A Machine Learning Framework for Quantifying Chemical Segregation and 
Microstructural Features in Atom Probe Tomography Data

Saxena, Alaukik; Polin, Nikita; Kusampudi, Navyanth; Katnagallu, Shyam; Molina-Luna, Leopoldo; Gutfleisch, Oliver; Berkels, Benjamin; Gault, Baptiste; Neugebauer, Jörg; Freysoldt, Christoph

doi:10.1093/micmic/ozad086

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A Machine Learning Framework for Quantifying Chemical Segregation and Microstructural Features in Atom Probe Tomography Data

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Saxena, Alaukik
Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Polin, Nikita
Atom Probe Tomography, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;
De magnete - Designing Magnetism on the atomic scale, MPG Group, Interdepartmental and Partner Groups, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Kusampudi, Navyanth
Integrated Computational Materials Engineering, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Katnagallu, Shyam
Atom Probe Tomography, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;
Defect Chemistry and Spectroscopy, Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Gault, Baptiste
Atom Probe Tomography, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;
Department of Materials, Royal School of Mines, Imperial College London, Prince Consort Road, London SW7 2BP, UK;

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Neugebauer, Jörg
Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

/persons/resource/persons125143

Freysoldt, Christoph
Defect Chemistry and Spectroscopy, Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Saxena, A., Polin, N., Kusampudi, N., Katnagallu, S., Molina-Luna, L., Gutfleisch, O., et al. (2023). A Machine Learning Framework for Quantifying Chemical Segregation and Microstructural Features in Atom Probe Tomography Data. Microscopy and Microanalysis, 29(5), 1658-1670. doi:10.1093/micmic/ozad086.

Cite as: https://hdl.handle.net/21.11116/0000-000D-FFF9-C

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