Flexible optoelectronic N-I-P synaptic device with visible spectrum perception for energy-efficient artificial vision and efferent neuromuscular system

Author:

Wei Huanhuan12,Fu Can1,Yang Wen34,He Gang1ORCID,Guo Jiahao34,Ni Yao5ORCID,Gong Jiangdong34ORCID

Affiliation:

1. School of Materials Science and Engineering, Anhui University 1 , Hefei, Anhui 230601, People's Republic of China

2. Institutes of Physical Science and Information Technology, Anhui University 2 , Hefei, Anhui 230601, People's Republic of China

3. School of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China 3 , Hefei, Anhui 230026, People's Republic of China

4. Center for Intelligent Medical Equipment and Devices, Suzhou Institute for Advanced Research, University of Science and Technology of China 4 , Suzhou, Jiangsu 215123, People's Republic of China

5. School of Integrated Circuits, Guangdong University of Technology 5 , Guangzhou, Guangdong 510006, People's Republic of China

Abstract

We have designed a flexible photoelectric artificial synapse with an oxide/mixed perovskite/polymer N-I-P structure that exhibits essential synaptic plasticity. Formamidinium lead triiodide FAPbI3 perovskite doped with bromine and methylammonium (FAxMA1−xPbI2Br) is employed as the intrinsic layer to improve the optical properties of devices. Without requiring a power source in reaction to outside optical spikes, multiple pulse-dependent plasticity is reproduced on the synaptic devices, and the image's edges are sharpened using high-pass filtering. Additionally, the classical conditioning and spatiotemporal learning are copied under the electric pulse excitation. Significant negative differential resistance is evident, even after 1500 flex/flat mechanical operation. The recognition rate of letters in the visual system is as high as 92%, and the walking distance in the efferent neuromuscular system is controllable. The flexible optoelectronic N-I-P synaptic device is designed to facilitate energy-efficient information processing for neuromorphic computing.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Anhui Province

China Postdoctoral Science Foundation

Publisher

AIP Publishing

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