Nanostructured CuO-Based Reversible Memristor Devices and Their Performance During Heating/Cooling Measurements

This article demonstrates the synthesis, characterization, scalable fabrication, and heating/cooling measurements of nanostructured copper oxide (CuO) based reversible memristors. The memristor’s fabrication process is related to IC-compatible microfabrication techniques and the possibility of integrating with on-chip processes. All tested memristor devices have shown bipolar resistive switching behavior. The memristors are capable of offering a high endurance of 500 cycles and a high resistance state (HRS) to low resistance state (LRS) ratio of $2\times 10^{2}$ . The process scalability and device stability were tested using processed 2-in silicon (Si) wafers for a year in the ambient environment. Furthermore, the reversible properties of the fabricated memristor were analyzed by stimulating the device using thermal stress. The reversible measurements were conducted by varying the temperature ( $293~\to ~403~\to ~293$ K) using a probe station associated with the heater and thermocouple. The devices and their characteristics at different temperatures confirm that the fabricated samples are reversible in nature. The developed memristors are useful for high-temperature and storage applications.

I. Introduction

Replication of the human brain’s synapse and data transfer mechanism has opened new roots for developing neuromorphic systems. Resistive switching devices such as memristors and synaptic transistors are considered as potential candidates for applications including data transmission, security, storage, memory logic, nonvolatile logic systems, neuromorphic computing, and so on [1]. Memristors are considered one of the important devices, which have the potential to replace transistor-based memories. These devices have advantages like tunable resistance states, nonvolatility, high endurance, high data retention capability, high speed, low power consumption, scalability, and so on [2]. In the case of the human brain, data is transferred from presynaptic neuron to postsynaptic neuron through synapse. Similarly, in the case of memristors, active material plays a predominant role in the charge transition between the top electrode and the bottom electrode. Resistive switching occurs due to variation of resistance state (HRS to LRS and vice versa) with respect to the applied stimuli [3], [4]. Various mechanisms are presented in the literature related to resistive switching mechanisms such as formation/rupture of conductive filaments, interface switching, metal-to-insulator transition, barrier height modulation, and so on [3], [4], [5].