Self-Selective Crossbar Synapse Array with n-ZnO/p-NiOx/n-ZnO Structure for Neuromorphic Computing

Abstract

Artificial synapse devices are essential elements for highly energy-efficient neuromorphic computing. They are implemented as crossbar array architecture, where highly selective synaptic weight updates for training and sneak leakage-free inference operations are required. In this study, self-selective bipolar artificial synapse device is proposed with n-ZnO/p-NiOx/n-ZnO heterojunction, and its analog synapse operation with high selectivity is demonstrated in 32 x 32 crossbar array architecture without the aid of selector devices. The built-in potential barrier at p-NiOx/n-ZnO junction and the Zener tunneling effect provided nonlinear current-voltage characteristics at both voltage polarities for self-selecting function for synaptic potentiation and depression operations. Voltage-driven redistribution of oxygen ions inside n-p-n oxide structure, evidenced by x-ray photoelectron spectroscopy, modulated the distribution of oxygen vacancies in the layers and consequent conductance in an analog manner for the synaptic weight update operation. It demonstrates that the proposed n-p-n oxide device is a promising artificial synapse device implementing self-selectivity and analog synaptic weight update in a crossbar array architecture for neuromorphic computing.