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Unsupervised clustering of nanoindentation data for microstructural reconstruction: Challenges in phase discrimination

MPS-Authors
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Jentner,  Robin
Nano-/ Micromechanics of Materials, Structure and Nano-/ Micromechanics of Materials, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Gallardo-Basile,  Francisco-José
Theory and Simulation, Microstructure Physics and Alloy Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Best,  James P.
Mechanics at Chemical Interfaces, Structure and Nano-/ Micromechanics of Materials, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Kirchlechner,  Christoph
Nano-/ Micromechanics of Materials, Structure and Nano-/ Micromechanics of Materials, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;
Institute for Applied Materials (IAM-WBM), Karlsruhe Institute of Technology (KIT), Eggenstein-Leopoldshafen D-76344, Germany;

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Dehm,  Gerhard
Structure and Nano-/ Micromechanics of Materials, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society;

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Citation

Jentner, R., Srivastava, K., Scholl, S., Gallardo-Basile, F.-J., Best, J. P., Kirchlechner, C., et al. (2023). Unsupervised clustering of nanoindentation data for microstructural reconstruction: Challenges in phase discrimination. Materialia, 28: 101750. doi:10.1016/j.mtla.2023.101750.


Cite as: https://hdl.handle.net/21.11116/0000-000D-037A-7
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