Hatami-Marbini H
Department of Mechanical & Industrial Engineering, University of Illinois at Chicago, 60607, Chicago, IL, USA.
Eur Phys J E Soft Matter. 2018 May 24;41(5):65. doi: 10.1140/epje/i2018-11673-0.
Filamentous protein networks are broadly encountered in biological systems such as cytoskeleton and extracellular matrix. Many numerical studies have been conducted to better understand the fundamental mechanisms behind the striking mechanical properties of these networks. In most of these previous numerical models, the Mikado algorithm has been used to represent the network microstructure. Here, a different algorithm is used to create random fiber networks in order to investigate possible roles of architecture on the elastic behavior of filamentous networks. In particular, random fibrous structures are generated from the growth of individual fibers from random nucleation points. We use computer simulations to determine the mechanical behavior of these networks in terms of their model parameters. The findings are presented and discussed along with the response of Mikado fiber networks. We demonstrate that these alternative networks and Mikado networks show a qualitatively similar response. Nevertheless, the overall elasticity of Mikado networks is stiffer compared to that of the networks created using the alternative algorithm. We describe the effective elasticity of both network types as a function of their line density and of the material properties of the filaments. We also characterize the ratio of bending and axial energy and discuss the behavior of these networks in terms of their fiber density distribution and coordination number.
丝状蛋白质网络广泛存在于生物系统中,如细胞骨架和细胞外基质。为了更好地理解这些网络显著力学性能背后的基本机制,人们进行了许多数值研究。在大多数先前的数值模型中,使用了米卡多算法来表示网络微观结构。在此,使用一种不同的算法来创建随机纤维网络,以研究结构对丝状网络弹性行为的可能作用。具体而言,随机纤维结构是由单个纤维从随机成核点生长而产生的。我们使用计算机模拟来根据模型参数确定这些网络的力学行为。研究结果将与米卡多纤维网络的响应一起呈现和讨论。我们证明这些替代网络和米卡多网络表现出定性相似的响应。然而,与使用替代算法创建的网络相比,米卡多网络的整体弹性更硬。我们将两种网络类型的有效弹性描述为其线密度和细丝材料特性的函数。我们还表征了弯曲能与轴向能的比率,并根据它们的纤维密度分布和配位数讨论这些网络的行为。