Methods of poly (3,4)-ethylenedioxithiophene (PEDOT) electrodeposition on metal electrodes for neural stimulation and recording

Thomas Niederhoffer, Anne Vanhoestenberghe, Henry T Lancashire

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Conductive polymers are of great interest in the field of neural electrodes because of their potential to improve the interfacial properties of electrodes. In particular, the conductive polymer poly (3,4)-ethylenedioxithiophene (PEDOT) has been widely studied for neural applications. Objective: This review compares methods for electrodeposition of PEDOT on metal neural electrodes, and analyses the effects of deposition methods on morphology and electrochemical performance. Approach: Electrochemical performances were analysed against several deposition method choices, including deposition charge density and co-ion, and correlations were explained to morphological and structural arguments as well as characterisation methods choices. Main results: Coating thickness and charge storage capacity are positively correlated with PEDOT electrodeposition charge density. We also show that PEDOT coated electrode impedance at 1 kHz, the only consistently reported impedance quantity, is strongly dependent upon electrode radius across a wide range of studies, because PEDOT coatings reduces the reactance of the complex impedance, conferring a more resistive behaviour to electrodes (at 1 kHz) dominated by the solution resistance and electrode geometry. This review also summarises how PEDOT co-ion choice affects coating structure and morphology and shows that co-ions notably influence the charge injection limit but have a limited influence on charge storage capacity and impedance. Finally we discuss the possible influence of characterisation methods to assess the robustness of comparisons between published results using different methods of characterisation. Significance: This review aims to serve as a common basis for researchers working with PEDOT by showing the effects of deposition methods on electrochemical performance, and aims to set a standard for accurate and uniform reporting of methods.

Original languageEnglish
Article number011002
JournalJournal of neural engineering
Issue number1
Early online date5 Jan 2023
Publication statusPublished - 1 Feb 2023


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