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A Machine Learning Approach to Cluster Characterization for Atom Probe Tomography

Published online by Cambridge University Press:  30 July 2021

Roland Bennett ,
Andrew Proudian  and
Jeramy Zimmerman
Roland Bennett
Affiliation:
Colorado School of Mines, GOLDEN, Colorado, United States
Andrew Proudian
Affiliation:
Colorado School of Mines, Physics, Golden, Colorado, United States
Jeramy Zimmerman
Affiliation:
Colorado School of Mines, Physics, GOLDEN, Colorado, United States

Abstract

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Type
Advanced Application of Atom Probe Tomography: Specimen preparation, Instrumentation, and Data analysis
Information
Microscopy and Microanalysis , Volume 27 , Supplement S1 , August 2021 , pp. 408 - 411
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

Jaskot, M.B. (2020), Linking Morphology to Electronic Properties in Small-Molecular Organic SemiconductorsGoogle Scholar
Deschamps, A, Pechiney-Centre de Recherches de Voreppe, & Brechet, Y. Influence of predeformation and ageing of an Al-Zn- Mg alloy. 2: Modeling of precipitation kinetics and yield stress. United States. doi:10.1016/S1359-6454(98)00296-1.Google Scholar
Hirata, A., Fujita, T., Wen, Y. R., Schneibel, J. H., Liu, C. T., & Chen, M. W. (2011). Atomic structure of nanoclusters in oxide- dispersion-strengthened steels. Nature Materials, 10(12), 922-926. https://doi.org/10.1038/nmat3150Google ScholarPubMed
Jägle, E., Choi, P., & Raabe, D. (2014). The Maximum Separation Cluster Analysis Algorithm for Atom-Probe Tomography: Parameter Determination and Accuracy. Microscopy and Microanalysis, 20(6), 1662-1671. doi:10.1017/S1431927614013294CrossRefGoogle ScholarPubMed
Vincent, G., Proudian, A.P., & Zimmerman, J. (2020). Three Dimensional Cluster Analysis for Atom Probe Tomography Using Ripley's K-function and Machine Learning.Google Scholar
Stephenson, Leigh T, Moody, Michael P, Liddicoat, Peter V, and Ringer, Simon P. New techniques for the analysis of fine-scaled clustering phenomena within atom probe tomography (apt) data. Microscopy and Microanalysis, 13(6):448–463, 2007.CrossRefGoogle Scholar
Vaumousse, D, Cerezo, A, and Warren, PJ. A procedure for quantification of precipitate microstructures from three-dimensional atom probe data. Ultramicroscopy, 95:215–221, 2003.CrossRefGoogle ScholarPubMed
Ceguerra, Anna V., Moody, Michael P., Stephenson, Leigh T., Marceau, Ross K.W. & Ringer, Simon P. (2010) A three- dimensional Markov field approach for the analysis of atomic clustering in atom probe data, Philosophical Magazine, 90:12, 1657-1683, DOI: 10.1080/14786430903441475CrossRefGoogle Scholar
Proudian, A.P.. Rapt: R for atom probe tomography. https://github.com/aproudian2/rapt, 2020.Google Scholar