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Author |
Stoops, T.; De Backer, A.; Lobato, I.; Van Aert, S. |
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Title |
Obtaining 3D Atomic Reconstructions from Electron Microscopy Images Using a Bayesian Genetic Algorithm: Possibilities, Insights, and Limitations |
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A1 Journal Article |
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Year  |
2024 |
Publication |
Microscopy and Microanalysis |
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Keywords |
A1 Journal Article; Electron Microscopy for Materials Science (EMAT) ; |
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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. |
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Publication Date |
2024-10-02 |
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ISSN |
1431-9276 |
ISBN |
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Additional Links |
UA library record |
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Impact Factor |
2.8 |
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Open Access |
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Notes |
European Research Council, 770887 ; Research Foundation Flanders, G034621N G0A7723N 40007495 ; FWO and F.R.S-FNRS; Flemish Government; |
Approved |
Most recent IF: 2.8; 2024 IF: 1.891 |
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Call Number |
EMAT @ emat @c:irua:208929 |
Serial |
9270 |
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