Abstract
Plant motion patterns and structures have inspired designers, researchers and engineers for centuries. Recent advancements in analyzing and manufacturing technologies have allowed for a deeper understanding of biological principles and their application to bioinspired engineered systems. This has advanced 3D printing of thermoresponsive materials, like shape memory polymers. These materials enable the translation and creation of complex bioinspired mobile structures. In this study, we use novel 3D printable shape memory polymers in a multi-material, multilayer system to create double curved surfaces that can change their curvature from concave to convex, like the lobes of a Venus flytrap. The artificial trap lobes can be manufactured by identifying suitable material combinations, bonding methods and programming parameters. In this study, the system parameters to achieve a motion and the closing behavior in response to a temperature change are characterized. The resulting trap lobe represents a successful translation of the prestress ratios and layered morphology found in the biological model into an autonomous artificial Venus flytrap.
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Acknowledgement
Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC-2193/1 – 390951807. We thank the AG Technik of the Institute for Biology 2 of University of Freiburg for the construction of the biaxial stretching device. This work was supported by Fraunhofer Cluster of Excellence “Programmable Materials” under PSP elements 40-01922-2500-00002 and 40-03420-2500-00003. T.P. wishes to thank the European Regional Development Fund for financing a large part of the laboratory equipment (project 85007031).We thank Laura Mahoney from the livMatS Writer studio for spellchecking and improving the manuscript.
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Tauber, F.J., Scheckenbach, F., Walter, M., Pretsch, T., Speck, T. (2023). A 3D-Printed Thermoresponsive Artificial Venus Flytrap Lobe Based on a Multilayer of Shape Memory Polymers. In: Meder, F., Hunt, A., Margheri, L., Mura, A., Mazzolai, B. (eds) Biomimetic and Biohybrid Systems. Living Machines 2023. Lecture Notes in Computer Science(), vol 14157. Springer, Cham. https://doi.org/10.1007/978-3-031-38857-6_7
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