This paper presents the fabrication and characterization of the cross-point structure 20 × 20 μm 2 RRAM with TiO x /TiO y bi-layer insulator for synaptic application in neuromorphic systems. The measured oxygen concentration of the TiO x /TiO y switching layers of the fabricated devices using X-ray photoelectron spectroscopy analysis showed that the oxygen concentration ratio between TiO x and TiO y is ~ 1.5. After electroforming at ~ 5.62 V, the on/off ratio was ~ 76 at 0.2 V with the DC sweep voltage scheme. Synaptic behaviors including long-term potentiation (LTP) and long-term depression (LTD) were performed with 50 identical pulses for the implementation of RRAM into neuromorphic systems based on convolutional neural networks. Also, linearly increased (or decreased) 25 pulses were applied to the device so that the conductance changes linearly. The resulting linear LTP and LTD characteristics were mirror-symmetric, which could maximize the accuracy. For Hebbian learning, the device also mimicked the spike-timing-dependent plasticity properties with a conductance change from − 77.79% to 96.07% using a time-division multiplexing approach.

Analog resistive switching (ARS) is an important characteristic of resistive random-access memory (RRAM) used as a synaptic device. An interface switching cross-point RRAM was fabricated with Au/TiO x /AlO σ /Al stacked structure in order to investigate its conduction mechanism and synaptic behaviour. The gradual resistive switching characteristic of the fabricated AlO σ -based RRAM was demonstrated and the ARS conduction mechanism was analyzed by using the DC sweep technique. The I-V relationship shows that the conduction mechanism in the RESET state is governed by Schottky conduction, which was confirmed by a linear relationship from the Log (I) vs. Sqrt (V) graph, while the conduction mechanism in the SET state is governed by Poole-Frenkel conduction, which was confirmed by a linear relationship from the Log (I/V) vs. Sqrt (V) graph. This AlO σ -based device also showed long-term potentiation and long-term depression characteristics, which are crucial in developing convolutional neural networks based neuromorphic systems, by using identical pulse series. The experimental results demonstrate that mimicking the synaptic characteristics of the neuromorphic systems would be possible with an interface switching cross-point AlO σ -based RRAM device with Au/TiO x /AlO σ /Al layer.