The purpose of this work is to develop a methodology to estimate the APT reconstruction parameters when limited crystallographic information is available. Reliable spatial scaling of APT data currently requires identification of multiple crystallographic poles from the field desorption image for estimating the reconstruction parameters. This requirement limits the capacity of accurately reconstructing APT data for certain complex systems, such as highly alloyed systems and nanostructured materials wherein more than one pole is usually not observed within one grain. To overcome this limitation, we develop a quantitative methodology for calibrating the reconstruction parameters in an APT dataset by ensuring accurate inter-planar spacing and optimizing the curvature correction for the atomic planes corresponding to a single crystallographic orientation. We validate our approach on an aluminum dataset and further illustrate its capabilities by computing geometric reconstruction parameters for W and Al-Mg-Sc datasets.
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http://dx.doi.org/10.1016/j.ultramic.2013.02.013 | DOI Listing |
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