Geometry-Driven Mechanical Memory in a Random Fibrous Matrix
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arXiv
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| Format: | Preprint |
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2025
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| author | Sarkar, Mainak Laukaitis, Christina Johnson, Amy Wagoner |
| author_facet | Sarkar, Mainak Laukaitis, Christina Johnson, Amy Wagoner |
| contents | Disordered fibrous matrices, formed by the random assembly of fibers, provide the structural framework for many biological systems and biomaterials. Applied deformation modifies the alignment and stress states of constituent fibers, tuning the nonlinear elastic response of these materials. While it is generally presumed that fibers return to their original configurations after deformation is released, except when neighboring fibers coalesce or individual fibers yield, this reversal process remains largely unexplored. The intricate geometry of these matrices leaves an incomplete understanding of whether releasing deformation fully restores the matrix or introduces new microstructural deformation mechanisms. To address this gap, we investigated the evolution of matrix microstructures during the release of an applied deformation. Numerical simulations were performed on quasi-two-dimensional matrices of random fibers under localized tension, with fibers modeled as beams in finite element analysis. After tension release, the matrix exhibited permanent mechanical remodeling, with greater remodeling occurring at higher magnitudes of applied tension, indicative of the matrix preserving its loading history as mechanical memory. This response was surprising; it occurred despite the absence of explicit plasticity mechanisms, such as activation of inter-fiber cohesion or fiber yielding. We attributed the observed remodeling to the gradient in fiber alignment that developed within the matrix microstructure under applied tension, driving the subsequent changes in matrix properties during the release of applied tension. Therefore, random fibrous matrices tend to retain mechanical memory due to their intricate geometry. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_13409 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Geometry-Driven Mechanical Memory in a Random Fibrous Matrix Sarkar, Mainak Laukaitis, Christina Johnson, Amy Wagoner Soft Condensed Matter Materials Science Biological Physics Disordered fibrous matrices, formed by the random assembly of fibers, provide the structural framework for many biological systems and biomaterials. Applied deformation modifies the alignment and stress states of constituent fibers, tuning the nonlinear elastic response of these materials. While it is generally presumed that fibers return to their original configurations after deformation is released, except when neighboring fibers coalesce or individual fibers yield, this reversal process remains largely unexplored. The intricate geometry of these matrices leaves an incomplete understanding of whether releasing deformation fully restores the matrix or introduces new microstructural deformation mechanisms. To address this gap, we investigated the evolution of matrix microstructures during the release of an applied deformation. Numerical simulations were performed on quasi-two-dimensional matrices of random fibers under localized tension, with fibers modeled as beams in finite element analysis. After tension release, the matrix exhibited permanent mechanical remodeling, with greater remodeling occurring at higher magnitudes of applied tension, indicative of the matrix preserving its loading history as mechanical memory. This response was surprising; it occurred despite the absence of explicit plasticity mechanisms, such as activation of inter-fiber cohesion or fiber yielding. We attributed the observed remodeling to the gradient in fiber alignment that developed within the matrix microstructure under applied tension, driving the subsequent changes in matrix properties during the release of applied tension. Therefore, random fibrous matrices tend to retain mechanical memory due to their intricate geometry. |
| title | Geometry-Driven Mechanical Memory in a Random Fibrous Matrix |
| topic | Soft Condensed Matter Materials Science Biological Physics |
| url | https://arxiv.org/abs/2501.13409 |