Electronic/optoelectronic memory device enabled by tellurium-based 2D van der Waals heterostructure for in-sensor reservoir computing at the optical communication band

• Main Authors: Zha, Jiajia, Shi, Shuhui, Chaturvedi, Apoorva, Huang, Haoxin, Yang, Peng, Yao, Yao, Li, Siyuan, Xia, Yunpeng, Zhang, Zhuomin, Wang, Wei, Wang, Huide, Wang, Shaocong, Yuan, Zhen, Yang, Zhengbao, He, Qiyuan, Tai, Huiling, Teo, Edwin Hang Tong, Yu, Hongyu, Ho, Johnny C., Wang, Zhongrui, Zhang, Hua, Tan, Chaoliang
• Other Authors: School of Materials Science and Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Engineering::Materials; Engineering::Electrical and electronic engineering; 2D Tellurium; van der Waals Heterostructures
• Online Access: https://hdl.handle.net/10356/172939
• Institution: Nanyang Technological University

Although 2D materials are widely explored for data storage and neuromorphic computing, the construction of 2D material-based memory devices with optoelectronic responsivity in the short-wave infrared (SWIR) region for in-sensor reservoir computing (RC) at the optical communication band still remains a big challenge. In this work, an electronic/optoelectronic memory device enabled by tellurium-based 2D van der Waals (vdW) heterostructure is reported, where the ferroelectric CuInP2 S6 and tellurium channel endow this device with both the long-term potentiation/depression by voltage pulses and short-term potentiation by 1550 nm laser pulses (a typical wavelength in the conventional fiber optical communication band). Leveraging the rich dynamics, a fully memristive in-sensor RC system that can simultaneously sense, decode, and learn messages transmitted by optical fibers is demonstrated. The reported 2D vdW heterostructure-based memory featuring both the long-term and short-term memory behaviors using electrical and optical pulses in SWIR region has not only complemented the wide spectrum of applications of 2D materials family in electronics/optoelectronics but also paves the way for future smart signal processing systems at the edge.