English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Organic Memristor and Bio-Inspired Information Processing

Erokhin, V., Schüz, A., & Fontana, M. (2010). Organic Memristor and Bio-Inspired Information Processing. International Journal of Unconventional Computing, 6(1), 15-32.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-C172-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0002-7E27-6
Genre: Journal Article

Files

show Files

Creators

show
hide
 Creators:
Erokhin, V, Author
Schüz, A1, 2, Author              
Fontana, MP, Author
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

Content

show
hide
Free keywords: -
 Abstract: The memristor is a circuit element whose conductance depends on its previous functioning history. Although postulated decades ago, it was actually fabricated only recently, spurring much debate and activity as to its possible applications in smart sensors and memory components in information handling systems. Recently we fabricated an organic memristor, basically a heterojunction between a conducting polymer (polyaniline) and a solid electrolyte (Li-doped polyethylene oxide). In this paper we describe the peculiar behavior of this device, due to the electrochemical control through ion flux and redox reactions in the conducting polymer, which lead to properties such as non linearity and memory. In special conditions, this organic memristor generates current auto-oscillation in fixed voltage conditions. Using these features we have fabricated several types of circuits which could be trained using the appropriate external stimuli, demonstrating supervised and unsupervised learning. Finally, the possibility of th e formation of adaptive networks of statistically distributed self-assembled complex molecules for biologically inspired parallel information handling will be discussed.

Details

show
hide
Language(s):
 Dates: 2010-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: BibTex Citekey: 6268
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: International Journal of Unconventional Computing
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 6 (1) Sequence Number: - Start / End Page: 15 - 32 Identifier: -