Application of Fourier transform and autocorrelation to cluster identification in the three-dimensional atom probe

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.