Researchers from Harvard’s (John A. Paulson) School of Engineering and Applied Sciences (SEAS) have taken a page out of nature to design a Reconfigurable Soft Actuator that’s fast, controlled through applied voltage, and reconfigurable into different 3D shapes. Actuation in mechanical systems involves two principle types of motions — linear (an object moving from one point to another), or rotational (an object rotating on an axis).
Those two rules don’t apply to movement found in nature, which can perform complex motions using soft materials. For example, our eyes can focus in on an object by contracting the eye muscles to change the shape of our corneas. Cameras on the other hand, focus by moving a lens along a straight line either manually or by autofocus.
The researchers designed their actuator using an elastomer sheet made up of several layers, which contain carbon nanotube-based electrodes deposited between each layer. When a voltage is applied to the electrodes, it creates a varying electric field that produces uneven changes in the elastomer’s geometry, thus morphing it into different shapes. Those shapes can be manipulated based on which electrodes are receiving a voltage, and which are turned off.
“We see this work as the first step in the development of a soft, shape-shifting material that changes shape according to electrical control signals from a computer. This is akin to the very first steps taken in the 1950’s to create integrated circuits from silicon, replacing circuits made of discrete, individual components. Just as those integrated circuits were primitive compared to the capabilities of today’s electronics, our devices have a simple but integrated three-dimensional architecture of electrical conductors and dielectrics, and demonstrate the elements of programmable reconfiguration, to create large and reversible shape changes.”—David Clarke, SEAS Professor of Materials
The researchers plan to continue the actuators development by looking at how different electrode designs and voltages can produce predicted actuation shapes and how those might be applied in the real world.