|About this Abstract
||2020 TMS Annual Meeting & Exhibition
||Atom Probe Tomography for Advanced Characterization of Metals, Minerals and Materials III
||Morphological Classification of Dense Objects in Atom Probe Tomography Data
||Iman Ghamarian, Emmanuelle A. Marquis
|On-Site Speaker (Planned)
Atom probe tomography (APT) is used for quantifying solute clusters and their interactions with defects in many alloy systems. Reliable quantification is essential to link these microstructural features and their evolution to materials properties. However, existing methods, i.e. the maximum separation method, only applies to limited microstructures and are highly dependent on user input. In an effort to develop reliable and statistical analysis methods, we explored the use of hierarchical density-based cluster analysis methods. We successfully applied it to complex microstructures. This approach is less dependent on subjective selection of parameters and exhibit significantly more accurate performance than the traditionally used maximum separation method. We also integrated an integrated density-based cluster analysis method and skeleton extraction to find dislocation loops/lines in APT data. We will provide a demonstration of the openly available interface on simulated and experimentally acquired datasets.
||Planned: Supplemental Proceedings volume