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Three-dimensional imaging of dislocations

Author

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  • Peter Rez

    (Arizona State University, PO Box 871504, Tempe, Arizona 85287-1504, USA)

  • Michael M. J. Treacy

    (Arizona State University, PO Box 871504, Tempe, Arizona 85287-1504, USA)

Abstract

arising from C.-C. Chen et al. Nature 496, 74–77 (2013)10.1038/nature12009 At first sight, the achievement of determining atom positions in three dimensions appears spectacular1. Chen and colleagues1 apply a form of tomographic reconstruction to a tilt series of annular dark field (ADF) images of crystalline particles with defects, where the original data has a filter applied to reduce noise. However, the filtering imposes periodicities and significantly downgrades resolution, and the condition of signal linearity—a requirement for tomography—has not been met. We consider that their procedure gives an illusion of locating atom positions accurately. There is a Reply to this Brief Communication Arising by Miao, J. et al. Nature503,http://dx.doi.org/10.1038/nature12661(2013) .

Suggested Citation

  • Peter Rez & Michael M. J. Treacy, 2013. "Three-dimensional imaging of dislocations," Nature, Nature, vol. 503(7476), pages 1-1, November.
    • Handle: RePEc:nat:nature:v:503:y:2013:i:7476:d:10.1038_nature12660
    DOI: 10.1038/nature12660
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    Cited by:

    1. Andreas Leitherer & Angelo Ziletti & Luca M. Ghiringhelli, 2021. "Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    2. Tore Niermann & Laura Niermann & Michael Lehmann, 2024. "Three dimensional classification of dislocations from single projections," Nature Communications, Nature, vol. 15(1), pages 1-7, December.

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