Atomic Probe Tomography Data Generation Model for Assessing the Applicability of Cluster Search Methods

Using atomic probe tomography (APT), it is possible to study nanoscale features of the structural and phase state of various materials. When developing methods for analyzing APT data, it is necessary evaluate the efficiency and accuracy of the proposed algorithms for feature search and analysis. However, the destructive nature of APT analysis and the high labor intensity of producing reference materials with specified nanostructure parameters make it difficult to evaluate the accuracy of nanoscale feature identification methods based on experimental data analysis. For such tasks, the most convenient approach is to use specially generated data with controlled nanostructure parameters. In this study, an approach based on modeling atomic probe data for evaluating the accuracy of cluster search algorithms has been proposed. The effect of a nanocluster size and composition on the accuracy of their determination has been considered. Assumptions regarding the main reasons for the reduced accuracy of basic cluster search algorithms have been made. Approaches for estimating and accounting for the applicability limits of approaches to characterizing nanoscale features have been proposed.