A flexible ultrasensitive optoelectronic sensor array for neuromorphic vision systems

The challenges of developing neuromorphic vision systems inspired by the human eye come not only from how to recreate the flexibility, sophistication, and adaptability of animal systems, but also how to do so with computational efficiency and elegance. Similar to biological systems, these neuromorph...

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Vydané v:Nature communications Ročník 12; číslo 1; s. 1798 - 7
Hlavní autori: Zhu, Qian-Bing, Li, Bo, Yang, Dan-Dan, Liu, Chi, Feng, Shun, Chen, Mao-Lin, Sun, Yun, Tian, Ya-Nan, Su, Xin, Wang, Xiao-Mu, Qiu, Song, Li, Qing-Wen, Li, Xiao-Ming, Zeng, Hai-Bo, Cheng, Hui-Ming, Sun, Dong-Ming
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Nature Publishing Group UK 19.03.2021
Nature Publishing Group
Nature Portfolio
Predmet:
142/126
147/135
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147/3
639/301/1005/1007
639/301/357/1017
639/301/357/73
639/925/927/1007
Adaptability
Artificial vision
Carbon nanotubes
Flexibility
Flexible components
Humanities and Social Sciences
Learning
multidisciplinary
Nanotechnology
Nanotubes
Optoelectronic devices
Perovskites
Pixels
Quantum dots
Reinforcement
Science
Science (multidisciplinary)
Sensitivity
Sensor arrays
Sensors
Signal processing
Vision systems
ISSN:2041-1723, 2041-1723
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Shrnutí:The challenges of developing neuromorphic vision systems inspired by the human eye come not only from how to recreate the flexibility, sophistication, and adaptability of animal systems, but also how to do so with computational efficiency and elegance. Similar to biological systems, these neuromorphic circuits integrate functions of image sensing, memory and processing into the device, and process continuous analog brightness signal in real-time. High-integration, flexibility and ultra-sensitivity are essential for practical artificial vision systems that attempt to emulate biological processing. Here, we present a flexible optoelectronic sensor array of 1024 pixels using a combination of carbon nanotubes and perovskite quantum dots as active materials for an efficient neuromorphic vision system. The device has an extraordinary sensitivity to light with a responsivity of 5.1 × 10 7  A/W and a specific detectivity of 2 × 10 16 Jones, and demonstrates neuromorphic reinforcement learning by training the sensor array with a weak light pulse of 1 μW/cm 2 . To emulate nature biological processing, highly-integrated ultra-sensitive artificial neuromorphic system is highly desirable. Here, the authors report flexible sensor array of 1024 pixels using combination of carbon nanotubes and perovskite QDs as active matetials, achieving highly responsive device for reinforcement learning.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-021-22047-w