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Abstract
Soft robotics is an emerging field enabled by advances in the development of soft materials with properties commensurate to their biological counterparts, for the purpose of reproducing locomotion and other distinctive capabilities of active biological organisms. The development of soft actuators is fundamental to the advancement of soft robots and bio-inspired machines. Among the different material systems incorporated in the fabrication of soft devices, ionic hydrogel–elastomer hybrids have recently attracted vast attention due to their favorable characteristics, including their analogy with human skin. Here, we demonstrate that this hybrid material system can be 3D printed as a soft dielectric elastomer actuator (DEA) with a unimorph configuration that is capable of generating high bending motion in response to an applied electrical stimulus. We characterized the device actuation performance via applied (i) ramp-up electrical input, (ii) cyclic electrical loading, and (iii) payload masses. A maximum vertical tip displacement of 9.78 ± 2.52 mm at 5.44 kV was achieved from the tested 3D printed DEAs. Furthermore, the nonlinear actuation behavior of the unimorph DEA was successfully modeled using an analytical energetic formulation and a finite element method (FEM).
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1-8 |
| Number of pages | 8 |
| Journal | Extreme Mechanics Letters |
| Volume | 21 |
| DOIs | |
| State | Published - May 2018 |
Bibliographical note
Publisher Copyright:© 2018 Elsevier Ltd
Keywords
- 3D printing
- Dielectric elastomer actuators
- Ionic hydrogels
- Soft actuators
- Soft robotics
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Dive into the research topics of '3D printed electrically-driven soft actuators'. Together they form a unique fingerprint.Projects
- 2 Finished
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University of Minnesota MRSEC (DMR-1420013)
Lodge, T. P. (PI)
11/1/14 → 10/31/20
Project: Research project
Datasets
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Supporting data for "3D printed electrically-driven soft actuators"
Haghiashtiani, G., Habtour, E., Park, S. H., Gardea, F. & McAlpine, M., Data Repository for the University of Minnesota, 2020
DOI: 10.13020/52fm-kj52, http://hdl.handle.net/11299/213918
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