TU Darmstadt / ULB / TUprints

Controllable helical deformations on printed anisotropic composite soft actuators

Wang, Dong ; Li, Ling ; Serjouei, Ahmad ; Dong, Longteng ; Weeger, Oliver ; Gu, Guoying ; Ge, Qi (2021):
Controllable helical deformations on printed anisotropic composite soft actuators. (Publisher's Version)
In: Applied Physics Letters, 112 (18), AIP, ISSN 0003-6951, e-ISSN 1077-3118,
DOI: 10.26083/tuprints-00019840,

Copyright Information: In Copyright.

Download (1MB) | Preview
Item Type: Article
Origin: Secondary publication service
Status: Publisher's Version
Title: Controllable helical deformations on printed anisotropic composite soft actuators
Language: English

Helical shapes are ubiquitous in both nature and engineering. However, the development of soft actuators and robots that mimic helical motions has been hindered primarily due to the lack of efficient modeling approaches that take into account the material anisotropy and the directional change of the external loading point. In this work, we present a theoretical framework for modeling controllable helical deformations of cable-driven, anisotropic, soft composite actuators. The framework is based on the minimum potential energy method, and its model predictions are validated by experiments, where the microarchitectures of the soft composite actuators can be precisely defined by 3D printing. We use the developed framework to investigate the effects of material and geometric parameters on helical deformations. The results show that material stiffness, volume fraction, layer thickness, and fiber orientation can be used to control the helical deformation of a soft actuator. In particular, we found that a critical fiber orientation angle exists at which the twist of the actuator changes the direction. Thus, this work can be of great importance for the design and fabrication of soft actuators with tailored deformation behavior.

Journal or Publication Title: Applied Physics Letters
Volume of the journal: 112
Issue Number: 18
Publisher: AIP
Classification DDC: 500 Naturwissenschaften und Mathematik > 530 Physik
600 Technik, Medizin, angewandte Wissenschaften > 600 Technik
600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften
Divisions: 16 Department of Mechanical Engineering > Cyber-Physical Simulation (CPS)
Date Deposited: 15 Dec 2021 10:24
Last Modified: 15 Dec 2021 10:24
DOI: 10.26083/tuprints-00019840
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-198409
Additional Information:



URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/19840
Actions (login required)
View Item View Item