Photo-patternable electrolytes for solid-state organic electrochemical neurons

Future advanced brain-computer interfaces, wearable and implantable bioelectronic devices, prosthetics, and intelligent soft robotics will require the ability to process signals in a highly personalized and localized manner, which will involve fully integrated electronic circuits within the nervous system and other living tissues.

To achieve this goal, it is imperative to develop energy-efficient intelligent electronics that have minimal device/circuit complexity and ion-based transducing and operating mechanisms akin to those observed in biology. The use of Silicon-based devices and circuits presents several limitations.

Organic electrochemical transistors (OECTs) represent a rapidly advancing technology that plays a pivotal role in the development of next-generation bioelectronic devices.

However, a notable limitation of OECTs is their typical operation in aqueous electrolytes, which can lead to undesired crosstalk between different devices on the same substrate, impeding their seamless integration into large-area arrays. Therefore, it is hard to develop neural networks based on the current OECTs.

Solid electrolytes offer a promising solution to these challenges. In this proposal, I design a photo-patternable solid electrolyte to develop solid-state OECTs. The aim is to directly pattern the electrolyte using sequential ultraviolet light-triggered solubility modulation. We plan to use UV-sensitive PEGDA to directly pattern the hydrogel without requiring photoresist or lift-off processes.

The PEGDA network will be covalently crosslinked after UV exposure to form a hydrogel network.

The strong intermolecular interaction between the two networks will allow the UV-exposed regions to resist subsequent water development, while the UV-unexposed regions will remain water-soluble.

This approach will enable the creation of smaller-size, large-area processing OECT devices, ultimately facilitating the development of OECNs with sizes approaching that of biological neurons.