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“Obtaining 3D Atomic Reconstructions from Electron Microscopy Images Using a Bayesian Genetic Algorithm: Possibilities, Insights, and Limitations”. Stoops T, De Backer A, Lobato I, Van Aert S, Microscopy and Microanalysis (2024). http://doi.org/10.1093/mam/ozae090
Abstract: The Bayesian genetic algorithm (BGA) is a powerful tool to reconstruct the 3D structure of mono-atomic single-crystalline metallic nanoparticles imaged using annular dark field scanning transmission electron microscopy. The number of atoms in a projected atomic column in the image is used as input to obtain an accurate and atomically precise reconstruction of the nanoparticle, taking prior knowledge and the finite precision of atom counting into account. However, as the number of parameters required to describe a nanoparticle with atomic detail rises quickly with the size of the studied particle, the computational costs of the BGA rise to prohibitively expensive levels. In this study, we investigate these computational costs and propose methods and control parameters for efficient application of the algorithm to nanoparticles of at least up to 10 nm in size.
Keywords: A1 Journal Article; Electron Microscopy for Materials Science (EMAT) ;
Impact Factor: 2.8
DOI: 10.1093/mam/ozae090
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“Investigation of the Octahedral Network Structure in Formamidinium Lead Bromide Nanocrystals by Low-Dose Scanning Transmission Electron Microscopy”. Schrenker NJ, Braeckevelt T, De Backer A, Livakas N, Yu C-P, Friedrich T, Roeffaers MBJ, Hofkens J, Verbeeck J, Manna L, Van Speybroeck V, Van Aert S, Bals S, Nano Letters 24, 10936 (2024). http://doi.org/10.1021/acs.nanolett.4c02811
Abstract: Metal halide perovskites (MHP) are highly promising semiconductors. In this study, we focus on FAPbBr3 nanocrystals, which are of great interest for green light-emitting diodes. Structural parameters significantly impact the properties of MHPs and are linked to phase instability, which hampers long-term applications. Clearly, there is a need for local and precise characterization techniques at the atomic scale, such as transmission electron microscopy. Because of the high electron beam sensitivity of MHPs, these investigations are extremely challenging. Here, we applied a low-dose method based on four-dimensional scanning transmission electron microscopy. We quantified the observed elongation of the projections of the Br atomic columns, suggesting an alternation in the position of the Br atoms perpendicular to the Pb–Br–Pb bonds. Together with molecular dynamics simulations, these results remarkably reveal local distortions in an on-average cubic structure. Additionally, this study provides an approach to prospectively investigating the fundamental degradation mechanisms of MHPs.
Keywords: A1 Journal Article; Electron Microscopy for Materials Science (EMAT) ;
Impact Factor: 10.8
DOI: 10.1021/acs.nanolett.4c02811
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“Optimal experimental design for the detection of light atoms from high-resolution scanning transmission electron microscopy images”. Gonnissen J, de Backer A, den Dekker AJ, Martinez GT, Rosenauer A, Sijbers J, Van Aert S, Applied physics letters 105, 063116 (2014). http://doi.org/10.1063/1.4892884
Abstract: We report an innovative method to explore the optimal experimental settings to detect light atoms from scanning transmission electron microscopy (STEM) images. Since light elements play a key role in many technologically important materials, such as lithium-battery devices or hydrogen storage applications, much effort has been made to optimize the STEM technique in order to detect light elements. Therefore, classical performance criteria, such as contrast or signal-to-noise ratio, are often discussed hereby aiming at improvements of the direct visual interpretability. However, when images are interpreted quantitatively, one needs an alternative criterion, which we derive based on statistical detection theory. Using realistic simulations of technologically important materials, we demonstrate the benefits of the proposed method and compare the results with existing approaches.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 3.411
Times cited: 12
DOI: 10.1063/1.4892884
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