Compression stiffening of fibrous networks with stiff inclusions

Abstract

Tissues commonly consist of cells embedded within a fibrous biopolymer network. Whereas cell-free reconstituted biopolymer networks typically soften under applied uniaxial compression, various tissues, including liver, brain, and fat, have been observed to instead stiffen when compressed. The mechanism for this compression stiffening effect is not yet clear. Here, we demonstrate that when a material composed of stiff inclusions embedded in a fibrous network is compressed, heterogeneous rearrangement of the inclusions can induce tension within the interstitial network, leading to a macroscopic crossover from an initial bending-dominated softening regime to a stretching-dominated stiffening regime, which occurs before and independently of jamming of the inclusions. Using a coarse-grained particle-network model, we first establish a phase diagram for compression-driven, stretching-dominated stress propagation and jamming in uniaxially compressed 2- and 3-dimensional systems. Then, we demonstrate that a more detailed computational model of stiff inclusions in a subisostatic semiflexible fiber network exhibits quantitative agreement with the predictions of our coarse-grained model as well as qualitative agreement with experiments.

References in corpus (4)

• Strain-induced alignment in collagen gels
• Elasticity of Stiff Polymer Networks
• The jamming transition and new percolation universality classes in particulate systems with attraction
• Actively stressed marginal networks

Cited by in corpus (7)

• Non-affine deformation of semiflexible polymer and fiber networks
• Elasticity-Controlled Jamming Criticality in Soft Composite Solids
• Complete mathematical theory of the jamming transition: A perspective
• Mechanics of fiber networks under a bulk strain
• Effective Medium Theory for Mechanical Phase Transitions of Fiber Networks
• Criticality enhances the reinforcement of disordered networks by rigid inclusions
• Geometry-Driven Mechanical Memory in a Random Fibrous Matrix