Plant-inspired multi stimuli and multi temporal morphing composites

• Main Authors: Le Ferrand, Hortense, Riley, Katherine S., Arrieta, Andres F.
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Materials; Bioinspired; Morphing
• Online Access: https://hdl.handle.net/10356/157092
• Institution: Nanyang Technological University

Plants are inspiring models for adaptive, morphing systems. In addition to their shape complexity, they can respond to multiple stimuli and exhibit both fast and slow motion. We attempt to recreate these capabilities in synthetic structures, proposing a fabrication and design scheme for multi stimuli and multi temporal responsive plant-inspired composites. We leverage a hierarchical, spatially tailored microstructural and compositional scheme to enable both fast morphing through bistability and slow morphing through diffusion processes. The composites consisted of a hydrogel layer made of gelatine and an architected particle-reinforced epoxy bilayer. Using magnetic fields to achieve spatially distributed orientations of magnetically responsive platelets in each epoxy layer, complex bilayer architectural patterns in various geometries were realised. This feature enabled the study of plant-inspired complex designs, via finite element analysis and experiments. We present the design and fabrication strategy utilizing the material properties of the composites. The deformations and temporal responses of the resulting composites are analysed using digital image correlation. Finally, we model and experimentally demonstrate plant-inspired composite shells whose stable shapes closely mimic those of the Venus flytrap, while maintaining the multi stimuli and multi temporal responses of the materials. The key to achieve this is to tune the local in plane orientations of the reinforcing particles in the bilayer shapes, to induce distributed in plane mechanical properties and shrinkage. How these particles should be distributed is determined using finite element modelling. The work presented in this study can be applied to autonomous applications such as robotic systems.