Departamento de Fisica, Universidade Federal do Amazonas, 69077-000 Manaus, Brazil.
Universidade Federal do Amazonas, 69077-000 Manaus, Brazil.
Phys Rev E. 2019 Aug;100(2-1):022501. doi: 10.1103/PhysRevE.100.022501.
We study the relaxation dynamics of the polymer networks that are constructed based on a degree distribution specific to small-world networks. The employed building algorithm generates polymers with a large variety of architectures, thus allowing for a detailed study of the structural transition from a pure linear chain to dendritic polymer networks. This is done by varying a single parameter p, which measures the randomness in the degree of the network's nodes. The dynamics is investigated in the framework of the generalized Gaussian structures model by monitoring the influence of the parameter p and of the stiffness parameter q on the behavior of the relaxation quantities: averaged monomer displacement, storage modulus, and loss modulus. The structure properties of the constructed polymers are described by the mean-square radius of gyration. In the absence of stiffness, in the intermediate frequencies domain of the dynamical quantities we encounter different behaviours, such as a dendritic behavior followed by a linear one for very small values of p or a single well-marked dendritic behavior for higher values of p. The stiffness parameter q influences drastically the relaxation dynamics of these polymer networks and in general no evident scaling regions were encountered. However, for some values of the parameter set (p,q), such as (0.8,0.4), an extremely short constant slope region, less than one order of magnitude, was found.
我们研究了基于具有小世界网络特定度分布的聚合物网络的弛豫动力学。所采用的构建算法生成了具有多种结构的聚合物,从而可以详细研究从纯线性链到树突状聚合物网络的结构转变。这是通过改变一个单一的参数 p 来实现的,该参数衡量网络节点的度的随机性。通过监测参数 p 和刚度参数 q 对弛豫量(平均单体位移、储能模量和损耗模量)行为的影响,在广义高斯结构模型的框架内研究了动力学。构建聚合物的结构特性由均方回转半径描述。在没有刚度的情况下,在动态量的中间频率域中,我们遇到了不同的行为,例如对于非常小的 p 值,先是树突状行为,然后是线性行为,或者对于更高的 p 值,只有一个明显的树突状行为。刚度参数 q 极大地影响了这些聚合物网络的弛豫动力学,并且通常没有遇到明显的标度区域。然而,对于某些参数集(p,q)的值,例如(0.8,0.4),发现了一个极其短的常数斜率区域,小于一个数量级。