Pd/IGZO/p(+)-Si Synaptic Device with Self-Graded Oxygen Concentrations for Highly Linear Weight Adjustability and Improved Energy Efficiency

Abstract

Non-von-Neumann computer architecture is gaining a great deal of interest for eliminating the speed bottleneck in transferring data between the processing and memory units by improving the processing parallelism. Hardware-driven neuromorphic systems are pursued actively for this goal, and they should accompany the innovations in the hardware components for higher energy efficiency. In this work, an indium gallium zinc oxide (IGZO)-based synaptic device was developed, and its synaptic behaviors were closely characterized. Processing simplicity has been improved in the structure of the device using a p(+)-Si bottom electrode (BE) in the Si substrate, and gradual switching characteristics have been obtained using a Pd top electrode (TE) with self-graded oxygen concentrations. By controlling the amount of oxygen atoms in depositing the switching layer, both highly linear weight adjustability and low-energy operation capability have been accomplished. In the end, the visual recognition of the IGZO synaptic device is evaluated with the Modified National Institute of Standards and Technology (MNIST) patterns in the neural network.