Abstract
Artificial synaptic devices are the essential hardware component in emerging neuromorphic computing systems by mimicking biological synapse and brain functions. When made from natural organic materials such as protein and carbohydrate, they have potential to improve sustainability and reduce electronic waste by enabling environmentally friendly disposal. In this paper, a new natural organic memristor based artificial synaptic device is reported with the memristive film processed by a honey and carbon nanotube (CNT) admixture, that is, honey-CNT memristor. Optical microscopy, scanning electron microscopy, and micro-Raman spectroscopy are employed to analyze the morphology and chemical structure of the honey-CNT film. The device demonstrates analog memristive potentiation and depression, with the mechanism governing these functions explained by the formation and dissolution of conductive paths due to the electrochemical metal filaments which are assisted by CNT clusters and bundles in the honey-CNT film. The honey-CNT memristor successfully emulates synaptic functionalities such as short-term plasticity and its transition to long-term plasticity for memory rehearsal, spatial summation, and shunting inhibition, and for the first time, the classical conditioning behavior for associative learning by mimicking the Pavlov's dog experiment. All these results testify that honey-CNT memristor based artificial synaptic device is promising for energy-efficient and eco-friendly neuromorphic systems.
Recommended Citation
M. M. Tanim et al., "A Natural Organic Artificial Synaptic Device Made from a Honey and Carbon Nanotube Admixture for Neuromorphic Computing," Advanced Materials Technologies, vol. 8, no. 14, article no. 2202194, Wiley, Jul 2023.
The definitive version is available at https://doi.org/10.1002/admt.202202194
Department(s)
Electrical and Computer Engineering
Publication Status
Full Access
Keywords and Phrases
artificial synapses; carbon nanotubes; honey; memristors; neuromorphic computing
International Standard Serial Number (ISSN)
2365-709X
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Wiley, All rights reserved.
Publication Date
24 Jul 2023

Comments
Washington State University Vancouver, Grant 2104976