What question did this study set out to answer?

The research aims to develop a light-driven swimming robot that adapts its movement based on environmental conditions.

March 28, 2026

3D‐Printed Dynamic Liquid Crystal Elastomer Composites with Adaptive Reconfiguration Showing Multimodal, Light‐Driven, Strider‐Inspired Locomotion at the Air–Water Interface

Key Points

The research aims to develop a light-driven swimming robot that adapts its movement based on environmental conditions.
3D printing of a liquid crystal elastomer swimming robot named OptiLCE Strider.
Incorporation of carbon nanotubes for photothermal effect and dynamic disulfide bonds for shape change.
Analysis of propulsion modes under varying light intensities.
Use of a qualitative phase map to guide locomotion decisions.
Energetic cost analysis for evaluating propulsion efficiency.
Demonstrated three propulsion modes with varying speeds based on light intensity.
Achieved continuous motion at speeds between 1.3-7.2 mm/s under low light.
Obtained pulsatile motion at speeds of 12.5-16.8 mm/s under high light.
Enabled flapping propulsion with deformation at speeds of 4.6-6.9 mm/s.
Exhibited versatility in tasks such as maze navigation, cargo handling, and programmed actions.

Abstract

Inspired by the environment-adaptive behaviors of water striders, we 3D-printed a light-driven liquid crystal elastomer (LCE) swimming robot, OptiLCE Strider, capable of multimodal locomotion and adaptive reconfiguration at the air-water interface. Utilizing carbon nanotubes (CNTs) as photothermal fillers and dynamic disulfide bonds for shape reconfigurability, the robot exhibits three distinct propulsion modes: Marangoni-effect-driven continuous motion under low light intensity (1.3-7.2 mm s- 1), steam-wave-induced pulsatile locomotion under high light intensity (12.5-16.8 mm s- 1), and flapping propulsion enabled by reversible LCE deformation (4.6-6.9 mm s- 1). The dynamic disulfide bonds enable exceptional structural reconfigurability and environmental adaptability for the LCE robot to execute complex tasks, including maze navigation, cargo capture/transport, programmable rotation, and light-powered jumping (escape from grounded or obstructed states via actuation energy storage/release, with jumping height/distance 6×/3.3× the robot length). The qualitative phase map guides locomotion mode selection, while energetic cost analysis reveals a clear force-efficiency trade off among the three modes, guiding application specific selection. This study highlights the potential of dynamic LCE-based robots for intelligent systems in liquid interface environments, paving the way for versatile applications in soft robotics and biomimetic engineering.

Bookmark

Cite This Study

Zhang et al. (Thu,) studied this question.

synapsesocial.com/papers/69c771198bbfbc51511e0ea7 https://doi.org/https://doi.org/10.1002/adma.202523039

Bookmark