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Selaginella lepidophylla-Inspired Multi-Stimulus Cooperative Control MXene-Based Flexible Actuator.
Xiang Li1, Ze Wu1, Bingjue Li1
1Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, School of Mechanical Engineering, Southeast University, Nanjing, People's Republic of China.
Soft Robotics
|June 19, 2023
Summary
Researchers developed a new flexible actuator inspired by plants, using a gradient structure for predictable bending and multi-stimulus control. This bionic design offers high stability for advanced flexible robots.
Area of Science:
- Robotics
- Materials Science
- Biomimetics
Background:
- Achieving predictable bending, high cycle stability, and complex motion in flexible robots remains a challenge.
- The humidity response of *Selaginella lepidophylla* offers inspiration for novel actuator designs.
Purpose of the Study:
- To develop a new multilevel assisted assembly strategy for constructing flexible actuators.
- To create MXene-CoFe2O4 (MXCFO) actuators with concentration gradients for predictable deformation and multi-stimulus control.
- To investigate the relationship between gradient changes and actuator bending ability.
Main Methods:
- A novel multilevel assisted assembly strategy was employed.
- MXene-CoFe2O4 (MXCFO) flexible actuators with varying concentration gradients were constructed.
- The actuators' bending deformation, cycle stability, and interlayer bonding were evaluated.
Main Results:
- The bionic gradient structured actuator exhibited uniform thickness and high cycle stability, maintaining excellent interlayer bonding after 100 bending cycles.
- A clear link was established between gradient changes and the actuator's bending deformation capability.
- The actuators demonstrated predictable bending deformation and multi-stimulus cooperative control.
Conclusions:
- The developed bionic gradient structure and multi-stimulus control strategy show significant potential for future flexible robot design.
- The actuators successfully realized conceptual models for humidity monitoring, climbing, grasping, cargo transportation, and drug delivery.
- This approach offers a promising pathway for creating advanced, responsive flexible robotic systems.
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