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- Title
Retina‐Inspired Artificial Synapses with Ultraviolet to Near‐Infrared Broadband Responses for Energy‐Efficient Neuromorphic Visual Systems.
- Authors
Zhang, Junyao; Guo, Pu; Guo, Ziyi; Li, Li; Sun, Tongrui; Liu, Dapeng; Tian, Li; Zu, Guoqing; Xiong, Lize; Zhang, Jianhua; Huang, Jia
- Abstract
Neuromorphic visual system with image perception, memory, and preprocessing functions is expected to simulate basic features of the human retina. Organic optoelectronic synaptic transistors emulating biological synapses may be promising candidates for constructing neural morphological visual system. However, the sensing wavelength range of organic optoelectronic synaptic transistors usually limits their potential in artificial multispectral visual perception. Here, retina‐inspired optoelectronic synaptic transistors that present broadband responses covering ultraviolet, visible, and near‐infrared regions are demonstrated, which leverage the wide‐range photoresponsive charge trapping layer and the heterostructure formed between PbS quantum dots and organic semiconductor. Simplified neuromorphic visual arrays are developed to simulate comprehensive image perception, memory, and preprocessing functions. Benefitting from the flexibility of the charge trapping and organic semiconductor layers, a flexible neuromorphic visual array can be fabricated, having an ultralow power consumption of 0.55 fJ per event under a low operating voltage of −0.01 V. More significantly, an accelerating image preprocessing effect can be observed in a wide wavelength range even beyond the perception range of the human visual system, due to the gate‐adjustable synaptic plasticity. These devices are highly promising for implementing neuromorphic visual systems with broadband perception, increasing image processing efficiency, and promoting the development of artificial vision.
- Subjects
QUANTUM dots; SEMICONDUCTOR quantum dots; ORGANIC semiconductors; RETINA; SYNAPSES; ARTIFICIAL vision; NEUROPLASTICITY
- Publication
Advanced Functional Materials, 2023, Vol 33, Issue 32, p1
- ISSN
1616-301X
- Publication type
Article
- DOI
10.1002/adfm.202302885