In Liquido Computation with Electrochemical Transistors and Mixed Conductors for Intelligent Bioelectronics

Cucchi, Matteo (author): Ecole Polytech Fed Lausanne EPFL, Switzerland; Tech Univ Dresden, Germany

Parker, Daniela (author): Linköpings universitet,Laboratoriet för organisk elektronik,Tekniska fakulteten

Stavrinidou, Eleni, 1986- (author): Linköpings universitet,Laboratoriet för organisk elektronik,Tekniska fakulteten

(creator_code:org_t)

2023-02-22
2023
English.
In: Advanced Materials. - : WILEY-V C H VERLAG GMBH. - 0935-9648 .- 1521-4095. ; 35:15

Related links:: https://liu.diva-por... (primary) (Raw object); show more...; https://urn.kb.se/re...; https://doi.org/10.1...; show less...

Abstract Subject headings

Next-generation implantable computational devices require long-term-stable electronic components capable of operating in, and interacting with, electrolytic surroundings without being damaged. Organic electrochemical transistors (OECTs) emerged as fitting candidates. However, while single devices feature impressive figures of merit, integrated circuits (ICs) immersed in common electrolytes are hard to realize using electrochemical transistors, and there is no clear path forward for optimal top-down circuit design and high-density integration. The simple observation that two OECTs immersed in the same electrolytic medium will inevitably interact hampers their implementation in complex circuitry. The electrolytes ionic conductivity connects all the devices in the liquid, producing unwanted and often unforeseeable dynamics. Minimizing or harnessing this crosstalk has been the focus of very recent studies. Herein, the main challenges, trends, and opportunities for realizing OECT-based circuitry in a liquid environment that could circumnavigate the hard limits of engineering and human physiology, are discussed. The most successful approaches in autonomous bioelectronics and information processing are analyzed. Elaborating on the strategies to circumvent and harness device crosstalk proves that platforms capable of complex computation and even machine learning (ML) can be realized in liquido using mixed ionic-electronic conductors (OMIECs).

By the author/editor: Cucchi, Matteo; Parker, Daniela; Stavrinidou, Ele ...; Gkoupidenis, Pas ...; Kleemann, Hans

About the subject

ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Electrical Engin ...; and Other Electrical ...

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.