Shen Jianxiang, Liu Jun, Gao Yangyang, Li Xiaolin, Zhang Liqun
Key Laboratory of Beijing City on Preparation and Processing of Novel Polymer Materials, Beijing University of Chemical Technology, Beijing 100029, P. R. China.
Soft Matter. 2014 Jul 28;10(28):5099-113. doi: 10.1039/c4sm00233d.
By setting up a coarse-grained model of polymer nanocomposites, we monitored the change in the elastic modulus as a function of the strain, derived from the stress-strain behavior by determining uniaxial tension and simple shear of two typical spatial distribution states (aggregation and dispersion) of nanoparticles (NPs). In both these cases, we observed that the elastic modulus decreases non-linearly with the increase of strain and reaches a low plateau at larger strains. This phenomenon is similar to the so-called "Payne effect" for elastomer nanocomposites. Particularly, the modulus of the aggregation case is more sensitive to the imposed strain. By examining the structural parameters, such as the number of neighboring NPs, coordination number of NPs, root-mean-squared average force exerted on the NPs, local strain, chain conformations (bridge, dangle, loop, interface bead and connection bead), and the total interaction energy of NP-polymer and NP-NP, we inferred that the underlying mechanism of the aggregation case is the disintegration of the NP network or clusters formed through direct contact; however, for the dispersion case, the non-linear behavior is attributed to the destruction of the NP network or clusters formed through the bridging of adsorbed polymer segments among the NPs. The former physical network is influenced by NP-NP interaction and NP volume fraction, while the latter is influenced by NP-polymer interaction and NP volume fraction. Lastly, we found that for the dispersion case, further increasing the inter-particle distance or grafting NPs with polymer chains can effectively reduce the non-linear behavior due to the decrease of the physical network density. In general, this simulation work, for the first time, establishes the correlation between the micro-structural evolution and the strain-induced non-linear behavior of polymer nanocomposites, and sheds some light on how to reduce the "Payne effect".
通过建立聚合物纳米复合材料的粗粒度模型,我们监测了弹性模量随应变的变化,该变化源自通过确定纳米颗粒(NPs)两种典型空间分布状态(聚集和分散)的单轴拉伸和简单剪切的应力-应变行为。在这两种情况下,我们观察到弹性模量随应变增加而非线性降低,并在较大应变时达到低平台期。这种现象类似于弹性体纳米复合材料的所谓“佩恩效应”。特别地,聚集情况下的模量对应变更为敏感。通过检查诸如相邻纳米颗粒的数量、纳米颗粒的配位数、施加在纳米颗粒上的均方根平均力、局部应变、链构象(桥连、悬垂、环、界面珠和连接珠)以及纳米颗粒-聚合物和纳米颗粒-纳米颗粒的总相互作用能等结构参数,我们推断聚集情况的潜在机制是通过直接接触形成的纳米颗粒网络或团簇的解体;然而,对于分散情况,非线性行为归因于通过纳米颗粒之间吸附的聚合物链桥连形成的纳米颗粒网络或团簇的破坏。前者物理网络受纳米颗粒-纳米颗粒相互作用和纳米颗粒体积分数影响,而后者受纳米颗粒-聚合物相互作用和纳米颗粒体积分数影响。最后,我们发现对于分散情况,进一步增加颗粒间距离或用聚合物链接枝纳米颗粒可由于物理网络密度降低而有效减少非线性行为。总体而言,这项模拟工作首次建立了聚合物纳米复合材料微观结构演变与应变诱导非线性行为之间的相关性,并为如何降低“佩恩效应”提供了一些启示。