Highly Uniform All-Vacuum-Deposited Inorganic Perovskite Artificial Synapses for Reservoir Computing

被引:30
作者
Chen, Li-Wei [1 ]
Wang, Wei-Chun [1 ]
Ko, Shao-Han [2 ]
Chen, Chien-Yu [1 ]
Hsu, Chih-Ting [1 ]
Chiao, Fu-Ching [1 ]
Chen, Tse-Wei [1 ]
Wu, Kai-Chiang [2 ]
Lin, Hao-Wu [1 ]
机构
[1] Natl Tsing Hua Univ, Dept Mat Sci & Engn, Hsinchu 30013, Taiwan
[2] Natl Chiao Tung Univ, Dept Comp Sci, Hsinchu 30010, Taiwan
关键词
artificial synapses; inorganic halide perovskites; neuromorphic computing; reservoir computing; vacuum deposition; LONG-TERM POTENTIATION; LIGHT-EMITTING-DIODES; PHASE-CHANGE MEMORY; SOLAR-CELLS; SYNAPTIC PLASTICITY; WORK-FUNCTION; EFFICIENCY; DEVICES; DESIGN;
D O I
10.1002/aisy.202000196
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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/MoO3/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.
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页数:11
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