Internal ion transport in ionic 2D CuInP2S6 enabling multi-state neuromorphic computing with low operation current

Abstract

Memristor-based neuromorphic computing is promising for artificial intelligence. However, most of the reported memristors have limited linear computing states and consume large operation energy which hinder their applications. Herein, we report a memristor based on ionic two-dimensional CuInP2S6 (2D CIPS), in which up to 1350 linear conductance states are achieved by controlling the migration of internal Cu ions in CIPS. In addition, the device shows a low operation current of ∼100 pA. Cu ions are proven to move along the electric field by in-situ scanning electron microscopy and energy dispersive spectroscopy measurements. Furthermore, complex signal transport among multiple neurons in the brain is imitated by 2D CIPS-based memristor arrays. Our results offer a new platform to fabricate high-performance memristors based on ion transport in 2D materials for neuromorphic computing.