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Atom Probe Tomography Analysis of Exsolved Mineral Phases
08:14

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Published on: October 25, 2019

Clustering and pair correlation function in atom probe tomography.

T Philippe1, S Duguay, D Blavette

  • 1Université de Rouen, GPM, UMR CNRS 6634 BP 12, Avenue de l'Université 76801 Saint Etienne de Rouvray, France. thomas.philippe@etu.univ-rouen.fr

Ultramicroscopy
|April 10, 2010
PubMed
Summary
This summary is machine-generated.

A new method using pair correlation functions accurately measures cluster composition in materials. This approach determines cluster concentration, size, and density, even for invisible clusters in 3D images.

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Computational Materials Science

Background:

  • Accurate characterization of nanoscale clusters in materials is challenging.
  • Existing methods for cluster analysis, like erosion or direct identification, have limitations.
  • 3D mapping techniques such as atom probe tomography provide detailed structural information but require robust analysis methods.

Purpose of the Study:

  • To develop a robust and efficient method for determining the composition and characteristics of small clusters within materials.
  • To establish an analytical framework for pair correlation functions applicable to two-phase systems.
  • To validate the method's efficacy on both visible and invisible clusters in silicon-based materials.

Main Methods:

  • Development of an analytical expression for the pair correlation function in a two-phase, mono-dispersed system.
  • Utilizing a best-fit procedure applied to experimental pair correlation functions.
  • Application and validation of the method on carbon-doped silicon and boron-implanted silicon.

Main Results:

  • The pair correlation function method accurately determines cluster concentration, parent phase concentration, cluster radius, and number density.
  • The method demonstrated high agreement with results obtained through other analytical techniques.
  • Successfully applied to analyze boron clusters in silicon, which are not directly visible in 3D images.

Conclusions:

  • The pair correlation function method offers a simple, fast, and elegant solution for cluster analysis in materials.
  • This approach overcomes limitations of traditional cluster identification and erosion techniques, particularly for sub-visual clusters.
  • The developed method provides a valuable tool for materials characterization, enhancing understanding of clustering phenomena.