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Piezoelectric-driven self-sensing leaf-mimic actuator enabled by integration of a self-healing dielectric elastomer and a piezoelectric composite
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Pan, Min, Yuan, Chenggang, Pickford, Tom, Tian, Jianhui, Ellingford, Christopher, Zhou, Ning, Bowen, Christopher and Wan, Chaoying (2021) Piezoelectric-driven self-sensing leaf-mimic actuator enabled by integration of a self-healing dielectric elastomer and a piezoelectric composite. Advanced Intelligent Systems, 3 (8). 2000248. doi:10.1002/aisy.202000248 ISSN 2640-4567.
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Official URL: https://doi.org/10.1002/aisy.202000248
Abstract
Soft robots and devices exploit highly deformable materials that are capable of changes in shape to allow conformable physical contact for controlled manipulation. While soft robots are resilient to mechanical impact, they are susceptible to mechanical damage, such as tears and punctures. The development of self‐healing materials and actuators continues to attract increasing interest, in particular, with respect to integrating self‐healing polymers to create bioinspired soft self‐healing devices. Herein, a novel piezoelectric‐driven self‐healing leaf‐motion mimic actuator is designed by combining a thermoplastic methyl thioglycolate–modified styrene–butadiene–styrene (MGSBS) elastomer with a piezoelectric macrofiber composite (MFC) for self‐sensing applications. This article is the first demonstration of a self‐sensing and self‐healing actuator‐sensor system, which is driven by a piezoelectric actuator and can mimic leaf motion. The leaf‐motion actuator combines built‐in dynamic sensing and room‐temperature self‐healing capabilities to restore macroscale cutting damage with an intrinsically high bandwidth of up to 10 kHz. The feasibility and potential of the new actuator for use in complex soft autonomous systems are demonstrated. These new results help to address the emerging influence of self‐healing soft actuators and the challenges of sensing, actuation, and damage resistance in soft robotics.
Item Type: | Journal Article | ||||||||||||
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Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||||||
Library of Congress Subject Headings (LCSH): | Actuators, Piezoelectric devices, Elastomers -- Electric properties, Self-healing materials, Artificial intelligence | ||||||||||||
Journal or Publication Title: | Advanced Intelligent Systems | ||||||||||||
Publisher: | Wiley-Blackwell Publishing Ltd. | ||||||||||||
ISSN: | 2640-4567 | ||||||||||||
Official Date: | August 2021 | ||||||||||||
Dates: |
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Volume: | 3 | ||||||||||||
Number: | 8 | ||||||||||||
Article Number: | 2000248 | ||||||||||||
DOI: | 10.1002/aisy.202000248 | ||||||||||||
Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||
Date of first compliant deposit: | 22 February 2021 | ||||||||||||
Date of first compliant Open Access: | 23 March 2021 | ||||||||||||
RIOXX Funder/Project Grant: |
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