A 2D Heterostructure‐Based Multifunctional Floating Gate Memory Device for Multimodal Reservoir Computing
Jiajia Zha, Yunpeng Xia, Shuhui Shi, Haoxin Huang, Siyuan Li, Chen Qian, Huide Wang, Peng Yang, Zhuomin Zhang, You Meng, Wei Wang, Zhengbao Yang, Hongyu Yu, Johnny Chung Yin Ho, Zhongrui Wang, Chaoliang Tan · Advanced Materials · 2023
Abstract The demand for economical and efficient data processing has led to a surge of interest in neuromorphic computing based on emerging two‐dimensional (2D) materials in recent years. As a rising van der Waals (vdW) p ‐type Weyl semiconductor with many intriguing properties, tellurium (Te) has been widely used in advanced electronics/optoelectronics. However, its application in floating gate (FG) memory devices for information processing has never been explored. Herein, an electronic/optoelectronic FG memory device enabled by Te‐based 2D vdW heterostructure for multimodal reservoir computing (RC) is reported. When subjected to intense electrical/optical stimuli, the device exhibits impressive nonvolatile electronic memory behaviors including ≈10 8 extinction ratio, ≈100 ns switching speed, >4000 cycles, >4000‐s retention stability, and nonvolatile multibit optoelectronic programmable characteristics. When the input stimuli weaken, the nonvolatile memory degrades into volatile memory. Leveraging these rich nonlinear dynamics, a multimodal RC system with high recognition accuracy of 90.77% for event‐type multimodal handwritten digit‐recognition is demonstrated.