Tetrachromatic vision-inspired neuromorphic sensors with ultraweak ultraviolet detection

Ting Jiang, Yiru Wang, Yingshuang Zheng, Le Wang, Xiang He, Liqiang Li, Yunfeng Deng, Huanli Dong, Hongkun Tian (), Yanhou Geng, Linghai Xie, Yong Lei, Haifeng Ling (), Deyang Ji () and Wenping Hu
Additional contact information
Ting Jiang: Tianjin University
Yiru Wang: Nanjing University of Posts & Telecommunications
Yingshuang Zheng: Tianjin University
Le Wang: Nanjing University of Posts & Telecommunications
Xiang He: Nanjing University of Posts & Telecommunications
Liqiang Li: Tianjin University
Yunfeng Deng: Tianjin University
Huanli Dong: Chinese Academy of Sciences
Hongkun Tian: Chinese Academy of Sciences
Yanhou Geng: Tianjin University
Linghai Xie: Nanjing University of Posts & Telecommunications
Yong Lei: Technische Universität Ilmenau
Haifeng Ling: Nanjing University of Posts & Telecommunications
Deyang Ji: Tianjin University
Wenping Hu: Haihe Laboratory of Sustainable Chemical Transformations

Nature Communications, 2023, vol. 14, issue 1, 1-9

Abstract: Abstract Sensing and recognizing invisible ultraviolet (UV) light is vital for exploiting advanced artificial visual perception system. However, due to the uncertainty of the natural environment, the UV signal is very hard to be detected and perceived. Here, inspired by the tetrachromatic visual system, we report a controllable UV-ultrasensitive neuromorphic vision sensor (NeuVS) that uses organic phototransistors (OPTs) as the working unit to integrate sensing, memory and processing functions. Benefiting from asymmetric molecular structure and unique UV absorption of the active layer, the as fabricated UV-ultrasensitive NeuVS can detect 370 nm UV-light with the illumination intensity as low as 31 nW cm−2, exhibiting one of the best optical figures of merit in UV-sensitive neuromorphic vision sensors. Furthermore, the NeuVS array exbibits good image sensing and memorization capability due to its ultrasensitive optical detection and large density of charge trapping states. In addition, the wavelength-selective response and multi-level optical memory properties are utilized to construct an artificial neural network for extract and identify the invisible UV information. The NeuVS array can perform static and dynamic image recognition from the original color image by filtering red, green and blue noise, and significantly improve the recognition accuracy from 46 to 90%.

Date: 2023
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DOI: 10.1038/s41467-023-37973-0

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