (SCLs) at grain boundaries play a crucial role in modulating local electric fields and influencing the functional properties of materials, such as oxygen vacancy migration and ionic conductivity in oxide ceramics. However, the direct experimental analysis of such localized electric fields and the corresponding charge distribution remains challenging. Conventional center-of-mass (CoM) analysis in scanning transmission electron microscopy differential phase contrast (STEM-DPC) is strongly affected by orientation-dependent contrast and dynamical scattering. Here, we demonstrate that combining electron beam precession with advanced post-processing, employing iterative edge detection via a Sobel filter and singular value decomposition (SVD), enables reliable and accurate, unbiased diffraction shift measurements with minimal crystallographic artefacts. The new method accurately refines the central disk position in nanobeam electron diffraction (NBED) patterns and thus significantly improves the extraction of the local electric field and corresponding charge distribution. Comparative analysis with conventional CoM methods shows superior accuracy and robustness for random grain boundaries in BaTiO3 and SrTiO3 as exemplary case studies. The experimental work is complemented by atomistic simulations to separate the electric field of the SCL from the mean inner potential difference of the grain boundary and the elemental segregation around the grain boundary. The in-depth analysis shows that our approach enables high-fidelity mapping of electromagnetic fields and their charge distribution in complex polycrystalline specimens, laying the groundwork for improved quantitative analysis using STEM-DPC.

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Sangjun Kang, Hyeyoung Cho, Maximilian Töllner, Anna Rose Nelson, Ziming Ding, Xiaoke Mu, Di Wang, Wolfgang Rheinheimer, Kai Wang, Bai-Xiang Xu, Jakob Konstantin Laux, Mahmoud Serour, Karsten Albe, Andreas Klein, Christian Kübel. 2026-04-24. Accurate Nanoscale Mapping of Electric Fields across Random Grain Boundaries in Polycrystalline Oxides Using Precession-Assisted 4D-STEM. https://arxiv.org/abs/2604.22398

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