English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Next-generation implantable computational devices require long-term stableelectronic components capable of operating in, and interacting with,electrolytic surroundings without being damaged. Organic electrochemicaltransistors (OECTs) emerged as fitting candidates. However, while singledevices feature impressive figures of merit, integrated circuits (ICs) immersedin a common electrolytes are hard to realize using electrochemical transistors,and there is no clear path forward for optimal top-down circuit design andhigh-density integration. The simple observation that two OECTs immersed in thesame electrolytic medium will inevitably interact hampers their implementationin complex circuitry. The electrolyte's ionic conductivity connects all thedevices in the liquid, producing unwanted and often unforeseeable dynamics.Minimizing or harnessing this crosstalk has been the focus of very recentstudies.  In this Perspective, we discuss the main challenges, trends, andopportunities for realizing OECT-based circuitry in a liquid environment thatcould circumnavigate the hard limits of engineering and human physiology. Weanalyze the most successful approaches in autonomous bioelectronics andinformation processing. Elaborating on the strategies to circumvent and harnessdevice crosstalk proves that platforms capable of complex computation and evenmachine learning can be realized in-liquido using mixed ionic-electronicconductors.

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