Carbon nanotube-integrated conductive hydrogels as multifunctional robotic skin. (May 2020)

• Record Type: Journal Article
• Authors: Hsiao, Li-Yin; Jing, Lin; Li, Kerui; Yang, Haitao; Li, Yang; Chen, Po-Yen
• Is Part Of: Carbon. Volume 161(2020)
• Page Start: 784
• Page End: 793
• Publication Date: 2020-05
• Subjects: Multi-walled carbon nanotubes -- Conductive hydrogels -- Strain sensing -- Fire retardancy -- Soft robots; Carbon -- Periodicals; Carbone -- Périodiques; Koolstof; Toepassingen; Electronic journals; 546.681
• DOI: 10.1016/j.carbon.2020.01.109
• Languages: English
• ISSNs: 0008-6223

Abstract

Abstract: Silicone elastomers with high mechanical stability have been conventionally adopted for the fabrication of emerging soft robots. However, these elastomers exhibit limited electrical and thermal properties that restrict the development of functional soft robots. A promising approach is to integrate carbon nanomaterials into hydrogels to develop multifunctional robotic skin with high deformability and diverse built-in functions for fabricated soft machines. Herein, a scalable approach was developed to fabricate a conductive hydrogel by integrating pristine multi-walled carbon nanotubes (MWNTs) into gelatin solution followed by the introduction of a crosslinking agent (i.e., glutaraldehyde). After the addition of glutaraldehyde, the viscosity of MWNT-gelatin dispersion increased with time, and a viscous precursor paste for conductive hydrogels was achieved for various scalable coating techniques including doctor blading. After large-area printing, the MWNT-gelatin paste continued to crosslink, and an MWNT-integrated gelatin hydrogel (MW-hydrogel) was obtained. The MW-hydrogels were highly deformable, and the electrical resistance of conductive MW-hydrogels was responsive to various mechanical deformations, enabling their applications in electronic robotic skin to monitor the actuations of soft robots in real time. Also, the MW-hydrogels were further utilized as flame-retardant skin for a soft robotic gripper, which could manipulate and rescue irregularly shaped objects from a fire scene. Graphical abstract: Image 1