Berlin 2024 – scientific programme

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MM: Fachverband Metall- und Materialphysik

MM 4: Data Driven Material Science: Big Data and Workflows I

MM 4.7: Talk

Monday, March 18, 2024, 12:00–12:15, C 243

Automatic extraction and analysis of dislocations in atom probe tomography data using skeletonization — •Alaukik Saxena, Baptiste Gault, and Christoph Freysoldt — Max-Planck-Institut für Eisenforschung GmbH, Düsseldorf 40237, Germany

Atom probe tomography (APT) is a unique technique that provides 3D elemental distribution with a near-atomic resolution for a given material. Extracting and analyzing microstructural features in 3D APT data is challenging and time-intensive, given their complex morphology. Here, we introduce a workflow to systematically extract linear microstructural features, particularly dislocations, from the APT data. The workflow extracts isosurface meshes from APT data and, as a preprocessing step, filters them using principal component analysis (PCA) to find geometrically anisotropic microstructural features. Further, a topology analysis concept called skeletonisation is applied to extract the linear graphs or skeletons of each mesh. Since the skeleton encapsulates the underlying geometry of a mesh, it is used to identify and segment linear features or dislocation segments even in very complex microstructures containing, for example, dislocation networks. This enables a robust composition and geometric analysis of dislocations in APT data. Additionally, the workflow integrates crystallographic data from APT to determine dislocation orientation in the crystal coordinate system. Overall, this advanced workflow significantly reduces manual effort and opens new possibilities for high-throughput studies in material science.

Keywords: Atom probe tomography; Skeletonisation; Dilocations