Self-Powered Optoelectronic Synaptic Devices for Neuromorphic Computing with the Lowest Energy Consumption Density

Abstract

Recently, self-powered optoelectronic synaptic devices have attracted great attention due to their bias-free and self-rectifying properties for future computing systems. However, high energy consumption may still be required to generate optical signals for the stimulation of the systems. In this work, self-powered optoelectronic synaptic devices are fabricated based on triple mixed cation perovskites with excellent synaptic stability. Various synaptic functions are mimicked in these devices, which are stimulated by a fully visible light spectral range. These devices demonstrate the lowest energy consumption density and the best consistency properties of all reported self-powered optoelectronic synaptic devices to date. Color classification and speech recognition are successfully implemented with high accuracy in these systems. The results significantly promote the development of self-powered systems in neuromorphic computing.