Mechanical Characterization of Nanocrystalline Materials via a Finite Element Nanoindentation Model
The difficulty of producing sufficient quantities of nanocrystalline materials for test specimens has led to an effort to explore alternative means for the mechanical characterization of small material volumes. In the present work, a numerical model simulating a nanoindentation test was developed us...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
MDPI AG
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/272c3902dea24e678df584bfb239985e |
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| Sumario: | The difficulty of producing sufficient quantities of nanocrystalline materials for test specimens has led to an effort to explore alternative means for the mechanical characterization of small material volumes. In the present work, a numerical model simulating a nanoindentation test was developed using Abaqus software. In order to implement the model, the principal material properties were used. The numerical nanoindentation results were converted to stress–strain curves through an inverse algorithm in order to obtain the macroscopic mechanical properties. For the validation of the developed model, nanoindentation tests were carried out in accordance with the ISO 14577. The composition of 75% wt. tungsten and 25% wt. copper was investigated by producing two batches of specimens with a coarse-grain microstructure with an average grain size of 150 nm and a nanocrystalline microstructure with a grain diameter of 100 nm, respectively. The porosity of both batches was derived to range between 9% and 10% based on X-ray diffraction analyses. The experimental nanoidentation results in terms of load–displacement curves show a good agreement with the numerical nanoindentation results. The proposed numerical technique combined with the inverse algorithm predicts the material properties of a fully dense, nanocrystalline material with very good accuracy, but it shows an appreciable deviation with the corresponding compression results, leading to the finding that the porosity effect is a crucial parameter which needs to be taken into account in the multiscale numerical methodology. |
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