Abstract
The ability to 3D print soft materials with integrated strain sensors enables significant flexibility for the design and fabrication of soft robots. Hydrogels provide an interesting alternative to traditional soft robot materials, allowing for more varied fabrication techniques. In this work, we investigate the 3D printing of a gelatin-glycerol hydrogel, where transglutaminase is used to catalyse the crosslinking of the hydrogel such that its material properties can be controlled for 3D printing. By including electron-conductive elements (aqueous carbon black) in the hydrogel we can create highly flexible and linear soft strain sensors. We present a first investigation into adapting a desktop 3D printer and optimizing its control parameters to fabricate sensorized 2D and 3D structures which can undergo >300% strain and show a response to strain which is highly linear and synchronous. To demonstrate the capabilities of this material and fabrication approach, we produce some example 2D and 3D structures and show their sensing capabilities.
Highlights
T HE development of new materials and fabrication techniques is fundamental to the construction of soft robots [1], [2]
We show how this material can undergo >300% strain, and how the sensor properties show a high sensitivity and high linearity compared to a number of existing sensorized hydrogels, making the material extremely promising for soft robotic applications
By ignoring thixotropic behaviors and assuming coalescence to be independent of d, we suggest a μ threshold at which coalescence between neighbouring lines becomes possible
Summary
T HE development of new materials and fabrication techniques is fundamental to the construction of soft robots [1], [2]. Many soft robots are currently fabricated from elastomeric materials such as silicones, which allow for complex, homogeneous, and highly flexible structures [3]. Whilst these have attractive properties for many applications, the use of such materials often limits the fabrication process to casting. The inclusion of soft sensors in this process can be challenging, and often the resultant sensor properties are suboptimal due to poor interfacing between the elastomer and the conductive particle [4]. Despite the many advances that have been seen, it is still a challenge
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