Issue 29, 2022

Intrinsically stretchable photonic synaptic transistors for retina-like visual image systems

Abstract

The retina is supposed to be an elastic concave image sensor with neuromorphological function, allowing the eyes to accept either still or moving images depending on the regulation of the ciliary muscle. Owing to the trends of visual prosthetics and artificial intelligence, the biomimetic retina has attracted increasing interest, but there are only a few studies that have mimicked the retinal structure and function simultaneously. Inspired by the elasticity of the retina, we present a stretchable photonic synaptic transistor, where both the retinal structure and function were simulated by a single device. Similar to the real morphology of the retina, the stretchable artificial vision system can conform to the concave of the transparent hemisphere to realize the process of visual imaging. Stretchable photonic synaptic transistor is accompanied by good mechanical performance, which can maintain basic synaptic functions, such as short-term plasticity (STP), long-term plasticity (LTP), transmission from STP to LTP, and high pass filtering upon 100% tensile deformation. Furthermore, the image pre-processing of human eyes is realized by our photonic synaptic transistor on account of oxygen-induced persistent photoconductivity. This work will open the capability of intrinsically stretchable organic semiconductors for the development of stretchable photonic synapses, and thus, advance neuromorphic device technology in visual prosthetics and artificial intelligence.

Graphical abstract: Intrinsically stretchable photonic synaptic transistors for retina-like visual image systems

Supplementary files

Article information

Article type
Paper
Submitted
29 Apr 2022
Accepted
27 Jun 2022
First published
01 Jul 2022

J. Mater. Chem. C, 2022,10, 10586-10594

Intrinsically stretchable photonic synaptic transistors for retina-like visual image systems

F. Xu, C. Zhang, X. Zhao, H. Yu, G. Zhao, J. Li, B. Wang, Y. Tong, Q. Tang and Y. Liu, J. Mater. Chem. C, 2022, 10, 10586 DOI: 10.1039/D2TC01775J

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