Issue 32, 2023

A high linearity and multilevel polymer-based conductive-bridging memristor for artificial synapses

Abstract

Conductive-bridging memristors based on a metal ion redox mechanism have good application potential in future neuromorphic computing nanodevices owing to their high resistance switch ratio, fast operating speed, low power consumption and small size. Conductive-bridging memristor devices rely on the redox reaction of metal ions in the dielectric layer to form metal conductive filaments to control the conductance state. However, the migration of metal ions is uncontrollable by the applied bias, resulting in the random generation of conductive filaments, and the conductance state is difficult to accurately control. Herein, we report an organic polymer carboxylated chitosan-based memristor doped with a small amount of the conductive polymer PEDOT:PSS to improve the polymer ionic conductivity and regulate the redox of metal ions. The resulting device exhibits uniform conductive filaments during device operation, more than 100 and non-volatile conductance states with a ∼1 V range, and linear conductance regulation. Moreover, simulation using handwritten digital datasets shows that the recognition accuracy of the carboxylated chitosan-doped PEDOT:PSS memristor array can reach 93%. This work provides a path to facilitate the performance of metal ion-based memristors in artificial synapses.

Graphical abstract: A high linearity and multilevel polymer-based conductive-bridging memristor for artificial synapses

Article information

Article type
Paper
Submitted
14 Apr 2023
Accepted
21 Jul 2023
First published
22 Jul 2023

Nanoscale, 2023,15, 13411-13419

A high linearity and multilevel polymer-based conductive-bridging memristor for artificial synapses

J. Zhou, Z. Wang, Y. Fu, Z. Xie, W. Xiao, Z. Wen, Q. Wang, Q. Liu, J. Zhang and D. He, Nanoscale, 2023, 15, 13411 DOI: 10.1039/D3NR01726E

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