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Title: The Application of the OPTICS Algorithm to Cluster Analysis in Atom Probe Tomography Data

Abstract

Atom probe tomography (APT) is a powerful technique to characterize buried 3D nanostructures in a variety of materials. Accurate characterization of those nanometer-scale clusters and precipitates is of great scientific significance to understand the structure-property relationships and the microstructural evolution. The current widely used cluster analysis method, a variant of the DBSCAN algorithm, can only accurately extract clusters of the same atomic density, neglecting several experimental realities, such as density variations within and between clusters and the non-uniformity of the atomic density in the APT reconstruction itself (e.g. crystallographic poles and other field evaporation artifacts). The clustering results of DBSCAN-like method rely heavily on multiple input parameters, but ideal selection of those parameters is challenging and oftentimes ambiguous. In this study, we present a new cluster analysis method consisting of a well-known algorithm, called OPTICS, and a cluster extraction algorithm we developed to enable accurate detection of clusters of varying atomic density in APT data. The new method requires only one free parameter, and other inputs can be estimated based on physical parameters of the material. The effectiveness of this method is demonstrated by application to several small-scale model datasets and a real APT dataset obtained from an oxide-dispersion strengthenedmore » ferritic alloy specimen. The method’s sensitivity with respect to parameter selection is discussed and compared with the current widely used methods.« less

Authors:
 [1];  [1];  [1];  [2];  [1]
  1. BATTELLE (PACIFIC NW LAB)
  2. University of California, Berkeley
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1531346
Report Number(s):
PNNL-SA-133361
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Microscopy and Microanalysis
Additional Journal Information:
Journal Volume: 25; Journal Issue: 2
Country of Publication:
United States
Language:
English
Subject:
atom probe tomography, cluster analysis, density-based clustering

Citation Formats

Wang, Jing, Schreiber, Daniel K., Bailey, Nathan A., Hosemann, Peter, and Toloczko, Mychailo B. The Application of the OPTICS Algorithm to Cluster Analysis in Atom Probe Tomography Data. United States: N. p., 2019. Web. doi:10.1017/S1431927618015386.
Wang, Jing, Schreiber, Daniel K., Bailey, Nathan A., Hosemann, Peter, & Toloczko, Mychailo B. The Application of the OPTICS Algorithm to Cluster Analysis in Atom Probe Tomography Data. United States. doi:10.1017/S1431927618015386.
Wang, Jing, Schreiber, Daniel K., Bailey, Nathan A., Hosemann, Peter, and Toloczko, Mychailo B. Mon . "The Application of the OPTICS Algorithm to Cluster Analysis in Atom Probe Tomography Data". United States. doi:10.1017/S1431927618015386.
@article{osti_1531346,
title = {The Application of the OPTICS Algorithm to Cluster Analysis in Atom Probe Tomography Data},
author = {Wang, Jing and Schreiber, Daniel K. and Bailey, Nathan A. and Hosemann, Peter and Toloczko, Mychailo B.},
abstractNote = {Atom probe tomography (APT) is a powerful technique to characterize buried 3D nanostructures in a variety of materials. Accurate characterization of those nanometer-scale clusters and precipitates is of great scientific significance to understand the structure-property relationships and the microstructural evolution. The current widely used cluster analysis method, a variant of the DBSCAN algorithm, can only accurately extract clusters of the same atomic density, neglecting several experimental realities, such as density variations within and between clusters and the non-uniformity of the atomic density in the APT reconstruction itself (e.g. crystallographic poles and other field evaporation artifacts). The clustering results of DBSCAN-like method rely heavily on multiple input parameters, but ideal selection of those parameters is challenging and oftentimes ambiguous. In this study, we present a new cluster analysis method consisting of a well-known algorithm, called OPTICS, and a cluster extraction algorithm we developed to enable accurate detection of clusters of varying atomic density in APT data. The new method requires only one free parameter, and other inputs can be estimated based on physical parameters of the material. The effectiveness of this method is demonstrated by application to several small-scale model datasets and a real APT dataset obtained from an oxide-dispersion strengthened ferritic alloy specimen. The method’s sensitivity with respect to parameter selection is discussed and compared with the current widely used methods.},
doi = {10.1017/S1431927618015386},
journal = {Microscopy and Microanalysis},
number = 2,
volume = 25,
place = {United States},
year = {2019},
month = {4}
}