Asymmetric Braided Artificial Muscles with Precise Electrothermal Actuation Control Enabled by Deep Learning

Liquid crystal elastomers show promise for artificial muscles, but challenges remain in achieving excellent actuation performance and controllability under diverse operational conditions. This study presents a novel asymmetric braiding method using a Maypole braiding machine to integrate carbon nanotube yarns with liquid crystal elastomer fibers, producing an electrothermal fiber-shaped actuator. The actuator demonstrates exceptional performance in both air and water. In air, the actuator lifts 261 times its own weight (0.17 MPa) within 2.5 s, achieving a 45% contraction with a strain rate of 18%·s<sup>-1</sup>. Underwater, it reaches a 32% contraction within 3 s. To enhance controllability under diverse conditions, a long short-term memory (LSTM) model was proposed and applied, accurately predicting actuation strain with a coefficient of determination (<i>R</i><sup>2</sup>) of 0.994. Applications in a music robot and underwater claw highlight its potential for flexible robotics, validating its advantages in programmable control, rapid response, and adaptability across environments.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-05-30
DOI
https://doi.org/10.1021/acsami.5c05636
Citations
2
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
1.35

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article

Asymmetric Braided Artificial Muscles with Precise Electrothermal Actuation Control Enabled by Deep Learning

Siyi Bi, John D. W. Madden, Huiqi Shao, Yichen Yao et al.
2 citations
ACS Applied Materials & Interfaces
Advanced Sensor and Energy Harvesting Materials
1.35
article

Asymmetric Braided Artificial Muscles with Precise Electrothermal Actuation Control Enabled by Deep Learning

Siyi Bi, John D. W. Madden, Huiqi Shao, Yichen Yao, Jinhua Jiang, Nanliang Chen, Syed Rashedul Islam, Guangwei Shao, Wendi Wang, Xuan Wang, Chenglong Zhang, Ye Zhang
article en
2 citations

Abstract

Liquid crystal elastomers show promise for artificial muscles, but challenges remain in achieving excellent actuation performance and controllability under diverse operational conditions. This study presents a novel asymmetric braiding method using a Maypole braiding machine to integrate carbon nanotube yarns with liquid crystal elastomer fibers, producing an electrothermal fiber-shaped actuator. The actuator demonstrates exceptional performance in both air and water. In air, the actuator lifts 261 times its own weight (0.17 MPa) within 2.5 s, achieving a 45% contraction with a strain rate of 18%·s<sup>-1</sup>. Underwater, it reaches a 32% contraction within 3 s. To enhance controllability under diverse conditions, a long short-term memory (LSTM) model was proposed and applied, accurately predicting actuation strain with a coefficient of determination (<i>R</i><sup>2</sup>) of 0.994. Applications in a music robot and underwater claw highlight its potential for flexible robotics, validating its advantages in programmable control, rapid response, and adaptability across environments.

ACS Applied Materials & InterfacesVol. 17(23)
University of British Columbia (CA), Donghua University (CN), Uttara University (BD), Materials Modification (United States) (US), Materials Processing (United States) (US), State Key Laboratory for Modification of Chemical Fibers and Polymer Materials
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 20%
Advanced Sensor and Energy Harvesting Materials
1.35
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