Damage Mechanisms of Filled Siloxanes for Predictive Multiscale Modeling of Aging Behavior [electronic resource].
- Washington, D.C. : United States. Dept. of Energy, 2002.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
- Physical Description:
- PDF-FILE: 8 ; SIZE: 8.4 MBYTES pages
- Additional Creators:
- Lawrence Livermore National Laboratory
United States. Department of Energy
United States. Department of Energy. Office of Scientific and Technical Information
- Predictions of component performance versus lifetime are often risky for complex materials in which there may be many underlying aging or degradation mechanisms. In order to develop more accurate predictive models for silica-filled siloxane components, we are studying damage mechanisms over a broad range of size domains, linked together through several modeling efforts. Atomistic and molecular dynamic modeling has elucidated the chemistry of the silica filler to polymer interaction, as this interaction plays a key role in this material's aging behavior. This modeling work has been supported by experimental data on the removal of water from the silica surface, the effect of the surrounding polymer on this desiccation, and on the subsequent change in the mechanical properties of the system. Solid State NMR efforts have characterized the evolution of the polymer and filler dynamics as the material is damaged through irradiation or desiccation. These damage signatures have been confirmed by direct measurements of changes in polymer crosslink density and filler interaction as measured by solvent swelling, and by mechanical property tests. Data from the changes at these molecular levels are simultaneously feeding the development of age-aware constitutive models for polymer behavior. In addition, the microstructure of the foam, including under load, has been determined by Computed Tomography, and this data is being introduced into Finite Element Analysis codes to allow component level models. All of these techniques are directed towards the incorporation of molecular and microstructural aging signatures into predictive models for overall component performance.
- Published through SciTech Connect.
Materials Research Society National Meeting, San Francisco, CA (US), 04/01/2002--04/05/2002.
Maxwell, R; Gee, R; Dinh, L; Balazs, B; de Teresa, S.
- Funding Information:
View MARC record | catkey: 14107735