Chen Quan, Gong Shushan, Moll Joseph, Zhao Dan, Kumar Sanat K, Colby Ralph H
Department of Materials Science and Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States.
Department of Chemical Engineering, Columbia University, 500 West 120th Street, New York, New York 10027, United States.
ACS Macro Lett. 2015 Apr 21;4(4):398-402. doi: 10.1021/acsmacrolett.5b00002. Epub 2015 Mar 23.
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.
纳米尺寸的颗粒很好地分散在聚合物熔体中，据推测这是由于颗粒与聚合物之间存在强烈的有利相互作用，这些颗粒可以通过聚合物桥连形成分形结构，最终形成类似于胶体凝胶的纳米颗粒（NP）网络。聚合物纳米复合材料的线性粘弹性响应可以通过一个无参数模型进行定量预测，在该模型中，应力是聚合物基体和由桥连聚合物链连接的分形NP结构贡献的简单总和。NP的贡献通过临界渗流进行建模，而聚合物部分由于流体动力学相互作用，因颗粒的存在而得到增强。右侧的相图表明，在合理的颗粒负载量下，需要小尺寸的NP才能通过玻璃态桥连实现更强的增强效果。
