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

TL;DR

This paper explores the development of in-liquid electronic circuits using organic electrochemical transistors and mixed conductors, aiming for stable, high-density bioelectronic computation in electrolytic environments.

Contribution

It analyzes challenges and strategies for implementing integrated circuits with electrochemical transistors in liquid environments, proposing methods to manage device crosstalk for complex computation.

Findings

Mixed ionic-electronic conductors enable complex in-liquid computation.

Strategies to mitigate and utilize device crosstalk are effective.

Potential for machine learning in bioelectronics using liquid-based circuits.

Abstract

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 a 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 electrolyte's 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. In this Perspective, we discuss 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. We analyze the most successful approaches in autonomous bioelectronics and information processing. Elaborating on the strategies to circumvent and harness device crosstalk proves that platforms capable of complex computation and even machine learning can be realized in-liquido using mixed ionic-electronic conductors.