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Advanced volume reconstruction and data mining methods in atom probe tomography

Published online by Cambridge University Press:  08 January 2016

F. Vurpillot ,
W. Lefebvre ,
J.M. Cairney ,
C. Oberdorfer ,
B.P. Geiser  and
K. Rajan
F. Vurpillot
Affiliation:
Groupe de Physique des Matériaux, UMR CNRS 6634, Université et INSA de Rouen, France; [email protected]
W. Lefebvre
Affiliation:
Groupe de Physique des Matériaux, UMR CNRS 6634, Université et INSA de Rouen, France; [email protected]
J.M. Cairney
Affiliation:
School of Aerospace Mechanical and Mechatronic Engineering, and Australian Centre for Microscopy & Microanalysis, The University of Sydney, Australia; [email protected]
C. Oberdorfer
Affiliation:
Institute of Materials Science, University of Stuttgart, Germany; [email protected]
B.P. Geiser
Affiliation:
CAMECA Instruments, Inc., USA; email [email protected]
K. Rajan
Affiliation:
Department of Materials Design and Innovation, The State University of New York at Buffalo, USA; [email protected]
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Abstract

This article reviews post-analysis processing methods for data acquired using atom probe tomography (APT). Field-induced aberrations of APT images arise from distorted ion flight trajectories and differences in ion evaporation rates. Addressing this issue requires the development of image processing tools that yield three-dimensionally reconstructed images that reliably reflect the original specimens. One of the biggest advantages of the APT technique is its ability to collect information about millions of individual atoms. Understanding these data requires the development of mathematical and statistical data mining tools, involving disciplines beyond the basic physics of APT. The above issues have important implications for addressing materials science-related questions.

Keywords

nanostructuresimulationmorphology
Type
Research Article
Information
MRS Bulletin , Volume 41 , Issue 1: Atom Probe Tomography , January 2016 , pp. 46 - 52
Copyright
Copyright © Materials Research Society 2016 

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