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

Abstract

The 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.

Precipitate modification in PH13-8 Mo type maraging steel

“…Frequency distribution analysis [37,38] was performed to examine the distribution of elements in the analyzed volume. Clusters were detected by applying a cluster search algorithm based on the maximum separation method [39]. The separation distance (d max ), the surround distance (L), the erosion distance (d ero ) and the minimum number of atoms (N min ) were determined based on a method described elsewhere [40].…”

“…1 were analyzed. The Al and Ti concentrations were obtained by applying a cluster search algorithm based on the maximum separation method [39], using d max = 0.42 nm, L = 0.35 nm, d ero = 0.35 nm and N min = 7. The results obtained are given in Fig.…”

The Precipitation Behavior of Superalloy ATI Allvac 718Plus

“…[8] at 1048 K for 60 s. Visual inspection does not give any evidence for precipitates and the spatial distribution of the elements seems to be completely homogeneous in the early stages of aging. By applying a cluster-search algorithm [28] for Ti and Al, respectively, it is possible to reconstruct clusters or small precipitates inside the scanned volume. The algorithm allows the identification of clusters and provides chemical information for both clusters and matrix.…”

Precipitation hardening of biodegradable Fe–Mn–Pd alloys

“…To gather more information on the Pd-enriched regions, a cluster search algorithm based on the maximum separation method was applied [21]. The required input parameters separation distance (d max ), surrounding distance (L), erosion distance (d ero ), and the minimum number of ions (N min ) were chosen, as suggested by Vaumousse et al [22] and Imago Scientific Instruments [23].…”