A 2D Heterostructure‐Based Multifunctional Floating Gate Memory Device for Multimodal Reservoir Computing

Author:

Zha Jiajia1,Xia Yunpeng2,Shi Shuhui34,Huang Haoxin2,Li Siyuan5,Qian Chen5,Wang Huide1,Yang Peng6,Zhang Zhuomin7,Meng You1,Wang Wei1,Yang Zhengbao78,Yu Hongyu4,Ho Johnny C.1,Wang Zhongrui3,Tan Chaoliang3ORCID

Affiliation:

1. Department of Materials Science and Engineering City University of Hong Kong Hong Kong SAR 999077 China

2. Department of Electrical Engineering City University of Hong Kong Hong Kong SAR 999077 China

3. Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong SAR 999077 China

4. School of Microelectronics Southern University of Science and Technology Shenzhen Guangdong 518055 China

5. Department of Chemistry City University of Hong Kong Hong Kong SAR 999077 China

6. College of Integrated Circuits and Optoelectronic Chips Shenzhen Technology University Shenzhen Guangdong 518118 China

7. Department of Mechanical Engineering City University of Hong Kong Hong Kong SAR 999077 China

8. Department of Mechanical and Aerospace Engineering Hong Kong University of Science and Technology Hong Kong SAR 999077 China

Abstract

AbstractThe 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 ≈108 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.

Publisher

Wiley

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

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