Understanding the Resistive Switching Behaviors of Top Electrode (Au, Cu, and Al)-Dependent TiO2-Based Memristive Devices

Abstract

Memristor-based neuromorphic computing is promising toward their potential application of handling complex parallel tasks in the period of big data. To implement brain-inspired applications of spiking neural networks, new physical architecture designs are needed. Here, a serial memristive structure (SMS) consisting of memristive devices with different top electrodes is proposed. Top electrodes Au, Cu, and Al are selected for nitrogen-doped TiO2 nanorod array-based memristive devices. The typical I-V cycles, retention, on/off ratio, and variations of cycle to cycle of top electrode-dependent memristive devices have been studied. Devices with Cu and Al electrodes exhibit a retention of over 104 s. And the resistance states of the device with the Al top electrode are reliable. Furthermore, the conductive mechanism underlining the I-V curves is discussed in detail. The interface-type mechanism and block conductance mechanism are illustrated, which are related to electron migration and ion/anion migration, respectively. Finally, the SMS has been constructed using memristive devices with Al and Cu top electrodes, which can mimic the spiking pulse-dependent plasticity of a synapse and a neuron body. The SMS provides a new approach to implement a fundamental physical unit for neuromorphic computing.