IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v503y2013i7476d10.1038_nature12660.html
   My bibliography  Save this article

Three-dimensional imaging of dislocations

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/nature12660
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/nature12660?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:503:y:2013:i:7476:d:10.1038_nature12660. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.