Issue 30, 2016

An organic terpyridyl-iron polymer based memristor for synaptic plasticity and learning behavior simulation

Abstract

Memristors have been extensively studied for nonvolatile memory storage, neuromorphic computing, and logic applications. Particularly, synapse emulation is viewed as a key step to realizing neuromorphic computing, because the biological synapse is the basic unit for learning and memory. In this study, a memristor with the simple structure of Ta/viologen diperchlorate [EV(ClO4)2]/terpyridyl-iron polymer (TPy-Fe)/ITO is fabricated to simulate the functions of the synapse. Essential synaptic plasticity and learning behaviours are emulated by using this memristor, such as spike-timing-dependent plasticity and spike-rate-dependent plasticity. It is demonstrated that the redox between a terpyridyl-iron polymer and viologen species leads to our memristor behavior. Furthermore, the learning behavior depending on different amplitudes of voltage pulses is investigated as well. These demonstrations help pave the way for building bioinspired neuromorphic systems based on memristors.

Graphical abstract: An organic terpyridyl-iron polymer based memristor for synaptic plasticity and learning behavior simulation

Supplementary files

Article information

Article type
Paper
Submitted
01 Feb 2016
Accepted
01 Mar 2016
First published
02 Mar 2016

RSC Adv., 2016,6, 25179-25184

An organic terpyridyl-iron polymer based memristor for synaptic plasticity and learning behavior simulation

X. Yang, C. Wang, J. Shang, C. Zhang, H. Tan, X. Yi, L. Pan, W. Zhang, F. Fan, Y. Liu, Y. Chen, G. Liu and R. Li, RSC Adv., 2016, 6, 25179 DOI: 10.1039/C6RA02915A

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