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

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.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-FFF9-C Version Permalink: https://hdl.handle.net/21.11116/0000-000F-20F3-A

Genre: Journal Article

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Creators:
Saxena, Alaukik¹, Author
Polin, Nikita^{2, 3}, Author
Kusampudi, Navyanth⁴, Author
Katnagallu, Shyam^{2, 5}, Author
Molina-Luna, Leopoldo⁶, Author
Gutfleisch, Oliver⁷, Author
Berkels, Benjamin⁸, Author
Gault, Baptiste^{2, 9}, Author
Neugebauer, Jörg¹, Author
Freysoldt, Christoph⁵, Author

Affiliations:
1Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society, ou_1863337
2Atom Probe Tomography, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society, ou_1863384
3De magnete - Designing Magnetism on the atomic scale, MPG Group, Interdepartmental and Partner Groups, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society, ou_3260224
4Integrated Computational Materials Engineering, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society, ou_3069168
5Defect Chemistry and Spectroscopy, Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society, ou_1863342
6Department of Materials and Earth Sciences, Technische Universität Darmstadt, Peter-Grünberg-Straße 2, 64287 Darmstadt, Germany, ou_persistent22
7Functional Materials, Materials Science, Technical University of Darmstadt, 64287 Darmstadt, Germany, ou_persistent22
8Aachen Institute for Advanced Study in Computational Engineering Science (AICES), Aachen, Germany, ou_persistent22
9Department of Materials, Royal School of Mines, Imperial College London, Prince Consort Road, London SW7 2BP, UK, ou_persistent22

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Language(s): eng - English

Dates: Date issued: 2023-10

Publication Status: Issued

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Identifiers: DOI: 10.1093/micmic/ozad086

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Title: Microscopy and Microanalysis

Abbreviation : Microsc. Microanal.

Source Genre: Journal

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Publ. Info: New York, NY : Cambridge University Press

Pages: - Volume / Issue: 29 (5) Sequence Number: - Start / End Page: 1658 - 1670 Identifier: ISSN: 1431-9276
CoNE: https://pure.mpg.de/cone/journals/resource/991042731793414