Multilevel resistive switching and synaptic plasticity of nanoparticulated cobaltite oxide memristive device

Multilevel resistive switching (RS) is a key property to embrace the full potential of memristive devices for non-volatile memory and neuromorphic computing applications. In this study, we employed nanoparticulated cobaltite oxide (Co3O4) as a model material to demonstrate the multilevel RS and synaptic learning capabilities because of its multiple and stable redox state properties. The Pt/Co3O4/Pt memristive device exhibited tunable RS properties with respect to different voltages and compliance currents (CC) without the electroforming process. That is, the device showed voltage-dependent RS at a higher CC whereas CC-dependent RS was observed at lower CC. The device showed four different resistance states during endurance and retention measurements and non-volatile memory results indicated that the CC-based measurement had less variation. Besides, we investigated the basic and complex synaptic plasticity properties using the analog current-voltage characteristics of the Pt/Co3O4/Pt device. In particular, we mimicked the potentiation-depression and four-spike time-dependent plasticity (STDP) rules such as asymmetric Hebbian, asymmetric anti-Hebbian, symmetric Hebbian, and symmetric anti-Hebbian learning rules. The results of the present work indicate that the cobaltite oxide is an excellent nanomaterial for both multilevel RS and neuromorphic computing applications. (C) 2021 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.

Automated summary

In this study, nanoparticulated cobaltite oxide was used to demonstrate multilevel resistive switching and synaptic learning capabilities, showing potential for non-volatile memory and neuromorphic computing applications. The device exhibited tunable resistive switching properties and different resistance states, with less variation in measurements based on compliance current. The study also explored basic and complex synaptic plasticity properties, mimicking various learning rules such as Hebbian and anti-Hebbian rules. The results suggest that cobaltite oxide is an excellent nanomaterial for both multilevel resistive switching and neuromorphic computing applications.