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

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 & SIM;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.

Automated summary

Conductive-bridging memristors based on metal ion redox mechanism have potential applications in future neuromorphic computing nanodevices due to their high resistance switch ratio, fast operating speed, low power consumption, and small size. However, the uncontrolled migration of metal ions results in random generation of conductive filaments and difficulty in accurately controlling the conductance state. In this study, an organic polymer carboxylated chitosan-based memristor doped with a small amount of conductive polymer PEDOT:PSS was reported to improve polymer ionic conductivity and regulate the redox of metal ions. The resulting device exhibited uniform conductive filaments, more than 100 non-volatile conductance states, and linear conductance regulation. Moreover, simulation using handwritten digital datasets showed a recognition accuracy of 93% for the carboxylated chitosan-doped PEDOT:PSS memristor array. This work provides a path to enhance the performance of metal ion-based memristors in artificial synapses.