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-NiO_x/n-ZnO heterojunction, and its analog synapse operation with high selectivity is demonstrated in 32 × 32 crossbar array architecture without the aid of selector devices. The built-in potential barrier at p-NiO_x/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.