Aspects of the observation of clusters in the 3‐dimensional atom probe

Abstract

AbstractThe maximum separation method is a useful technique for the identification of solute clusters within 3‐dimensional atom probe (3DAP) data. However, the method requires the selection of appropriate parameters that will correctly identify solute clusters without incorrectly identifying random variation in solute atom separations as being due to cluster formation. A simple analytical approach has been used to estimate the apparent number of clusters that would be expected using the maximum separation method in a random solute distribution of a given overall composition. Results of the analytical model have been found to give a good match with tests where the maximum separation method has been applied to randomised experimental 3DAP data. The model allows calculation of suitable parameters for accurate identification of clusters under a range of different conditions. A Poisson probability distribution has been used to formalise the errors involved in the measurement of the number densities of clusters or precipitates within 3DAP data. This approach also allows an upper limit for the precipitate density to be defined in cases where no precipitates are observed within a volume of analysis. Copyright © 2007 John Wiley & Sons, Ltd.