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Fabrication Process of Silicone-based Dielectric Elastomer Actuators
Published on: February 1, 2016
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Modelling dielectric elastomer circuit networks for soft biomimetics.
Luca Ciarella1, Katherine E Wilson1,2,3, A Richter1
1Institute of Semiconductors and Microsystems, TU Dresden, 01062 Dresden, Germany.
Bioinspiration & Biomimetics
|September 16, 2021
Summary
This study models soft electro-mechanical circuit networks using dielectric elastomers (DEs) for bio-inspired robots. The developed SIMULINK model accurately predicts DE circuit behavior, paving the way for advanced soft robotics.
Area of Science:
- Robotics and Materials Science
- Soft Actuators and Electroactive Polymers
Background:
- Fully soft electronic circuits are essential for creating entirely soft bio-inspired robots.
- Dielectric elastomers (DEs) are versatile electroactive polymers capable of actuation, sensing, and energy harvesting.
- Basic logic and memory functions have been demonstrated using DE actuators and switches.
Purpose of the Study:
- To develop a comprehensive SIMULINK model for soft electro-mechanical circuit networks composed of DEs.
- To integrate various mathematical models of DE behavior into a unified software representation.
- To demonstrate the model's validity for complex DE circuit networks.
Main Methods:
- Building a SIMULINK model incorporating the electro-mechanical behavior of DE logic units and their interconnections.
- Integrating existing mathematical models for DEs, overcoming limitations of single-aspect conventional models.
- Utilizing direct measurements to refine and validate the software representation of DE circuit networks.
Main Results:
- A comprehensive SIMULINK model for DE circuit networks was successfully developed.
- The model demonstrates qualitatively good prediction of device behavior, even with manual assembly variations.
- The study validates a recently introduced model for DE behavior and applies it to more complex circuits.
Conclusions:
- The developed model provides a robust software representation for DE circuit networks, essential for soft robotics.
- Despite current limitations in manual fabrication, the model shows significant predictive capability.
- Future improvements in materials and automated processes are expected to enhance model accuracy further.

