Poly(5-nitroindole) Thin Film as Conductive and Adhesive Interfacial Layer for Robust Neural Interface

Poly(3,4-ethylenedioxythiophene) (PEDOT) has emerged as a promising neural interface material, but the weak adhesion of PEDOT to substrates adversely affects its reliability and practical application. Although adhesive interfacial layers have been explored to enhance the adhesion of PEDOT, their poor conductivity seriously compromises the performance of neural electrodes. It is a great challenge to develop an adhesive interfacial layer with excellent electrical properties. Herein, utilizing the advantages of polyindole derivatives, conductive polymers which have various functional groups for potential interface bonding, a conductive, adhesive, and biocompatible poly(5-nitroindole) (PIN-5NO(2)) interfacial layer is developed to enhance the adhesion of PEDOT to metal electrodes. The conjugated PIN-5NO(2) with its superior electrical property can be prepared by electropolymerization of 5-nitroindole; however, the electrografting of amino groups, which is reduced from nitro groups in 5-nitroindole can provide strong adhesion with the gold (Au) substrate. With PIN-5NO(2) as an adhesive interfacial layer, the resultant Au/PIN-5NO(2)/PEDOT electrode exhibits excellent electrochemical property, superb stability, and biocompatibility for high-performance neural interface. The in vivo evaluation of Au/PIN-5NO(2)/PEDOT electrocorticographic microelectrodes demonstrates superior capacity to capture the neural dynamics of the brain. The novel strategy would offer a new insight for the construction of high-performance neural electrodes with high stability for neural interface application.

Automated summary

The article introduces a novel adhesive interfacial layer PIN-5NO(2) developed using polyindole derivatives to enhance the adhesion of PEDOT to metal electrodes while maintaining excellent electrical properties. This interfacial layer can improve the electrode's electrochemical performance, stability, and biocompatibility, making it suitable for high-performance neural interfaces.