Harnessing the 2D Structure‐Enabled Viscoelasticity of Graphene‐Based Hydrogel Membranes for Chronic Neural Interfacing

Autor: Zhiyuan Xiong, Wenhui Huang, Qinghua Liang, Yang Cao, Shuyi Liu, Zicong He, Ranran Zhang, Bin Zhang, Rylie Green, Shuixing Zhang, Dan Li
Rok vydání: 2022
Předmět:
Zdroj: Small Methods. 6:2200022
ISSN: 2366-9608
Popis: Stiffness and viscoelasticity of neural implants regulate the foreign body response. Recent studies have suggested the use of elastic or viscoelastic materials with tissue-like stiffness for long-term neural electrical interfacing. Herein, the authors find that a viscoelastic multilayered graphene hydrogel (MGH) membrane, despite exhibiting a much higher Young's modulus than nerve tissues, shows little inflammatory response after 8-week implantation in rat sciatic nerves. The MGH membrane shows significant viscoelasticity due to the slippage between graphene nanosheets, facilitating its seamless yet minimally compressive interfacing with nerves to reduce the inflammation caused by the stiffness mismatch. When used as neural stimulation electrodes, the MGH membrane can offer abundant ion-accessible surfaces to bring a charge injection capacity 1-2 orders of magnitude higher than its traditional Pt counterpart, and further demonstrates chronic neural therapy potential in low-voltage modulation of rat blood pressure. This work suggests that the emergence of 2D nanomaterials and particularly their unique structural attributes can be harnessed to enable new bio-interfacing design strategies.
Databáze: OpenAIRE