Tuning the mechanical impedance of disordered networks for impact mitigation

Disordered-Network Mechanical Materials (DNMM), comprised of random arrangements of bonds and nodes, have emerged as mechanical metamaterials with the potential for achieving fine control over their mechanical properties. Recent computational studies have demonstrated this control whereby an extremely high degree of mechanical tunability can be achieved in disordered networks via a selective bond removal process called pruning. In this study, we experimentally demonstrate how pruning of a disordered network alters its macroscopic dynamic mechanical response and its capacity to mitigate impact. Impact studies with velocities ranging from 0.1 m s^-1 to 1.5 m s^-1 were performed, using a mechanical impactor and a drop tower, on 3D printed pruned and unpruned networks comprised of materials spanning a range of stiffness. High-speed videography was used to quantify the changes in Poisson's ratio for each of the network samples. Our results demonstrate that pruning is an efficient way to reduce the transmitted force and impulse from impact in the medium strain rate regime (10¹ s^-1 to 10² s^-1). This approach provides an interesting alternative route for designing materials with tailored impact mitigating properties compared to random material removal based on open cell foams.