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The microstructure of capsule containing self-healing materials: A micro-computed tomography study
Autonomic self-healing materials are materials with built-in (micro-) capsules or vessels, which upon fracturing release healing agents in order to recover the material's physical and mechanical properties. In order to better understand and engineer these materials, a thorough characterization...
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Published in: | Materials characterization 2016-09, Vol.119, p.99-109 |
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Main Authors: | , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Autonomic self-healing materials are materials with built-in (micro-) capsules or vessels, which upon fracturing release healing agents in order to recover the material's physical and mechanical properties. In order to better understand and engineer these materials, a thorough characterization of the material's microstructural behavior is essential and often overlooked. In this context, micro-computed tomography (μCT) can be used to investigate the three dimensional distribution and (de)bonding of (micro-) capsules in their native state in a polymer system with self-healing properties. Furthermore, in-situ μCT experiments in a self-healing polymer and a self-healing concrete system can elucidate the breakage and leakage behavior of (micro-) capsules at the micrometer scale. While challenges related to image resolution and contrast complicate the characterization in specific cases, non-destructive 3D imaging with μCT is shown to contribute to the understanding of the link between the microstructure and the self-healing behavior of these complex materials.
•μCT imaging allows for the analysis of microcapsule distribution patterns in self-healing materials.•μCT allows for qualitative and quantitative measurements of healing agent release from carriers in self-healing materials.•Experimental set-ups can be optimized by changing chemical compounds in the system to ensure maximum quality imaging. |
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ISSN: | 1044-5803 1873-4189 |
DOI: | 10.1016/j.matchar.2016.07.014 |