Speaker
Description
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Defect engineering is an important strategy for tuning the electronic and magnetic properties of complex oxides. Therefore, it is essential to understand atomic-scale defects, such as dopants and vacancies, in complex oxides like SrTiO$_{3}$ (STO). However, linking the microscopic properties of individual point defects to macroscopic material behavior remains challenging. Although first-principles density functional theory (DFT) provides the structural and electronic basis needed to interpret advanced electron microscopy data and predict bulk functionality, reliable defect characterization and single-atom sensitivity in the bulk are often limited by spatial resolution, signal sensitivity, and experimental stability.
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To address this, we conducted atomic-resolution momentum-resolved scanning transmission electron microscopy, mostly called 4D-STEM [1], experiments on STO doped with 0.5 wt% Ta using a Nion HERMES microscope operated at 60 kV with a semi-convergence angle of 36 mrad. Ultrathin samples (less than 6 nm), prepared by wedge polishing and characterized by neural network-assisted PACBED analysis [2], were crucial for reliable defect detection. [3] DFT calculations [4] were used to determine relaxed structures of Ta dopants and associated Sr vacancies. These structures were then used in multislice simulations [5] to optimize the experimental conditions and predict defect-induced changes in the angular scattering distribution. [6]
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We demonstrate that sub-ångström atomic displacements generate distinctive diffuse Huang scattering [7] that significantly impacts the momentum-resolved 4D-STEM signal. By incorporating these distortions into the simulations, we identify defect-specific scattering signatures and design virtual detectors that enhance sensitivity to individual point defects.
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By combining DFT-derived defect structures, multislice simulations, and 4D-STEM, we establish a robust framework for detecting and characterizing individual point defects in complex oxides and other functional materials.
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[1] Colin Ophus. “Four-Dimensional Scanning Transmission Electron Microscopy (4D-STEM): From Scanning Nanodiffraction to Ptychography and Beyond”, Microscopy and Microanalysis 25.3 (2019): 563–582.
[2] Oberaigner, Michael, et al. "Online thickness determination with position averaged convergent beam electron diffraction using convolutional neural networks." Microscopy and Microanalysis 29.1 (2023): 427-436.
[3] Mittal, Anudha, and K. Andre Mkhoyan. "Limits in detecting an individual dopant atom embedded in a crystal." Ultramicroscopy 111.8 (2011): 1101-1110.
[4] Volker Blum, Ralf Gehrke, Felix Hanke, Paula Havu, Ville Havu, Xinguo Ren, Karsten Reuter, and Matthias Scheffler, “Ab Initio Molecular Simulations with Numeric Atom-Centered Orbitals”, Computer Physics Communications 180 (2009): 2175-2196.
[5] Madsen, Jacob, and Toma Susi. "The abTEM code: transmission electron microscopy from first principles." Open Research Europe 1 (2021): 24.
[6] Rafael Fritz. „Quantitative Untersuchungen der Zusammensetzung von kubischen III/V-Verbindungshalbleitern mittels HAADF-STEM“, PhD Thesis, Philipps-Universität Marburg (2013)
[7] Huang, Kun. "X-ray reflexions from dilute solid solutions." Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences 190.1020 (1947): 102-117.