The innovation engine for new materials

Erin Mee

Erin Mee, Material Science and Engineering, Everett Community College


Materials Science and Engineering


Everett Community College


Veronica Reynolds

Faculty Sponsor(s): 

Michael Chabinyc

Faculty Sponsor's Department(s): 


Project Title: 

Super-Soft Elastomer Electrodes for Dielectric Actuators

Project Description: 

The field of soft robotics aims to create robotic systems that can function in diverse and variable environments and can be used in applications including prosthetics, healthcare, or even outer space and deep sea exploration. Dielectric elastomer actuators (DEAs) are an interesting option to drive the movement of soft robots because they directly transform electrical potential into mechanical work and can be easily integrated into existing electronic technologies. The device architecture of a DEA appears similar to a parallel plate capacitor, with a dielectric sandwiched between two electrodes. In a DEA, however, both the dielectric and the electrodes are soft and stretchable. Upon applying a potential across the two electrodes, the collection of charges creates electrostatic forces that attract perpendicular to the electrodes and repulse parallel to the electrodes, causing the actuator to contract and expand. One major challenge for DEAs is the high voltage required for actuation with current materials.  Developing lower modulus materials can reduce actuation voltages, as higher strain would be developed under a given stress. My group works with an elastomer architecture that reduces trapped entanglements inherent to typical elastomers, which impose a lower limit to the elastic modulus. In this project, I created an electrode material by dispersing carbon nanotubes in my group’s super-soft elastomer architecture through a variety of dispersion techniques. Impedance spectroscopy was used to probe the material’s electrical properties. In this work, high conductivity is demonstrated in a carbon nanotube elastomer composite that could ultimately be applied in a better performing DEA.