Shaping and Locomotion of Soft Robots Using Filament Actuators Made from Liquid Crystal Elastomer–Carbon Nanotube Composites

Abstract

Soft robots, with their agile locomotion and responsiveness to environment, have attracted great interest in recent years. Liquid crystal elastomers (LCEs), known for their reversible and anisotropic deformation, are promising candidates as embedded intelligent actuators in soft robots. So far, most studies on LCEs have focused on achieving complex deformation in thin films over centimeter‐scale areas with relatively small specific energy densities. Herein, using an extrusion process, meter‐long LCE composite filaments that are responsive to both infrared light and electrical fields are fabricated. In the composite filaments, a small quantity of cellulose nanocrystals (CNCs) is incorporated to facilitate the alignment of liquid crystal molecules along the long axis of the filament. Up to 2 wt% carbon nanotubes (CNTs) is introduced into a LCE matrix without aggregation, which in turn greatly improves the mechanical property of filaments and their actuation speed, where the Young's modulus along the long axis reaches 40 MPa, the electrothermal response time is within 10 s. The maximum work capacity is 38 J kg−1 with 2 wt% CNT loading. Finally, shape transformation and locomotion in several soft robotics systems achieved by the dual‐responsive LCE/CNT composite filament actuators are demonstrated.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 18, 2020
Source ID
10.1002/aisy.201900163

Entities

People

  • Chinedum Osuji
  • Haihuan Wang
  • Jiaqi Liu
  • Ryan Poling-skutvik
  • Shu Yang
  • Yuchong Gao

Organizations

  • Army Research Office
  • National Science Foundation
  • University of Pennsylvania

Tags

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Mechanical Engineering/Mechanics of Materials.
  • Nanocomposite Materials Science

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy