材料科学
聚合物
聚合物纳米复合材料
渗透(认知心理学)
纳米复合材料
纳米颗粒
粘弹性
渗流阈值
耗散颗粒动力学模拟
相图
粒子(生态学)
复合材料
相(物质)
纳米技术
电阻率和电导率
化学
地质学
工程类
电气工程
神经科学
有机化学
海洋学
生物
作者
Quan Chen,Shushan Gong,Joseph Moll,Dan Zhao,Sanat K. Kumar,Ralph H. Colby
出处
期刊:ACS Macro Letters
[American Chemical Society]
日期:2015-03-23
卷期号:4 (4): 398-402
被引量:205
标识
DOI:10.1021/acsmacrolett.5b00002
摘要
Nanometer-sized particles that are well dispersed in a polymer melt, presumably due to strongly favorable particle-polymer interactions, can form fractal structures via polymer bridging, leading ultimately to a nanoparticle (NP) network analogous to a colloidal gel. The linear viscoelastic response of polymer nanocomposites can be quantitatively predicted by a parameter-free model in which the stress is a simple sum of contributions from the polymer matrix and the fractal NP structure linked by bridging polymer chains. The NP contribution is modeled using critical percolation, while the polymer part is enhanced by the presence of particles, owing to hydrodynamic interactions. The phase diagram at the right shows that small NPs are needed to achieve the stronger reinforcement from glassy bridges at reasonable particle loadings.
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