Research article Special Issues

Diversity of internal structures in inhibited epoxy primers

  • Received: 03 June 2015 Accepted: 27 September 2015 Published: 16 October 2015
  • Computed tomography is making a significant impact in the field of materials science in recent years. In this paper the authors report on advances made in three areas of characterization and also identified where further research needs to be focused. First we report on a new approach to data analysis called “Data Constrained Modelling (DCM)” in which compositional tomography can be undertaken rather than adsorption or phase contrast tomography. This is achieved by collecting X-ray CT data at different energies and then combining the datasets to reconstruct 3D compositional tomography. Second, on the application of this approach to inhibited primers typical of those used in the aerospace industry. Aerospace primers are effectively composite materials containing inorganic phases which are bound together with a polymer. Understanding the materials science of these systems requires information over several orders of magnitude in length-scale. In this paper we report on how DCM can be used to extend our understanding at the smaller length scales at the limits of resolution of the technique. The third and final advance is in extending the approach to include 4-dimensional studies. In this case we examine the primer before and after leaching. This process causes changes in the primer which can be both detected and quantified using the above approach.

    Citation: Anthony E. Hughes, Y. Sam Yang, Simon G. Hardin, Andrew Tulloh, Yudan Wang, You He. Diversity of internal structures in inhibited epoxy primers[J]. AIMS Materials Science, 2015, 2(4): 379-391. doi: 10.3934/matersci.2015.4.379

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  • Computed tomography is making a significant impact in the field of materials science in recent years. In this paper the authors report on advances made in three areas of characterization and also identified where further research needs to be focused. First we report on a new approach to data analysis called “Data Constrained Modelling (DCM)” in which compositional tomography can be undertaken rather than adsorption or phase contrast tomography. This is achieved by collecting X-ray CT data at different energies and then combining the datasets to reconstruct 3D compositional tomography. Second, on the application of this approach to inhibited primers typical of those used in the aerospace industry. Aerospace primers are effectively composite materials containing inorganic phases which are bound together with a polymer. Understanding the materials science of these systems requires information over several orders of magnitude in length-scale. In this paper we report on how DCM can be used to extend our understanding at the smaller length scales at the limits of resolution of the technique. The third and final advance is in extending the approach to include 4-dimensional studies. In this case we examine the primer before and after leaching. This process causes changes in the primer which can be both detected and quantified using the above approach.


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  • © 2015 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
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