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The Influence of Isoconcentration Surface Selection in Quantitative Outputs from Proximity Histograms

Published online by Cambridge University Press:  04 March 2019

Dallin J Barton ,
B Chad Hornbuckle ,
Kristopher A Darling  and
Gregory B Thompson
Dallin J Barton*
Affiliation:
Department of Metallurgical & Materials Engineering, The University of Alabama, Box 870202 Tuscaloosa, AL 35487-0200, USA
B Chad Hornbuckle
Affiliation:
United States Army Research Laboratory, Weapons and Materials Research Directorate, RDRL-WMM-B Aberdeen Proving Grounds, Aberdeen Proving Grounds, MD, 21005-5069, USA
Kristopher A Darling
Affiliation:
United States Army Research Laboratory, Weapons and Materials Research Directorate, RDRL-WMM-B Aberdeen Proving Grounds, Aberdeen Proving Grounds, MD, 21005-5069, USA
Gregory B Thompson
Affiliation:
Department of Metallurgical & Materials Engineering, The University of Alabama, Box 870202 Tuscaloosa, AL 35487-0200, USA
*
*Author for correspondence: Dallin J. Barton, E-mail: [email protected]
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Abstract

Isoconcentration surfaces are commonly used to delineate phases in atom probe datasets. These surfaces then provide the spatial and compositional reference for proximity histograms, the number density of particles, and the volume fraction of particles within a multiphase system. This paper discusses the influence of the isoconcentration surface selection value on these quantitative outputs, using a simple oxide dispersive strengthened alloy, Fe91Ni8Zr1, as the case system. Zirconium reacted with intrinsic oxygen impurities in a consolidated ball-milled powder to precipitate nanoscale zirconia particles. The zirconia particles were identified by varying the Zr-isoconcentration values as well as by the maximum separation data mining method. The associated outputs mentioned above are elaborated upon in reference to the variation in this Zr isosurface value. Considering the dataset as a whole, a 10.5 at.% Zr isosurface provided a compositional inflection point for Zr between the particles and matrix on the proximity histogram; however, this value was unable to delineate all of the secondary oxide particles identified using the maximum separation method. Consequently, variations in the number density and volume fraction were observed as the Zr isovalue was changed to capture these particles resulting in a loss of the compositional accuracy. This highlighted the need for particle-by-particle analysis.

Keywords

cluster analysishigh-chemical-partitioningisoconcentration surfacelow-soluteproximity histogram
Type
Data Analysis
Information
Microscopy and Microanalysis , Volume 25 , Special Issue 2: Atom Probe Tomography and Microscopy APT&M 2018 , April 2019 , pp. 401 - 409
Copyright
Copyright © Microscopy Society of America 2019 

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