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ZENODO
Dataset . 2017
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2017
License: CC BY
Data sources: ZENODO
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Magnesium Az31 Hrdic Data Set

Authors: Orozco-Caballero, Alberto; Quinta da Fonseca, João; School of Materials;

Magnesium Az31 Hrdic Data Set

Abstract

This pack contains the data set obtained from the high-resolution digital image correlation (HRDIC) study of an AZ31 magnesium alloy. This data set can be visualised using the notebook (https://doi.org/10.5281/zenodo.376503), which can be used as a companion to out article entitled " Why magnesium is not brittle: a quantitative study on the accommodation of deformation incompatibility". Additionally, EBSD data set for the same region can be found in https://doi.org/10.5281/zenodo.345925. This data repository contains: AZ31.txt: correlation data. AZ31.npy: correlation data in binary iPython format. MSSPowerNorm.tif: high-resolution image of the effective shear strain using the data set and the iPython notebook. Patterning was performed using an in house styrene-assisted gold remodelling device producing gold speckles sizes in the range 20-40 nm. Backscattered electron images were obtained using a FEI Magellan HR 400L FE-SEM at a working distance of 3.2 mm, 1 kV, 0.8 nA beam current, using immersion mode and a beam deceleration with stage bias of 2 kV. Mosaics of 15x15 images were used to cover 135x120 µm2. Each tile is an image containing 2048 x 1768 pixels and has a horizontal field of view of 14.92 µm. The images were overlapped by 25% to enable easy stitching prior to the digital image correlation. Two mosaics were obtained, one before and one after deformation

Country
United Kingdom
Related Organizations
Keywords

Magnesium, high-resolution digital image correlation (HRDIC), slip,

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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