Abnormal stiffness behaviour in artificial cactus-inspired reinforcement materials

Bioinspir Biomim. 2020 Dec 24;16(2). doi: 10.1088/1748-3190/abc1f2.

Abstract

Cactus fibres have previously shown unusual mechanical properties in terms of bending and axial stiffness due to their hierarchical structural morphology. Bioinspiration from those cactus fibres could potentially generate architected materials with exciting properties. To that end we have built bioinspired artificial analogues of cactus fibres to evaluate their mechanical properties. We have generated 3D printed specimens from rendered models of the cactus structure using two different printing techniques to assess the reproducibility of the structural topology. Bioinspired additive manufactured materials with unusual mechanical properties constitute an ever-evolving field for applications ranging from novel wing designs to lightweight plant-inspired analogues. The cactus-inspired 3D printed specimens developed here demonstrate an unusually high bending to axial stiffness ratios regardless of the manufacturing method used. Moreover, when compared to their equivalent beam analogues the cactus specimens demonstrate a significant potential in terms of specific (weight averaged) flexural modulus. Imaging of the artificial cactus reinforcements has enabled the generation of a one-dimensional reduced order finite element model of the cactus structure, with a distribution of cross sections along the length that simulate the inertia and mechanical behaviour of the cactus topology. The novel bioinspired material structure shows an excellent reproducibility across different manufacturing methods and suggest that the tree-like topology of the cactus fibre could be very suited to applications where high bending to axial stiffness ratios are critical.

Keywords: 3D printing; bioinspiration; cactus; finite element; mechanical testing.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomimetic Materials*
  • Cactaceae*
  • Printing, Three-Dimensional
  • Reproducibility of Results