Geometry-Driven Mechanical Memory in a Random Fibrous Matrix
Mainak Sarkar, Christina Laukaitis, Amy Wagoner Johnson

TL;DR
This study reveals that disordered fibrous matrices can retain mechanical memory through microstructural remodeling driven by fiber alignment gradients, even without plasticity mechanisms, impacting biological and biomaterial applications.
Contribution
It demonstrates that random fibrous matrices exhibit permanent mechanical remodeling and memory due to geometry-driven microstructural changes during tension release.
Findings
Matrix remodeling increases with higher tension levels.
Microstructural changes encode mechanical history.
Remodeling occurs without fiber yielding or cohesion activation.
Abstract
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…
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