| Summary: | Atom Probe Tomography (APT) is extensively used for the analysis of RPV steels. However, many different analysis methods and cluster search parameters are used, making comparisons between different datasets difficult. Suitable d(max) and N(min) parameters for the maximum separation method are investigated. In a randomised distribution of solute there is a finite probability that a group of more than N(min) solute ions exists within the d(max) distance. The same is true for experimental datasets from samples which have been thermally aged or irradiated, however these background clusters are not the result of ageing, they are purely statistically random co-incidences. A method is presented for identifying such "background" statistical clusters in real APT data sets, based upon their size and composition, which allows for improved sensitivity to small clusters.
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