Self‐Doped Mixed Ionic‐Electronic Conductors to Tune the Threshold Voltage and the Mode of Operation in Organic Electrochemical Transistors

Organic mixed ionic‐electronic conductors with tunable doping, low threshold voltages, and air stability are crucial for bioelectronic applications. A homopolymer based on an alkoxy thiophene monomer and its copolymer with a thiophene carrying ethylene glycol side chains are synthesized and converted to self‐doped conjugated polyelectrolytes, P3HOTS‐TMA+, and P3HOTS‐TMA+‐co‐P3MEEET. The self‐doping occurs during the conversion to polyelectrolytes. Both polyelectrolytes show high electrical conductivity without any external dopants. UV–Vis–NIR spectroscopy and spectroelectrochemistry confirm excellent air stability of the doped state. In an organic electrochemical transistor (OECT), the P3HOTS‐TMA+ operates in depletion mode, while P3HOTS‐TMA+‐co‐P3MEEET exhibits accumulation mode of operation with low threshold voltage, both showing fast response times. On the other hand, the non‐doped homopolymer, P3MEEET, shows a high negative threshold voltage in accumulation mode. Thus, copolymerization with the self‐dopable monomer changes the mode of operation as well as the threshold voltage substantially. Ultraviolet photoelectron spectroscopy reveals a considerable reduction of the hole injection barrier for the self‐doped system P3HOTS‐TMA+. Mott‐Schottky analysis shows reduction in charge carrier concentration in the copolymer compared to the homopolymer. Thus, the copolymerization strategy with a self‐dopable monomer is an efficient tool for tuning the degree of doping leading to low threshold voltage in OECTs. Self‐doped, air‐stable organic mixed ionic‐electronic conductors showing high electrical conductivity are synthesized. A copolymerization with a not self‐dopable comonomer is demonstrated to tune the degree of doping and the mode of operation in electrochemical transistors. This copolymer operates in the accumulation mode with a low threshold voltage, which make these materials highly interesting for applications in neuromorphic computing and bioelectronics.