Data mining for isotope discrimination in atom probe tomography

TitleData mining for isotope discrimination in atom probe tomography
Publication TypeJournal Article
Year of Publication2013
AuthorsBroderick SR, Bryden A, Suram SK, Rajan K
Journal TitleUltramicroscopy
Volume132
Pages121-128
Date Published09
Type of ArticleArticle
ISBN Number0304-3991
Accession NumberWOS:000324235500021
KeywordsAtom probe tomography (APT), Data visualization, discrimination, Eigenvalue decomposition, energy, Kinetic energy, Principal component analysis (PCA), spectra
Abstract

Ions with similar time (TOP) can be discriminated by mapping their kinetic energy. While current generation position sensitive detectors have been considered insufficient for capturing the isotope kinetic energy, we demonstrate in this paper that statistical learning methodologies can be used to capture the kinetic energy from all or the parameters currently measured by mathematically transforming the signal. This approach works because the kinetic energy is sufficiently described by the descriptors on the potential, the material, and the evaporation process within atom probe tomography (APT). We discriminate the isotopes for Mg and Al by capturing the kinetic energy, and then decompose the TOF spectrum into its isotope components and identify the isotope for each individual atom measured. This work demonstrates the value of advanced data mining methods to help enhance the information resolution of the atom probe. (C) 2013 Elsevier By. All rights reserved.

URL<Go to ISI>://WOS:000324235500021
DOI10.1016/j.ultramic.2013.02.001