Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. In Liquido Computation with Electrochemical Transistors and Mixed Conductors for Intelligent Bioelectronics
 
research article

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

Cucchi, Matteo  
•
Parker, Daniela
•
Stavrinidou, Eleni
Show more
February 22, 2023
Advanced Materials

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 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. 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).

  • Files
  • Details
  • Metrics
Type
research article
DOI
10.1002/adma.202209516
Web of Science ID

WOS:000936376500001

Author(s)
Cucchi, Matteo  
Parker, Daniela
Stavrinidou, Eleni
Gkoupidenis, Paschalis
Kleemann, Hans
Date Issued

2023-02-22

Publisher

Wiley-V C H Verlag Gmbh

Published in
Advanced Materials
Subjects

Chemistry, Multidisciplinary

•

Chemistry, Physical

•

Nanoscience & Nanotechnology

•

Materials Science, Multidisciplinary

•

Physics, Applied

•

Physics, Condensed Matter

•

Chemistry

•

Science & Technology - Other Topics

•

Materials Science

•

Physics

•

bioelectronics

•

electrochemical transistors

•

neuromorphic computing

•

in-vivo polymerization

•

poly(3,4-ethylenedioxythiophene) pedot

•

real-time

•

electronics

•

interface

•

sensor

•

brain

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LSBI  
Available on Infoscience
March 27, 2023
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/196522
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés