Open AccessHighly Uniform All‐Vacuum‐Deposited Inorganic Perovskite Artificial Synapses for Reservoir Computing
Author(s) -
Chen Li-Wei,
Wang Wei-Chun,
Ko Shao-Han,
Chen Chien-Yu,
Hsu Chih-Ting,
Chiao Fu-Ching,
Chen Tse-Wei,
Wu Kai-Chiang,
Lin Hao-Wu
Publication year - 2021
Publication title -
advanced intelligent systems
Language(s) - English
Resource type - Journals
ISSN - 2640-4567
DOI - 10.1002/aisy.202000196
Subject(s) - neuromorphic engineering , perovskite (structure) , long term potentiation , reservoir computing , computer science , homogeneous , neural facilitation , voltage , artificial neural network , materials science , synaptic weight , facilitation , nanotechnology , neuroscience , artificial intelligence , chemistry , physics , electrical engineering , engineering , recurrent neural network , biochemistry , receptor , biology , thermodynamics , crystallography
The development of artificial synapses is inspired by the energy‐efficient recognition ability of the central nervous system of living organisms and is proposed for use as the basic building units of next‐generation neuromorphic computing networks. Herein, the perovskite/MoO 3 /Ag synaptic device exhibits very uniform electrical characteristics, a low operation voltage, and linear and repeatable analog switching. Important synaptic functions such as paired‐pulse facilitation (PPF) and short‐ and long‐term potentiation (STP/LTP) are all successfully and stably implemented in the device. The diffusion of Ag + and I − ions is believed to contribute to the synaptic behavior of the device. Furthermore, the uniform and stable volatile characteristics are utilized in a proof‐of‐concept reservoir‐computing‐based simulation program using all the experimental parameters; the results strongly suggest that the neuromorphic computing that utilizes such components can simultaneously reduce the circuitry complexity and increase its recognition accuracy with noisy inputs. The findings of this work promise to significantly facilitate the utilization of highly homogeneous vacuum‐deposited perovskite/metal oxide structures in high‐performance neuromorphic computing systems.