Adaptive Optoelectronic Transistor Enabled by Nanoporous Patterning for Low‐Contrast Image Recognition

Abstract Photoadaptive neuromorphic device is fundamental for artificial vision system to effectively perceive and accurately process information in complex light scenes. However, adaptive optoelectronic device remains a challenge due to the difficulty in achieving the light‐dependent modulation of charge dynamics. Here, an adaptive optoelectronic transistor enabled by the conformal nanoporous patterning that can perform the biomimetic eye functions and facilitate the precise contrast enhancement under harsh lighting conditions is reported. The enhanced light absorption, photoexciton separation, and charge injection properties are originated from the localized electric field in the nanoporous optoelectronic transistor, which further endow the light intensity‐dependent charge trapping and de‐trapping dynamics, realizing the adaptive decay rate of conduction states. Based on the improved device performances and the adaptive properties, an artificial vision system is constructed to present the biomimetic eye model with visual selective attention functions and a contrast enhancement in the low‐contrast sub‐images. The eye rotation and closing functions, as well as a high recognition accuracy of 95.4% for non‐ideal image with a contrast as low as 0.8% are demonstrated. This study provide an approach for the photoadaptive neuromorphic device and support their visual adaptation applications in biomimetic eye system.

Authors

Institutions

Publication Details

Journal
Advanced Functional Materials
Published
2024-10-02
DOI
https://doi.org/10.1002/adfm.202414546
Citations
9
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.88

Funders

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article

Adaptive Optoelectronic Transistor Enabled by Nanoporous Patterning for Low‐Contrast Image Recognition

Jingwei Fu, Haifeng Ling, Mingdong Yi, Jing Hua et al.
9 citations
Advanced Functional Materials
Advanced Memory and Neural Computing
1.88
article

Adaptive Optoelectronic Transistor Enabled by Nanoporous Patterning for Low‐Contrast Image Recognition

Jingwei Fu, Haifeng Ling, Mingdong Yi, Jing Hua, Shanshuo Liu, Yiru Wang, Wen Li, Le Wang, Wei Huang, Linghai Xie, Hongxin Zhang, Xiang He, Jiahao Li
article en
9 citations

Abstract

Abstract Photoadaptive neuromorphic device is fundamental for artificial vision system to effectively perceive and accurately process information in complex light scenes. However, adaptive optoelectronic device remains a challenge due to the difficulty in achieving the light‐dependent modulation of charge dynamics. Here, an adaptive optoelectronic transistor enabled by the conformal nanoporous patterning that can perform the biomimetic eye functions and facilitate the precise contrast enhancement under harsh lighting conditions is reported. The enhanced light absorption, photoexciton separation, and charge injection properties are originated from the localized electric field in the nanoporous optoelectronic transistor, which further endow the light intensity‐dependent charge trapping and de‐trapping dynamics, realizing the adaptive decay rate of conduction states. Based on the improved device performances and the adaptive properties, an artificial vision system is constructed to present the biomimetic eye model with visual selective attention functions and a contrast enhancement in the low‐contrast sub‐images. The eye rotation and closing functions, as well as a high recognition accuracy of 95.4% for non‐ideal image with a contrast as low as 0.8% are demonstrated. This study provide an approach for the photoadaptive neuromorphic device and support their visual adaptation applications in biomimetic eye system.

Advanced Functional MaterialsVol. 35(5)
Nanjing University of Posts and Telecommunications (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 14%
Advanced Memory and Neural Computing
1.88
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