Plant‐Inspired Soft Bistable Structures Based on Hygroscopic Electrospun Nanofibers. Issue 4 (15th January 2020) - Lunni, Dario; Cianchetti, Matteo; Filippeschi, Carlo; Sinibaldi, Edoardo; Mazzolai, Barbara
Abstract: The tissue composition and microstructures of plants have dynamic morphologies that change according to their environments. Recently, multifunctional responsive materials and smart structures also took inspiration from these plants' features. Dionaea muscipula leaves provide a remarkable example of an optimized structure that, owing to the synergistic integration of bistability, material, and geometrical properties, permits to overcome the performance limits of purely diffusive processes. In this paper, a hygroscopic bistable structure (HBS) inspired by the Venus flytrap leaves is presented, obtained by bonding prestretched poly(dimethylsiloxane) (PDMS) layers prior to depositing electrospun polyethylene oxide (PEO) nanofibers. A hygroresponsive bilayer (HBL) is also obtained by electrospinning of PEO on an unstretched PDMS layer. The hygroscopic material (Young's modulus and hygroscopic expansion) is mechanically characterized so as to predict the response time of a bending HBL in response to a step humidity variation. The HBS response time (≈1 s) is sensibly lower than the one of purely diffusive HBL (≈10 s) thanks to bistability. An illustrative implementation is also presented, exploiting an HBS to trigger the curvature of a PDMS optical focusing system. The developed plant‐inspired soft bistable structure can also be used for sensing (e.g., humidity), energy harvesting, as well as advanced soft robotics applications. Abstract : This paper presents hygroresponsive bistable structures inspired by Dionaea muscipula, obtained by electrospinning polyethylene oxide nanofibers on poly(dimethylsiloxane). In response to a step humidity variation, they exhibit a quick response (≈1 s, sensibly shorter than the one underlying purely diffusive hygroscopic bilayers), which can be used for integrated actuation/sensing, e.g., for soft robotics.