Charge-Mediated Copper-Iodide-Based Artificial Synaptic Device with Ultrahigh Neuromorphic Efficacy

Abstract

In the realm of artificial intelligence, ultrahigh-performance neuromorphic computing plays a significant role in executing multiple complex operations in parallel while adhering to a more biologically plausible model. Despite their importance, developing an artificial synaptic device to match the human brain's efficiency is an extremely complex task involving high energy consumption and poor parallel processing latency. Herein, a simple molecule, copper-iodide-based artificial synaptic device demonstrating core synaptic functions of human neural networks is introduced. Exceptionally high carrier mobility and dielectric constant in the developed device lead to superior efficacies in neuromorphic characteristics with ultrahigh paired-pusle facilitation index (>195). The results demonstrate biomimetic capabilities that exert a direct influence on neural networks across multiple timescales, ranging from short- to long-term memory. This flexible reconfiguration of neural excitability provided by the copper-iodide-based synaptic device positions it as a promising candidate for creating advanced artificial intelligence systems.