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Reconfigurable Logic‐in‐Memory and Multilingual Artificial Synapses Based on 2D Heterostructures
Author(s) -
Xiong Xiong,
Kang Jiyang,
Hu Qianlan,
Gu Chengru,
Gao Tingting,
Li Xuefei,
Wu Yanqing
Publication year - 2020
Publication title -
advanced functional materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.069
H-Index - 322
eISSN - 1616-3028
pISSN - 1616-301X
DOI - 10.1002/adfm.201909645
Subject(s) - heterojunction , materials science , non volatile memory , computer science , ternary operation , artificial neural network , optoelectronics , nanotechnology , artificial intelligence , programming language
Nonvolatile logic devices have attracted intensive research attentions recently for energy efficiency computing, where data computing and storage can be realized in the same device structure. Various approaches have been adopted to build such devices; however, the functionality and versatility are still very limited. Here, 2D van der Waals heterostructures based on direct bandgap materials black phosphorus and rhenium disulfide for the nonvolatile ternary logic operations is demonstrated for the first time with the ultrathin oxide layer from the black phosphorus serving as the charge trapping as well as band‐to‐band tunneling layer. Furthermore, an artificial electronic synapse based on this heterostructure is demonstrated to mimic trilingual synaptic response by changing the input base voltage. Besides, artificial neural network simulation based on the electronic synaptic arrays using the handwritten digits data sets demonstrates a high recognition accuracy of 91.3%. This work provides a path toward realizing multifunctional nonvolatile logic‐in‐memory applications based on novel 2D heterostructures.