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Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements

Author

Listed:
  • Xing Wang

    (Oak Ridge National Laboratory)

  • Constantinos Hatzoglou

    (Groupe de Physique des Matériaux)

  • Brian Sneed

    (Oak Ridge National Laboratory)

  • Zhe Fan

    (Oak Ridge National Laboratory)

  • Wei Guo

    (Oak Ridge National Laboratory)

  • Ke Jin

    (Oak Ridge National Laboratory)

  • Di Chen

    (Los Alamos National Laboratory)

  • Hongbin Bei

    (Oak Ridge National Laboratory)

  • Yongqiang Wang

    (Los Alamos National Laboratory)

  • William J. Weber

    (Oak Ridge National Laboratory
    University of Tennessee-Knoxville)

  • Yanwen Zhang

    (Oak Ridge National Laboratory
    University of Tennessee-Knoxville)

  • Baptiste Gault

    (Max-Planck-Institut für Eisenforschung
    Imperial College London, Royal School of Mine)

  • Karren L. More

    (Oak Ridge National Laboratory)

  • Francois Vurpillot

    (Groupe de Physique des Matériaux)

  • Jonathan D. Poplawsky

    (Oak Ridge National Laboratory)

Abstract

Quantifying chemical compositions around nanovoids is a fundamental task for research and development of various materials. Atom probe tomography (APT) and scanning transmission electron microscopy (STEM) are currently the most suitable tools because of their ability to probe materials at the nanoscale. Both techniques have limitations, particularly APT, because of insufficient understanding of void imaging. Here, we employ a correlative APT and STEM approach to investigate the APT imaging process and reveal that voids can lead to either an increase or a decrease in local atomic densities in the APT reconstruction. Simulated APT experiments demonstrate the local density variations near voids are controlled by the unique ring structures as voids open and the different evaporation fields of the surrounding atoms. We provide a general approach for quantifying chemical segregations near voids within an APT dataset, in which the composition can be directly determined with a higher accuracy than STEM-based techniques.

Suggested Citation

  • Xing Wang & Constantinos Hatzoglou & Brian Sneed & Zhe Fan & Wei Guo & Ke Jin & Di Chen & Hongbin Bei & Yongqiang Wang & William J. Weber & Yanwen Zhang & Baptiste Gault & Karren L. More & Francois Vu, 2020. "Interpreting nanovoids in atom probe tomography data for accurate local compositional measurements," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-14832-w
    DOI: 10.1038/s41467-020-14832-w
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