Integrating nano- to micro-sized dielectric fillers to elastomer matrices to form dielectric composites is one of the commonly utilized methods to improve the performance of dielectric elastomer actuators (DEAs). Barium titanate (BaTiO3) is among the widely used ferroelectric fillers for this purpose; however, calcium copper titanate CaCu3Ti4O12 (CCTO) has the potential to outperform such conventional fillers. Despite their promising performance, CCTO-based dielectric composites for DEA application are studied to a relatively lower degree. Particularly, the composites are characterized for a comparably small particle loading range, while critical DEA properties such as breakdown strength and nonlinear elasticity are barely addressed in the literature. Thus, in this study, CCTO was paired with polydimethylsiloxane (CH3)3SiO[Si(CH3)2O]nSi(CH3)3 (PDMS), Sylgard 184, to gain a comprehensive understanding of the effects of particle loading and size on the dielectric composite properties important for DEA applications. The dielectric composites’ performance was described through the figures of merit (FOMs) that consider materials’ Young’s modulus, dielectric permittivity, and breakdown strength. The optimum amounts of the ferroelectric filler were determined through the FOMs to maximize composite DEA performance. Lastly, electromechanical testing of the pre-stretched CCTO-composite DEA validated the improved performance over the plain elastomer DEA, with deviations from prediction attributed to the studied composites’ nonlinearity.
Dielectric elastomer actuator (DEA) is a smart material that holds promise for soft robotics due to the material’s intrinsic softness, high energy density, fast response, and reversible electromechanical characteristics. Like for most soft robotics materials, additive manufacturing (AM) can significantly benefit DEAs and is mainly applied to the unimorph DEA (UDEA) configuration. While major aspects of UDEA modeling are known, 3D printed UDEAs are subject to specific material and geometrical limitations due to the AM process and require a more thorough analysis of their design and performance. Furthermore, a figure of merit (FOM) is an analytical tool that is frequently used for planar DEA design optimization and material selection but is not yet derived for UDEA. Thus, the objective of the paper is modeling of 3D printed UDEAs, analyzing the effects of their design features on the actuation performance, and deriving FOMs for UDEAs. As a result, the derived analytical model demonstrates dependence of actuation performance on various design parameters typical for 3D printed DEAs, provides a new optimum thickness to Young’s modulus ratio of UDEA layers when designing a 3D printed DEA with fixed dielectric elastomer layer thickness, and serves as a base for UDEAs’ FOMs. The FOMs have various degrees of complexity depending on considered UDEA design features. The model was numerically verified and experimentally validated through the actuation of a 3D printed UDEA. The fabricated and tested UDEA design was optimized geometrically by controlling the thickness of each layer and from the material perspective by mixing commercially available silicones in non-standard ratios for the passive and dielectric layers. Finally, the prepared non-standard mix ratios of the silicones were characterized for their viscosity dynamics during curing at various conditions to investigate the silicones’ manufacturability through AM.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.