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Enhancing Element Identification by Expectation–Maximization Method in Atom Probe Tomography

Published online by Cambridge University Press:  28 February 2019

Francois Vurpillot ,
Constantinos Hatzoglou ,
Bertrand Radiguet ,
Gerald Da Costa ,
Fabien Delaroche  and
Frederic Danoix
Francois Vurpillot*
Affiliation:
Normandie Université, UNIROUEN, INSA Rouen, CNRS, Groupe de Physique des Matériaux, 76000 Rouen, France
Constantinos Hatzoglou
Affiliation:
Normandie Université, UNIROUEN, INSA Rouen, CNRS, Groupe de Physique des Matériaux, 76000 Rouen, France
Bertrand Radiguet
Affiliation:
Normandie Université, UNIROUEN, INSA Rouen, CNRS, Groupe de Physique des Matériaux, 76000 Rouen, France
Gerald Da Costa
Affiliation:
Normandie Université, UNIROUEN, INSA Rouen, CNRS, Groupe de Physique des Matériaux, 76000 Rouen, France
Fabien Delaroche
Affiliation:
Normandie Université, UNIROUEN, INSA Rouen, CNRS, Groupe de Physique des Matériaux, 76000 Rouen, France
Frederic Danoix
Affiliation:
Normandie Université, UNIROUEN, INSA Rouen, CNRS, Groupe de Physique des Matériaux, 76000 Rouen, France
*
*Author for correspondence: Francois Vurpillot, E-mail: [email protected]
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Abstract

This paper describes an alternative way to assign elemental identity to atoms collected by atom probe tomography (APT). This method is based on Bayesian assignation of label through the expectation–maximization method (well known in data analysis). Assuming the correct shape of mass over charge peaks in mass spectra, the probability of each atom to be labeled as a given element is determined, and is used to enhance data visualization and composition mapping in APT analyses. The method is particularly efficient for small count experiments with a low signal to noise ratio, and can be used on small subsets of analyzed volumes, and is complementary to single-ion decomposition methods. Based on the selected model and experimental examples, it is shown that the method enhances our ability to observe and extract information from the raw dataset. The experimental case of the superimposition of the Si peak and N peak in a steel is presented.

Keywords

atom probe tomographydata mininggeneral mixture modelsmass spectrum
Type
Data Analysis
Information
Microscopy and Microanalysis , Volume 25 , Special Issue 2: Atom Probe Tomography and Microscopy APT&M 2018 , April 2019 , pp. 367 - 377
Copyright
Copyright © Microscopy Society of America 2019 

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