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Flexible Artificial Memristive Synapse Constructed from Solution‐Processed MgO–Graphene Oxide Quantum Dot Hybrid Films
Author(s) -
Chen Tong,
Yang Siwei,
Wang Jing,
Chen Wei,
Liu Lifu,
Wang Yuan,
Cheng Shijie,
Zhao Xu
Publication year - 2021
Publication title -
advanced electronic materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.25
H-Index - 56
ISSN - 2199-160X
DOI - 10.1002/aelm.202000882
Subject(s) - materials science , neuromorphic engineering , graphene , quantum dot , memristor , nanotechnology , synapse , oxide , artificial neural network , optoelectronics , computer science , electronic engineering , artificial intelligence , neuroscience , engineering , metallurgy , biology
Inspired by the low energy consumption and highly parallel processing power of the biological neuromorphic system, the development of a brain‐inspired computing paradigm with electronic devices based artificial synapse may play an essential role in eliminating the Von Neumann bottleneck. Among candidate electronic devices, memristive devices have shown great potential for artificial synapse because of its tunable resistive switching (RS) behaviors. Herein, a biological synapse with solution‐processed MgO‐graphene oxide quantum dots (MgO‐GOQDs) based memristor is developed. The device exhibits highly controllable RS behavior owing to the enhancement of the local electric field by GOQDs and redox of GOQDs under electric fields. Moreover, essential biosynaptic functions including paired‐pulse facilitation, short‐term plasticity (STP)/long‐term plasticity (LTP), STP to LTP transition, and spike‐time‐dependent plasticity are successfully emulated. It is noteworthy that the device fabricated on a polyethylene terephthalate substrate also presents stable RS behavior after a large number of bending cycles. This study demonstrates the great potential of solution‐processed MgO–GOQD hybrid film on its application for the realization of flexible artificial neural networks.