title: New techniques for the analysis of fine-scaled clustering phenomena within atom probe tomography (APT) data.
abstract: 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.
authors.affiliation: Australian Key Centre for Microscopy and Microanalysis, University of Sydney, Madsen Building, F09, Sydney, NSW 2006, Australia. stephenson@usyd.edu.au
authors.forename: Leigh T
authors.initials: LT
authors.lastname: Stephenson
authors.forename: Michael P
authors.initials: MP
authors.lastname: Moody
authors.forename: Peter V
authors.initials: PV
authors.lastname: Liddicoat
authors.forename: Simon P
authors.initials: SP
authors.lastname: Ringer