Design of adhesive conducting PEDOT-MeOH:PSS/PDA neural interface via electropolymerization for ultrasmall implantable neural microelectrodes

材料科学 微电极 佩多:嘘 导电聚合物 纳米技术 聚合物 聚苯乙烯 生物相容性 聚合 微加工 聚苯乙烯磺酸盐 图层(电子) 电极 复合材料 化学 冶金 替代医学 物理化学 病理 制作 医学
作者
Fajuan Tian,Jiawen Yu,Wen Wang,Dianbo Zhao,Jie Cao,Qi Zhao,Fucheng Wang,Hanjun Yang,Zhixin Wu,Jingkun Xu,Baoyang Lu
出处
期刊:Journal of Colloid and Interface Science [Elsevier BV]
卷期号:638: 339-348 被引量:37
标识
DOI:10.1016/j.jcis.2023.01.146
摘要

Conducting polymers are emerging as promising neural interfaces towards diverse applications such as deep brain stimulation due to their superior biocompatibility, electrical, and mechanical properties. However, existing conducting polymer-based neural interfaces still suffer from several challenges and limitations such as complex preparation procedures, weak interfacial adhesion, poor long-term fidelity and stability, and expensive microfabrication, significantly hindering their broad practical applications and marketization. Herein, we develop an adhesive and long-term stable conducting polymer neural interface by a simple two-step electropolymerization methodology, namely, the pre-polymerization of polydopamine (PDA) as an adhesive thin layer followed by electropolymerization of hydroxymethylated 3,4-ethylenedioxythiophene (EDOT-MeOH) with polystyrene sulfonate (PSS) to form stable interpenetrating PEDOT-MeOH:PSS/PDA networks. As-prepared PEDOT-MeOH:PSS/PDA interface exhibits remarkably improved interfacial adhesion against metallic electrodes, showing 93% area retention against vigorous sonication for 20 min, which is one of the best tenacious conducting polymer interfaces so far. Enabled by the simple methodology, we can facilely fabricate the PEDOT-MeOH:PSS/PDA interface onto ultrasmall Pt-Ir wire microelectrodes (diameter: 10 μm). The modified microelectrodes display two orders of magnitude lower impedance than commercial products, and also superior long-term stability to previous reports with high charge injection capacity retention up to 99.5% upon 10,000,000 biphasic input pulse cycles. With these findings, such a simple methodology, together with the fabricated high-performance and stable neural interface, can potentially provide a powerful tool for both advanced neuroscience researches and cutting-edge clinical applications like brain-controlled intelligence.
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