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Using nanoparticles to create self-healing composites
Abstract
The need for viable materials for optical communications, display technologies, and biomedical engineering is driving the creation of multilayer composites that combine brittle materials, such as glass, with moldable polymers. However, crack formation is a critical problem in composites where thin brittle films lie in contact with deformable polymer layers. Using computer simulations, we show that adding nanoparticles to the polymers yields materials in which the particles become localized at nanoscale cracks and effectively form “patches” to repair the damaged regions. Through micromechanics simulations, we evaluate the properties of these systems in the undamaged, damaged, and healed states and determine optimal conditions for harnessing nanoparticles to act as responsive, self-assembled “band aids” for composite materials. The results reveal situations where the mechanical properties of the repaired composites can potentially be restored to 75%–100% of the undamaged material.
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Cited by
Self-Healing Polymers and Composites
Blaiszik, B. J., Kramer, S. L. B., Olugebefola, S. C., Moore, J. S., Sottos, N. R., & White, S. R. (2010) · Annual Review of Materials Research · doi:10.1146/annurev-matsci-070909-104532 · Cited by 1,505
Metadata
- Authors
- Lee, J. Y., Buxton, G. A., & Balazs, A. C.
- Venue
- The Journal of Chemical Physics
- Publisher
- AIP Publishing
- Published
- 2004-09-15
- Volume
- 121
- Issue
- 11
- Pages
- 5531-5540
- ISSN
- 0021-9606 (ISSN-L)
- 1089-7690
- OpenAlex
- W1974520747
- Cited by
- 201
- References
- 0
- FWCI
- 6.35
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lee, J. Y., Buxton, G. A., & Balazs, A. C. (2004). Using nanoparticles to create self-healing composites. The Journal of Chemical Physics. https://doi.org/10.1063/1.1784432
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
