Application of Delaunay tessellation for the characterization of solute-rich clusters in atom probe tomography

This work presents an original method for cluster selection in Atom Probe Tomography designed to be applied to large datasets. It is based on the calculation of the Delaunay tessellation generated by the distribution of atoms of a selected element. It requires a single input parameter from the user. Furthermore, no prior knowledge of the material is needed. The sensitivity of the proposed Delaunay cluster selection is demonstrated by its application on simulated APT datasets. A strong advantage of the proposed methodology is that it is reinforced by the availability of an analytical model for the distribution of Delaunay cells circumspheres, which is used to control the accuracy of the cluster selection procedure. Another advantage of the Delaunay cluster selection is the direct calculation of a sharp envelope for each identified cluster or precipitate, which leads to the more appropriate morphology of the objects as they are reconstructed in the APT dataset.