Volatile Resistive Switching Characteristics of Pt/HfO2/TaOx/TiN Short-Term Memory Device

Machine Learning Methods and Sustainable Development: Metal Oxides and Multilayer Metal Oxides

The development of nanotechnologies and new methods of machine learning are responsible for the significant attention and demand for metal oxides and multilayer metal-oxide nanostructures [...]

Multi-Level Resistive Switching of Pt/HfO2/TaN Memory Device

This work characterizes resistive switching and neuromorphic simulation of Pt/HfO2/TaN stack as an artificial synaptic device. A stable bipolar resistive switching operation is performed by repetitive DC sweep cycles. Furthermore, endurance (DC 100 cycles) and retention (5000 s) are demonstrated for reliable resistive operation. Low-resistance and high-resistance states follow the Ohmic conduction and Poole–Frenkel emission, respectively, which is verified through the fitting process. For practical operation, the set and reset processes are performed through pulses. Further, potentiation and depression are demonstrated for neuromorphic application. Finally, neuromorphic system simulation is performed through a neural network for pattern recognition accuracy of the Fashion Modified National Institute of Standards and Technology dataset.

Demonstration of Threshold Switching and Bipolar Resistive Switching in Ag/SnOx/TiN Memory Device

In this work, we observed the duality of threshold switching and non-volatile memory switching of Ag/SnOx/TiN memory devices by controlling the compliance current (CC) or pulse amplitude. The insulator thickness and chemical analysis of the device stack were confirmed by transmission electron microscope (TEM) images of the Ag/SnOx/TiN stack and X-ray photoelectron spectroscopy (XPS) of the SnOx film. The threshold switching was achieved at low CC (50 μA), showing volatile resistive switching. Optimal CC (5 mA) for bipolar resistive switching conditions with a gradual transition was also found. An unstable low-resistance state (LRS) and negative-set behavior were observed at CCs of 1 mA and 30 mA, respectively. We also demonstrated the pulse operation for volatile switching, set, reset processes, and negative-set behaviors by controlling pulse amplitude and polarity. Finally, the potentiation and depression characteristics were mimicked by multiple pulses, and MNIST pattern recognition was calculated using a neural network, including the conductance update for a hardware-based neuromorphic system.