Unsupervised learning of nanoindentation data to infer microstructural details of complex materials
In this study, Cu-Cr composites were studied by nanoindentation. Arrays of indents were placed over large areas of the samples resulting in datasets consisting of several hundred measurements of Young’s modulus and hardness at varying indentation depths. The unsupervised learning technique, Gaussian...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2024-12-01
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| Series: | Frontiers in Materials |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmats.2024.1440608/full |
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