Floating gate photo-memory devices based on van der Waals heterostructures for neuromorphic image recognition

Abstract

Two-dimensional (2D) materials with reconfigurable properties show potential in neuromorphic hardware applications. However, most 2D materials-based neuromorphic hardware is volatile, which needs large energy to accomplish perception functions. Here, we report on nonvolatile floating gate photo-memory devices based on ReS2/h-BN/SnS2 van der Waals heterostructures. The devices exhibit a large memory window of ∼60 V, a high program/erase current ratio of ∼107 with excellent retention characteristics, a low off-state current of 7.4 × 10−13 A, and a high detectivity of 1.98 × 1013 cm Hz1/2 W−1, allowing for multi-bit information storage. For the multi-level storage capacity, 27 photo-memory states are obtained by pulsed laser illumination. Moreover, a neuromorphic computing network is also constructed based on the photo-memory devices with a maximum recognition accuracy of up to 90%. This work paves the way for miniaturization and high-density integration of future optoelectronics for neuromorphic hardware applications.