Asymmetric Braided Artificial Muscles with Precise Electrothermal Actuation Control Enabled by Deep Learning.
Journal:
ACS applied materials & interfaces
Published Date:
May 30, 2025
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. 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 () 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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