Mapping the Mesoscale Interface Structure in Polycrystalline Materials

Wu, Chunzhi; Adams, Brent L.; Bauer, C.; Casasent, David P.; Morawiec, Adam; Özdemir, Serhat; Talukder, Ashit

doi:10.1017/s1431927600014628

Cited by 4 publications

(3 citation statements)

References 3 publications

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“…This approach would not be possible with classical EBSD because a complete scan has to be done first before knowing the contours of all the grains. However, some interesting solutions have been proposed to determine the position of the grain boundaries using the forward-scatter detectors installed around the EBSD screen (FSD diodes) [29], the EBSD screen itself as a detector [30] or using a scanning mesh refinement technique [2,31].…”

Section: Discussionmentioning

confidence: 99%

Crystal orientation mapping via ion channeling: An alternative to EBSD

Langlois¹,

Douillard²,

Yuan³

et al. 2015

Ultramicroscopy

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A new method, which we name ion CHanneling ORientation Determination (iCHORD), is proposed to obtain orientation maps on polycrystals via ion channeling. The iChord method exploits the dependence between grain orientation and ion beam induced secondary electron image contrast. At each position of the region of interest, intensity profiles are obtained from a series of images acquired with different orientations with respect to the ion beam. The profiles are then compared to a database of theoretical profiles of known orientation. The Euler triplet associated to the most similar theoretical profile gives the orientation at that position. The proof-of-concept is obtained on a titanium nitride sample. The potentialities of iCHORD as an alternative to EBSD are then discussed.

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Section: Discussionmentioning

confidence: 99%

Crystal orientation mapping via ion channeling: An alternative to EBSD

Langlois¹,

Douillard²,

Yuan³

et al. 2015

Ultramicroscopy

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“…This motivated the acquisition of the preliminary undistorted and undeformed reference (Fig. 1, (3)) since it allows for a spatial distortion correction of EBSD data as proposed by [23][24][25]. To reduce spatial distortions in the reference SEM image (3) and SEM image after fatigue (7), high magnifications, long dwell times, and low working distances were utilized here as suggested by [26].…”

Section: Specimen Fabrication and Characterizationmentioning

confidence: 99%

Efficient Experimental and Data-Centered Workflow for Microstructure-Based Fatigue Data

et al. 2021

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Background Early fatigue mechanisms for various materials are yet to be unveiled for the (very) high-cycle fatigue (VHCF) regime. This can be ascribed to a lack of available data capturing initial fatigue damage evolution, which continues to adversely affect data scientists and computational modeling experts attempting to derive microstructural dependencies from small sample size data and incomplete feature representations. Objective The aim of this work is to address this lack and to drive the digital transformation of materials such that future virtual component design can be rendered more reliable and more efficient. Achieving this relies on fatigue models that comprehensively capture all relevant dependencies. Methods To this end, this work proposes a combined experimental and data post-processing workflow to establish multimodal fatigue crack initiation and propagation data sets efficiently. It evolves around fatigue testing of mesoscale specimens to increase damage detection sensitivity, data fusion through multimodal registration to address data heterogeneity, and image-based data-driven damage localization. Results A workflow with a high degree of automation is established, that links large distortion-corrected microstructure data with damage localization and evolution kinetics. The workflow enables cycling up to the VHCF regime in comparatively short time spans, while maintaining unprecedented time resolution of damage evolution. Resulting data sets capture the interaction of damage with microstructural features and hold the potential to unravel a mechanistic understanding. Conclusions The proposed workflow lays the foundation for future data mining and data-driven modeling of microstructural fatigue by providing statistically meaningful data sets extendable to a wide range of materials.

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“…Second, each sample (also called the representative volume element or RVE) is expected to be sufficiently large in size so that the measured distributions from the different samples of the ensemble are sufficiently close to each other (within a specified acceptable tolerance). Third, because most measurement probes used are unable to interrogate the interior of a material, one has to either employ stereology principles on a set of judiciously selected 2D sections of the sample [29] or recent advances in automated serial sectioning [30][31][32] to reconstruct the internal structure of the material, and then extract the distributions (described earlier) from those reconstructions. The recent advances in 3D X-ray tomography offer tremendous promise in this regard [33,34].…”

Section: Statistical Description Of the Spatial Correlation Of The Local Statementioning

confidence: 99%

Application of the Spectral Methods of Microstructure Design to Continuous Fiber-reinforced Composites

Kalidindi

Houskamp

2007

Journal of Composite Materials

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A new mathematical framework called microstructure-sensitive design (MSD) has recently been developed to facilitate solutions to inverse problems in microstructure design, where the goal is to identify the complete set of relevant microstructures that are theoretically predicted to satisfy a set of designer-specified criteria on effective properties or performance. This methodology has been applied previously to a few design-related case studies, mainly involving polycrystalline metals. This article describes the first application of MSD methodology to customized design of continuous fiber-reinforced composites for specified combinations of performance criteria. The main contribution of this study is that it presents a novel but simple mathematical framework for the application of first-order MSD to the design problems involving continuous fiber-reinforced composites. In the examples presented in this article, elementary first-order theories spanning two length scales have been selected to obtain effective properties of continuous fiber-reinforced composite material systems. Having selected these first-order theories, the authors proceed to demonstrate the viability of applying the first-order MSD framework to design the case studies in continuous fiber-reinforced composites.

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Mapping the Mesoscale Interface Structure in Polycrystalline Materials

Cited by 4 publications

References 3 publications

Crystal orientation mapping via ion channeling: An alternative to EBSD

Crystal orientation mapping via ion channeling: An alternative to EBSD

Efficient Experimental and Data-Centered Workflow for Microstructure-Based Fatigue Data

Application of the Spectral Methods of Microstructure Design to Continuous Fiber-reinforced Composites

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