2014
DOI: 10.1144/sp409.8
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Descriptive tools for the analysis of texture projects with large datasets using MTEX : strength, symmetry and components

Abstract: This paper presents the background for the calculation of various numbers that can be used to characterize crystal-preferred orientation (CPO), also known as texture in materials science, for large datasets using the combined scripting possibilities of MTEX and MatLab w . The paper is focused on three aspects in particular: the strength of CPO represented by orientation and misorientation distribution functions (ODFs, MDFs) or pole figures (PFs); symmetry of PFs and components of ODFs; and elastic tensors. The… Show more

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Cited by 256 publications
(255 citation statements)
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“…In any case, we document extremely weak LPOs considering the amount of strain accommodated. For instance, one would expect J > 10 and M > 0.3 for a gamma strain higher than 3 (Hansen et al, 2014;Mainprice et al, 2015), whereas we never quantify higher than J = 2 and M = 0.1, irrespective of the amount of finite strain. GBS.…”
Section: Olivine Fabric and Diffusion Creepcontrasting
confidence: 64%
“…In any case, we document extremely weak LPOs considering the amount of strain accommodated. For instance, one would expect J > 10 and M > 0.3 for a gamma strain higher than 3 (Hansen et al, 2014;Mainprice et al, 2015), whereas we never quantify higher than J = 2 and M = 0.1, irrespective of the amount of finite strain. GBS.…”
Section: Olivine Fabric and Diffusion Creepcontrasting
confidence: 64%
“…Densities of pole figures of the CPO were normalized to a uniform distribution and contoured at intervals of 0.5 × uniform. The BA-index was introduced by Mainprice et al (2014) to characterize the symmetry of olivine pole figures [100] and [010].…”
Section: Scanning Electron Microscope Based Electron Backscatter Diffmentioning
confidence: 99%
“…Unless otherwise specified, only the maps of the high-bulk-strain experiments w1092, w946 and w935 were analyzed (details in Heilbronner and Kilian, 2017). For data cleanup and processing, the MTEX toolbox by Ralf Hielscher was used (https://mtex-toolbox.github.io/; e.g., Bachmann et al, 2011;Mainprice et al, 2015). Single mis-indexed pixels were deleted and reconstructed together with single nonindexed pixels.…”
Section: Ebsd Data Processing and Analysismentioning
confidence: 99%