Summary
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.
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| Web resources: | https://cordis.europa.eu/project/id/101151352 |
| Start date: | 06-11-2024 |
| End date: | 05-11-2026 |
| Total budget - Public funding: | - 206 887,00 Euro |
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Original description
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.Status
SIGNEDCall topic
HORIZON-MSCA-2023-PF-01-01Update Date
22-11-2024
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