|About this Abstract
||2018 TMS Annual Meeting & Exhibition
||Atom Probe Tomography for Advanced Characterization of Metals, Minerals and Materials
||A New Approach to Detect Clusters of Varying Density in Atom Probe Tomography and Its Applications to Oxide-dispersion Strengthened Alloys
||Jing Wang, Nathan Bailey, Peter Hosemann, Daniel K. Schreiber, Mychailo Toloczko
|On-Site Speaker (Planned)
Accurate extraction of nanometer-scale features in atom probe tomography (APT) data is essential to many applications. The current widely used cluster analysis method can only accurate extract clusters of the same atomic density. For many applications, clusters of varying density may exist, and fully exploring the parameter space to effectively extract clusters can be time prohibitive. In this study we present a new cluster analysis method that is based on an advanced well-known algorithm called OPTICS to enable the accurate detection of clusters of varying atomic density in APT data requiring determination of one free parameter. The effects of parameter selection and data quality on retrieving cluster structures is explored. The effectiveness of this method is demonstrated by application to multiple APT datasets of an unirradiated or irradiated oxide-dispersion strengthened ferritic alloy, and the result is compared with the current widely used method.
||Planned: Supplemental Proceedings volume