Microscopy and Microanalysis

Special Issue: Atom Probe Tomography

New Techniques for the Analysis of Fine-Scaled Clustering Phenomena within Atom Probe Tomography (APT) Data

Leigh T.  Stephenson  a1 c1 , Michael P.  Moody  a1 , Peter V.  Liddicoat  a1 and Simon P.  Ringer  a1 a2
a1 Australian Key Centre for Microscopy and Microanalysis, University of Sydney, Madsen Building, F09, Sydney, NSW 2006, Australia
a2 ARC Centre for Design in Light Metals, The University of Sydney, Sydney, NSW 2006, Australia

Article author query
stephenson lt   [PubMed][Google Scholar] 
moody mp   [PubMed][Google Scholar] 
liddicoat pv   [PubMed][Google Scholar] 
ringer sp   [PubMed][Google Scholar] 


Nanoscale atomic clusters in atom probe tomographic data are not universally defined but instead are characterized by the clustering algorithm used and the parameter values controlling the algorithmic process. A new core-linkage clustering algorithm is developed, combining fundamental elements of the conventional maximum separation method with density-based analyses. A key improvement to the algorithm is the independence of algorithmic parameters inherently unified in previous techniques, enabling a more accurate analysis to be applied across a wider range of material systems. Further, an objective procedure for the selection of parameters based on approximating the data with a model of complete spatial randomness is developed and applied. The use of higher nearest neighbor distributions is highlighted to give insight into the nature of the clustering phenomena present in a system and to generalize the clustering algorithms used to analyze it. Maximum separation, density-based scanning, and the core linkage algorithm, developed within this study, were separately applied to the investigation of fine solute clustering of solute atoms in an Al-1.9Zn-1.7Mg (at.%) at two distinct states of early phase decomposition and the results of these analyses were evaluated.

(Received August 23 2007)
(Accepted September 9 2007)

Key Words: atom probe tomography; solute clustering; cluster algorithms; nearest neighbors; data analysis; data mining.

c1 Corresponding author. E-mail: l.stephenson@usyd.edu.au