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Data-Constrained Microstructure Characterization with Multispectrum X-Ray Micro-CT

Published online by Cambridge University Press:  03 May 2012

Sheridan C. Mayo ,
Andrew M. Tulloh ,
Adrian Trinchi  and
Sam Y.S. Yang
Sheridan C. Mayo*
Affiliation:
CSIRO Materials Science & Engineering, Private Bag 33, Clayton, Victoria 3169, Australia
Andrew M. Tulloh
Affiliation:
CSIRO Materials Science & Engineering, Private Bag 33, Clayton, Victoria 3169, Australia
Adrian Trinchi
Affiliation:
CSIRO Materials Science & Engineering, Private Bag 33, Clayton, Victoria 3169, Australia
Sam Y.S. Yang
Affiliation:
CSIRO Materials Science & Engineering, Private Bag 33, Clayton, Victoria 3169, Australia
*
Corresponding author. E-mail: [email protected]
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Abstract

Conventional X-ray microcomputed tomography (micro-CT) is not usually sufficient to determine microscopic compositional distributions as it is limited to measuring the X-ray attenuation of the sample, which for a given dataset can be similar for materials of different composition. In contrast, the present work enables three-dimensional compositional analysis with a data-constrained microstructure (DCM) modeling methodology, which uses two or more CT datasets acquired with different X-ray spectra and incorporates them as model constraints. For providing input data for DCM, we have also developed a method of micro-CT data collection that enables two datasets with different X-ray spectra to be acquired in parallel. Such data are used together with the DCM methodology to predict the distributions of corrosion inhibitor and filler in a polymer matrix. The DCM-predicted compositional microstructures have a reasonable agreement with energy dispersive X-ray images taken on the sample surface.

Keywords

microcomputed tomography (micro-CT)data-constrained modelingmultienergy X-ray
Type
Materials Applications
Information
Microscopy and Microanalysis , Volume 18 , Issue 3 , June 2012 , pp. 524 - 530
Copyright
Copyright © Microscopy Society of America 2012

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