Abstract Fiber networks are the primary structural components of many biological structures, including the cell cytoskeleton and the extracellular matrix. These materials exhibit global nonlinearities, such as stiffening in extension and shear, during which the fibers bend and align with the direction of applied loading. Precise details of deformations at the scale of the fibers during strain stiffening are still lacking, however, as prior work has studied fiber alignment primarily from a qualitative perspective, which leaves incomplete the understanding of how the local microstructural evolution leads to the global mechanical behavior. To fill this gap, we studied how axial forces are transmitted inside the fiber network along paths called force chains, which continuously evolve during the course of deformation. We performed numerical simulations on two-dimensional networks of random fibers under uniaxial extension and shear, modeling the fibers using beam elements in finite element software. To quantify the force chains, we identified all chains of connected fibers for which the axial force was larger than a preset threshold and computed the total length of all such chains. To study the evolution of force chains during loading, we computed the derivative of the total length of all force chains with respect to the applied engineering strain. Results showed that the highest rate of evolution of force chains coincided with the global critical strain for strain stiffening of the fiber network. Therefore, force chains are an important factor connecting understanding of the local kinematics and force transmission to the macroscale stiffness of the fiber network.
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This content will become publicly available on August 1, 2024
Bioinspired Fiber Networks With Tunable Mechanical Properties by Additive Manufacturing
Abstract Soft bioinspired fiber networks offer great potential in biomedical engineering and material design due to their adjustable mechanical behaviors. However, existing strategies to integrate modeling and manufacturing of bioinspired networks do not consider the intrinsic microstructural disorder of biopolymer networks, which limits the ability to tune their mechanical properties. To fill in this gap, we developed a method to generate computer models of aperiodic fiber networks mimicking type I collagen ready to be submitted for additive manufacturing. The models of fiber networks were created in a scripting language wherein key geometric features like connectivity, fiber length, and fiber cross section could be easily tuned to achieve desired mechanical behavior, namely, pretension-induced shear stiffening. The stiffening was first predicted using finite element software, and then a representative network was fabricated using a commercial 3D printer based on digital light processing technology using a soft resin. The stiffening response of the fabricated network was verified experimentally on a novel test device capable of testing the shear stiffness of the specimen under varying levels of uniaxial pretension. The resulting data demonstrated clear pretension-induced stiffening in shear in the fabricated network, with uniaxial pretension of 40% resulting in a factor of 2.65 increase in the small strain shear stiffness. The strategy described in this article addresses current challenges in modeling bioinspired fiber networks and can be readily integrated with advances in fabrication technology to fabricate materials truly replicating the mechanical response of biopolymer networks.
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- Award ID(s):
- 1749400
- NSF-PAR ID:
- 10422331
- Date Published:
- Journal Name:
- Journal of Applied Mechanics
- Volume:
- 90
- Issue:
- 8
- ISSN:
- 0021-8936
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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