Atom Probe Tomography Interlaboratory Study on Clustering Analysis in Experimental Data Using the Maximum Separation Distance Approach
Journal article, 2019

We summarize the findings from an interlaboratory study conducted between ten international research groups and investigate the use of the commonly used maximum separation distance and local concentration thresholding methods for solute clustering quantification. The study objectives are: to bring clarity to the range of applicability of the methods; identify existing and/or needed modifications; and interpretation of past published data. Participants collected experimental data from a proton-irradiated 304 stainless steel and analyzed Cu-rich and Ni-Si rich clusters. The datasets were also analyzed by one researcher to clarify variability originating from different operators. The Cu distribution fulfills the ideal requirements of the maximum separation method (MSM), namely a dilute matrix Cu concentration and concentrated Cu clusters. This enabled a relatively tight distribution of the cluster number density among the participants. By contrast, the group analysis of the Ni-Si rich clusters by the MSM was complicated by a high Ni matrix concentration and by the presence of Si-decorated dislocations, leading to larger variability among researchers. While local concentration filtering could, in principle, tighten the results, the cluster identification step inevitably maintained a high scatter. Recommendations regarding reporting, selection of analysis method, and expected variability when interpreting published data are discussed.

atom probe tomography

maximum separation

cluster analysis

Author

Yan Dong

University of Michigan

Auriane Etienne

INSA Rouen

Alex Frolov

National Research Centre "Kurchatov Institute"

Svetlana Fedotova

National Research Centre "Kurchatov Institute"

Katsuhiko Fujii

Institute of Nuclear Safety System, Incorporated

Koji Fukuya

Institute of Nuclear Safety System, Incorporated

Constantinos Hatzoglou

INSA Rouen

Evgenia Kuleshova

National Research Centre "Kurchatov Institute"

Kristina Lindgren

Chalmers, Physics, Materials Microstructure

Andrew London

United Kingdom Atomic Energy Authority

Anabelle Lopez

University Paris-Saclay

Sergio Lozano-Perez

University of Oxford

Yuichi Miyahara

Central Research Institute of Electric Power Industry (CRIEPI)

Yasuyoshi Nagai

Tohoku University

Kenji Nishida

Central Research Institute of Electric Power Industry (CRIEPI)

Bertrand Radiguet

INSA Rouen

Daniel K. Schreiber

Pacific Northwest National Laboratory

Naoki Soneda

Central Research Institute of Electric Power Industry (CRIEPI)

Mattias Thuvander

Chalmers, Physics, Materials Microstructure

Takeshi Toyama

Tohoku University

Jing Wang

Pacific Northwest National Laboratory

Faiza Sefta

Electricite de France (EDF)

Peter Chou

Electric Power Research Institute (EPRI)

Emmanuelle A. Marquis

University of Michigan

Microscopy and Microanalysis

1431-9276 (ISSN) 1435-8115 (eISSN)

Subject Categories

Other Computer and Information Science

Analytical Chemistry

Bioinformatics and Systems Biology

DOI

10.1017/S1431927618015581

More information

Latest update

2/13/2019