Estimation of directional single crystal elastic properties from nano-indentation by correlation with EBSD and first-principle calculations
In this study, a two-step optimisation process for the estimation of the single crystal stiffness tensor from the indentation modulus is presented. This was accomplished by using a 2-dimensional data correlation method for nano-indentation, EBSD and ab initio data, as well as EDS for phase separatio...
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Elsevier
2023-10-01
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Series: | Materials & Design |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S0264127523007116 |
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author | Mattis Seehaus Sang-Hyeok Lee Tobias Stollenwerk Jeffrey M. Wheeler Sandra Korte-Kerzel |
author_facet | Mattis Seehaus Sang-Hyeok Lee Tobias Stollenwerk Jeffrey M. Wheeler Sandra Korte-Kerzel |
author_sort | Mattis Seehaus |
collection | DOAJ |
description | In this study, a two-step optimisation process for the estimation of the single crystal stiffness tensor from the indentation modulus is presented. This was accomplished by using a 2-dimensional data correlation method for nano-indentation, EBSD and ab initio data, as well as EDS for phase separation in a multi-phase material. Here, a single-phase Fe-24Ni-0.4C austenitic steel and a two-phase Fe-9.5Ni-0.5Co Seymchan meteorite were used as example materials.In a first step, the combination of high-speed nano-indentation mapping data with elemental and orientation distribution maps allowed the estimation of indentation moduli along specific crystal surface planes normal directions, (001), (011) and (111) using a least squares optimisation based on starting values from DFT or experimentally determined stiffness tensors. A second global optimisation step to estimate the single crystal stiffness tensor using pre-solved solution parameters of the Vlassak-Nix equations yielded reasonable correspondence between the experimentally determined stiffness tensors from correlative nano-indentation data and other methods. The presented method demonstrates generally the possibility to derive directionally sensitive elastic properties from high-speed nano-indentation for cubic materials statistically. |
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institution | Directory Open Access Journal |
issn | 0264-1275 |
language | English |
last_indexed | 2024-03-11T15:24:02Z |
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publisher | Elsevier |
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spelling | doaj.art-2be29e9693a74e9593be35b657781b0b2023-10-28T05:06:21ZengElsevierMaterials & Design0264-12752023-10-01234112296Estimation of directional single crystal elastic properties from nano-indentation by correlation with EBSD and first-principle calculationsMattis Seehaus0Sang-Hyeok Lee1Tobias Stollenwerk2Jeffrey M. Wheeler3Sandra Korte-Kerzel4Institut für Metallkunde und Materialphysik, RWTH Aachen University, 52074 Aachen, Germany; Corresponding author.Institut für Metallkunde und Materialphysik, RWTH Aachen University, 52074 Aachen, GermanyInstitut für Metallkunde und Materialphysik, RWTH Aachen University, 52074 Aachen, GermanyLaboratory of Metal Physics and Technology, Department of Materials, ETH Zürich, 8093 Zurich, Switzerland; FemtoTools AG, Furtbachstrasse 4, CH-8107 Buchs/ZH, SwitzerlandInstitut für Metallkunde und Materialphysik, RWTH Aachen University, 52074 Aachen, GermanyIn this study, a two-step optimisation process for the estimation of the single crystal stiffness tensor from the indentation modulus is presented. This was accomplished by using a 2-dimensional data correlation method for nano-indentation, EBSD and ab initio data, as well as EDS for phase separation in a multi-phase material. Here, a single-phase Fe-24Ni-0.4C austenitic steel and a two-phase Fe-9.5Ni-0.5Co Seymchan meteorite were used as example materials.In a first step, the combination of high-speed nano-indentation mapping data with elemental and orientation distribution maps allowed the estimation of indentation moduli along specific crystal surface planes normal directions, (001), (011) and (111) using a least squares optimisation based on starting values from DFT or experimentally determined stiffness tensors. A second global optimisation step to estimate the single crystal stiffness tensor using pre-solved solution parameters of the Vlassak-Nix equations yielded reasonable correspondence between the experimentally determined stiffness tensors from correlative nano-indentation data and other methods. The presented method demonstrates generally the possibility to derive directionally sensitive elastic properties from high-speed nano-indentation for cubic materials statistically.http://www.sciencedirect.com/science/article/pii/S0264127523007116Nano-indentationStiffness tensorLeast-squares optimisationAustenitic steelMeteoriteDFT |
spellingShingle | Mattis Seehaus Sang-Hyeok Lee Tobias Stollenwerk Jeffrey M. Wheeler Sandra Korte-Kerzel Estimation of directional single crystal elastic properties from nano-indentation by correlation with EBSD and first-principle calculations Materials & Design Nano-indentation Stiffness tensor Least-squares optimisation Austenitic steel Meteorite DFT |
title | Estimation of directional single crystal elastic properties from nano-indentation by correlation with EBSD and first-principle calculations |
title_full | Estimation of directional single crystal elastic properties from nano-indentation by correlation with EBSD and first-principle calculations |
title_fullStr | Estimation of directional single crystal elastic properties from nano-indentation by correlation with EBSD and first-principle calculations |
title_full_unstemmed | Estimation of directional single crystal elastic properties from nano-indentation by correlation with EBSD and first-principle calculations |
title_short | Estimation of directional single crystal elastic properties from nano-indentation by correlation with EBSD and first-principle calculations |
title_sort | estimation of directional single crystal elastic properties from nano indentation by correlation with ebsd and first principle calculations |
topic | Nano-indentation Stiffness tensor Least-squares optimisation Austenitic steel Meteorite DFT |
url | http://www.sciencedirect.com/science/article/pii/S0264127523007116 |
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