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Application of Fourier transform and autocorrelation to cluster identification in the three‐dimensional atom probe
Author(s) -
VURPILLOT F.,
DE GEUSER F.,
DA COSTA G.,
BLAVETTE D.
Publication year - 2004
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/j.0022-2720.2004.01413.x
Subject(s) - fourier transform , autocorrelation , atom (system on chip) , cluster (spacecraft) , reciprocal lattice , discrete fourier transform (general) , computer science , reciprocal , algorithm , physics , materials science , optics , short time fourier transform , mathematics , fourier analysis , statistics , quantum mechanics , linguistics , philosophy , diffraction , programming language , embedded system
Summary Because of the increasing number of collected atoms (up to millions) in the three‐dimensional atom probe, derivation of chemical or structural information from the direct observation of three‐dimensional images is becoming more and more difficult. New data analysis tools are thus required. Application of a discrete Fourier transform algorithm to three‐dimensional atom probe datasets provides information that is not easily accessible in real space. Derivation of mean particle size from Fourier intensities or from three‐dimensional autocorrelation is an example. These powerful methods can be used to detect and image nano‐segregations. Using three‐dimensional ‘bright‐field’ imaging, single nano‐segregations were isolated from the surrounding matrix of an iron–copper alloy. Measurement of the inner concentration within clusters is, therefore, straightforward. Theoretical aspects related to filtering in reciprocal space are developed.