Abstract
Atom probe tomography (APT) constitutes a rather unique analytical technique for the 3D elemental characterization of solid materials with potentially sub‐nm spatial resolution. APT is, therefore, very well suited for the analysis of a nanostructured specimen such as matrix‐embedded nanoparticles, ultra‐thin films and junctions, grain boundaries, and others. This presentation will emphasize these capabilities, describing three methods of data mining that can be used to fully exploit APT: (i) Visualization of atomic lattice planes in crystalline specimens, (ii) the determination of iso‐concentration surfaces and proximity histograms derived thereof, and (iii) a cluster identification algorithm based on maximum‐atom separations. These approaches will be illustrated by means of different types of samples: a crystalline tungsten specimen, a Fe/Cr/Fe multilayer system, Si nanocrystals embedded in a silicon oxide matrix, and Mg clustering in GaN. The results demonstrate clearly that sub‐nm‐sized structures can be characterized by APT. Copyright © 2014 John Wiley & Sons, Ltd.
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