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A Fluorographene‐Based Synaptic Transistor
Author(s) -
Liu Bo,
Hong MingChun,
Sahoo Mamina,
Ong Bin Leong,
Tok Eng Soon,
Di MengFu,
Ho YuPing,
Liang Hanyuan,
Bow JongShing,
Liu Zhiwei,
Wang JerChyi,
Hou TuoHung,
Lai ChaoSung
Publication year - 2019
Publication title -
advanced materials technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.184
H-Index - 42
ISSN - 2365-709X
DOI - 10.1002/admt.201900422
Subject(s) - neuromorphic engineering , transistor , materials science , synaptic plasticity , hysteresis , neuroscience , computer science , optoelectronics , physics , voltage , electrical engineering , artificial neural network , chemistry , condensed matter physics , engineering , psychology , biochemistry , receptor , machine learning
Exploring brain‐inspired synaptic devices has recently become a new focus of research in nanoelectronic communities. In this emerging field, incorporating 2D materials into three‐terminal synaptic transistors has brought various advantages. However, achieving a stable and long‐term weight‐modulation in these synaptic transistors, which are typically based on interface charge storage, is still a challenge due to the nature of their spontaneous relaxation. The application of an atomically thin fluorographene layer into the synaptic junction region suppresses this issue and improves the efficiency, tunability, and symmetry of the synaptic plasticity as well as establishing a stable weight‐regulation paradigm. These unique properties can be attributed to the dipolar rotation of CF in fluorographene. To obtain a better physical understanding, a vacancy‐dependent CF dipolar rotation model is proposed and supported by hysteresis analysis and density functional theory calculations. As proposed and demonstrated, the unique fluorographene‐based synaptic transistor may be a promising building block for constructing efficient neuromorphic computing hardware.