Published June 9, 2014
| Version v1
Journal article
Conductance with stochastic resonance in Mn12 redox network without tuning
Creators
- 1. Graduate School of Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui 910-8507 (Japan)
- 2. Department of Chemistry, Graduate School of Science, Osaka University, 1-1 Machikaneyama-cho, Toyonaka, Osaka 560-0043 (Japan)
- 3. Institute of Scientific and Industrial Research (ISIR), Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka 567-0047 (Japan)
- 4. Department of Chemistry, Faculty of Science and Engineering, Kinki University, 3-4-1 Kowakae, Higashi-Osaka, Osaka 577-8502 (Japan)
Description
Artificial neuron-based information processing is one of the attractive approaches of molecular-scale electronics, which can exploit the ability of molecular system for self-assembling or self-organization. The self-organized Mn12/DNA redox network shows nonlinear current-voltage characteristics that can be described by the Coulomb blockade network model. As a demonstration of the nonlinear network system, we have observed stochastic resonance without tuning for weak periodic input signals and thermal noise, which suggests a route to neural network composed of molecular materials.
Additional details
Identifiers
- DOI
- 10.1063/1.4882160;
Publishing Information
- Journal Title
- Applied Physics Letters
- Journal Volume
- 104
- Journal Issue
- 23
- Journal Page Range
- p. 233104-233104.4
- ISSN
- 0003-6951
- CODEN
- APPLAB
INIS
- Country of Publication
- United States
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 46006224
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; S77: NANOSCIENCE AND NANOTECHNOLOGY;
- Descriptors DEI
- COMPUTERIZED SIMULATION; CURRENTS; DNA; ELECTRIC CONDUCTIVITY; ELECTRIC POTENTIAL; MOLECULES; NEURAL NETWORKS; NOISE; NONLINEAR PROBLEMS; PERIODICITY; RESONANCE; STOCHASTIC PROCESSES
- Descriptors DEC
- ELECTRICAL PROPERTIES; NUCLEIC ACIDS; ORGANIC COMPOUNDS; PHYSICAL PROPERTIES; SIMULATION; VARIATIONS
Optional Information
- Notes
- (c) 2014 AIP Publishing LLC