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Updated: Feb 25, 2026

Development and Functionalization of Electrolyte-Gated Graphene Field-Effect Transistor for Biomarker Detection
Published on: February 1, 2022
Direct electrodeposition of Graphene enhanced conductive polymer on microelectrode for biosensing application
Ming-Hao Wang1, Bo-Wen Ji1, Xiao-Wei Gu2
1National Key Laboratory of Science and Technology on Micro/Nano Fabrication Laboratory, Key Laboratory for Thin Film and Microfabrication of the Ministry of Education, Collaborative Innovation Center of IFSA, Department of Micro/Nano-electronics, Shanghai Jiao Tong University, Shanghai, PR China.
Abstract:
Engineering of neural interface with nanomaterials for high spatial resolution neural recording and stimulation is still hindered by materials properties and modification methods. Recently, poly(3,4-ethylene-dioxythiophene) (PEDOT) has been widely used as an electrode-tissue interface material for its good electrochemical property. However, cracks and delamination of PEDOT film under pulse stimulation are found which restrict its long-term applications. This paper develops a flexible electrochemical method about the co-deposition of graphene with PEDOT on microelectrode sites to enhance the long-term stability and improve the electrochemical properties of microelectrode. This method is unique and profound because it co-deposits graphene with PEDOT on microelectrode sites directly and avoids the harmful post reduction process. And, most importantly, significantly improved electrochemical performances of the modified microelectrodes (compared to PEDOT-GO) are demonstrated due to the large effective surface area, good conductivity and excellent mechanical property of graphene. Furthermore, the good mechanical stability of the composites is verified by ultrasonication and CV scanning tests. In-vivo acute implantation of the microelectrodes reveals the modified microelectrodes show higher recording performance than the unmodified ones. These findings suggest the composites are excellent candidates for the applications of neural interface.

