Cargando…

Characterization and Optimization of Elastomeric Electrodes for Dielectric Elastomer Artificial Muscles

Dielectric elastomer actuators (DEAs) are an emerging type of soft actuation technology. As a fundamental unit of a DEA, the characteristics of compliant electrodes play a crucial role in the actuation performances of DEAs. Generally, the compliant electrodes can be categorized into uncured and cure...

Descripción completa

Detalles Bibliográficos
Autores principales: Ma, Guangqiang, Wu, Xiaojun, Chen, Lijin, Tong, Xin, Zhao, Weiwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7729933/
https://www.ncbi.nlm.nih.gov/pubmed/33291817
http://dx.doi.org/10.3390/ma13235542
Descripción
Sumario:Dielectric elastomer actuators (DEAs) are an emerging type of soft actuation technology. As a fundamental unit of a DEA, the characteristics of compliant electrodes play a crucial role in the actuation performances of DEAs. Generally, the compliant electrodes can be categorized into uncured and cured types, of which the cured one commonly involves mixing conductive particles into an elastomeric matrix before curing, thus demonstrating a better long-term performance. Along with the increasing proportion of conductive particles, the electrical conductivity increases at the cost of a stiffer electrode and lower elongation at break ratio. For different DEA applications, it can be more desirable to minimize the electrode stiffness or to maximize its conductivity. In examination of the papers published in recent years, few works have characterized the effects of elastomeric electrodes on the outputs of DEAs, or of their optimizations under different application scenarios. In this work, we propose an experimental framework to characterize the performances of elastomeric electrodes with different formulas based on the two key parameters of stiffness and conductivity. An optimizing method is developed and verified by two different application cases (e.g., quasi-static and dynamic). The findings and the methods developed in this work can offer potential approaches for developing high-performance DEAs.