Mechanics of transient semi-flexible networks: Soft-elasticity, stress relaxation and remodeling
Mechanics of transient semi-flexible networks: Soft-elasticity, stress relaxation and remodeling
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DOI：
10.1016/j.jmps.2022.104776
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发表时间：
2022-01-21
影响因子：
5.3
通讯作者：
Vernerey，Franck J.
中科院分区：
文献类型：
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作者：
Vernerey，Franck J.
由柔性链交联的半柔性（或无热）细丝的网络存在于各种生物聚合物中，例如软结缔组织、细胞的细胞骨架或植物细胞壁。它们也可以在实验室中合成，以产生液晶凝胶状凝胶以及组织模拟物。虽然这些网络的弹性已被探索，源于可逆和动态交联的存在的粘弹性响应仍然知之甚少。在这里，我们通过多尺度统计力学方法为这些网络开发了一个模型，其中网络被分解为最基本的构建块：弹性杆（描述半柔性细丝）和用于交联它们的柔性链。该组装体的拓扑结构由一个毛杆模型表示，我们表达了非仿射运动学，以及交联剂和杆构象的演化方程。这个毛杆的机械响应，然后表示为一个弹性的潜力，是建立作为其组件的基本弹性的函数。由此产生的模型是能够捕捉到的力学这样的网络，包括非线性弹性（特别是液晶类软弹性响应），蠕变和应力松弛，以及速率和历史相关的网络重塑的显着特征。因此，该理论可以用于更好地理解这些复杂但无处不在的网络的丰富响应，并指导它们在实验室中的发展。
Networks of semi-flexible (or athermal) filaments cross-linked by flexible chains are found in a variety of biopolymers such as soft connective tissues, the cell’s cytoskeleton or the wall of plant cells. They can also be synthetized in the lab to create liquid crystal elastomers-like gels as well as tissue mimetics. While the elasticity of these networks has been explored, the visco-elastic response that originate from the existence of reversible and dynamic cross-links is still poorly understood. We here develop a model for these networks by taking a multiscale, statistical mechanics approach where the network is decomposed into its most basic building blocks: elastic rods (to describe semi-flexible filaments) and the flexible chains used to cross-link them. The topology of this assembly is represented by ahairy rodmodel for which we express the non-affine kinematics, and evolution equations for both cross-linkers and rods conformation. The mechanical response of this hairy rod is then expressed by an elastic potential that is built as a function of the basic elasticity of its components. The resulting model is able to capture salient features of the mechanics of such networks, including nonlinear elasticity (and in particular a liquid crystal-like soft-elastic response), creep and stress relaxation, as well as rate- and history-dependent network remodeling. The theory can thus be potentially used to better understand the rich response of these complex, yet ubiquitous networks and guide their development in the laboratory.