Controllable analog-to-digital bipolar resistive switching behavior and mechanism analysis in δ-MnO2-based memristor

Abstract

Memristor is one of the most emerging electronic components to realize synaptic functions in the neuromorphic computing. Memristor with controllable analog-to-digital resistive switching behaviors has the potential to considerably accelerate the realization of high-performance neuromorphic computing. In this work, a memristor with Ag/δ-MnO2/Ti structure was fabricated, and an analog-to-digital resistive switching behavior with voltage regulation was demonstrated. Memristive switching with analogue characteristics can generate a gradual increase in conductance at low voltage of less than 1.3 V to aid in the building of artificial synapses. The Ag/δ-MnO2/Ti memristor with excellent digital resistive switching performance can be applied for data storage and in-memory computation at voltage windows of higher than 1.3 V. Furthermore, the resistive switching mechanism was analyzed by employing the first-principle calculation. The main reason for the emergence of digital memristor characteristics is the Ag+ ions can enter to the δ-MnO2 layer driven by a larger voltage and continue to cluster and form conductive filament. This work enriches the application of analog-to-digital bipolar memristor in neuromorphic computing, and facilitates further realization of memristor in low-power and high-density circuit integration.