Auxeticity and stiffness of random networks: Lessons for the rational design of 3D printed mechanical metamaterials

<p>The emergence of advanced 3D printing techniques and the recent interest in architected materials have sparked a surge of interest in mechanical metamaterials whose unusual properties are defined by their highly ordered microarchitectures. Mechanical metamaterials with disordered microarchitectures have, however, not received as much attention despite their inherent advantages, such as robustness against the precise arrangement and design parameters of individual unit cells. Here, we computationally studied the elastic properties of two general types of disordered networks, namely, lattice-restricted and unrestricted networks that were made of beamlike elements and possessed mean connectivity values, Z, ranging between 2.5 and 7. We also additively manufactured a number of representative networks using selective laser sintering and showed that their deformations are consistent with our computational predictions. Unrestricted networks exhibited several advantages over the lattice-restricted ones including a broader range of achievable elastic modulus-Poisson's ratio duos as well as a higher probability of exhibiting auxetic and double-auxetic (i.e., auxetic behavior in both orthogonal directions) behaviors. Most interestingly, we could find unrestricted auxetic networks for high connectivity levels of up to 4.5, while no lattice-restricted auxetic networks were found for any connectivity level beyond 3.5. Given the fact that, according to Maxwell's criterion, 3.5 is the highest Z for which both of our lattice-restricted and unrestricted networks are bending-dominated, we concluded that unrestricted networks exhibit auxetic behavior well into their stretch-dominated domain. This is a promising observation that underlines the potential of unrestricted networks for the challenging task of designing stiff auxetic metamaterials in the stretch-dominated domain (i.e., Z = 4-4.5).