Light-adaptable and polarization-sensitive bionic vision by contact engineering for multi-dimensional imaging recognition

Simulating ambient light adaptability and polarization sensitivity of biological vision is paramount for developing intelligent optoelectronic devices with multi-dimensional perception capabilities. However, achieving both functionalities in semiconductor devices has historically necessitated complex architectures and high-voltage operation, posing significant challenges for bionic vision systems. Here, we present a light-adaptable and polarization-sensitive bionic vision utilizing a simple yet effective strategy of semiconductor-metal contact engineering in PdSe<sub>2</sub> transistors. By exploiting the differential coupling strengths at diverse metal-semiconductor interfaces to modulate the dynamics of photogenerated carriers, the device achieves energy-efficient visual adaptive perception across a broad range of lighting conditions, from dim to bright, without the need for additional gate voltage. Furthermore, this transistor enables multi-dimensional perception of visual information through dynamic polarization angle changes and light intensity (dim/bright) detection, providing rich input features for intelligent recognition in complex scenarios. Capitalizing on &nbsp;the intrinsic anisotropy of PdSe<sub>2</sub> and contact engineering, we have constructed a bionic light-adaptive visual neural network capable of perceiving and recognizing images in complex lighting environments. When enhanced by a residual-generating adversarial network, the system achieves remarkable recognition accuracies of 98% and 97% under dim and bright adaptation conditions, respectively. This research offers a streamlined, versatile, and scalable approach for developing energy-efficient, highly integrated, and multi-dimensional imaging recognition capabilities in environment-adaptive and polarization-sensitive bionic vision devices.

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Publication Details

Journal
Nano Research
Published
2025-05-06
DOI
https://doi.org/10.26599/nr.2025.94907546
Citations
2
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
1.35
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article

Light-adaptable and polarization-sensitive bionic vision by contact engineering for multi-dimensional imaging recognition

Lingan Kong, Chunlei Zhang, Pei Lin, Xiankai Lin et al.
2 citations
Nano Research
Advanced Sensor and Energy Harvesting Materials
1.35
article

Light-adaptable and polarization-sensitive bionic vision by contact engineering for multi-dimensional imaging recognition

Lingan Kong, Chunlei Zhang, Pei Lin, Xiankai Lin, Qijie Liang, Ziling Chen, Wenbo Li, Shihong Ma, Guitian Qiu, Junli Du
article en
2 citations

Abstract

Simulating ambient light adaptability and polarization sensitivity of biological vision is paramount for developing intelligent optoelectronic devices with multi-dimensional perception capabilities. However, achieving both functionalities in semiconductor devices has historically necessitated complex architectures and high-voltage operation, posing significant challenges for bionic vision systems. Here, we present a light-adaptable and polarization-sensitive bionic vision utilizing a simple yet effective strategy of semiconductor-metal contact engineering in PdSe<sub>2</sub> transistors. By exploiting the differential coupling strengths at diverse metal-semiconductor interfaces to modulate the dynamics of photogenerated carriers, the device achieves energy-efficient visual adaptive perception across a broad range of lighting conditions, from dim to bright, without the need for additional gate voltage. Furthermore, this transistor enables multi-dimensional perception of visual information through dynamic polarization angle changes and light intensity (dim/bright) detection, providing rich input features for intelligent recognition in complex scenarios. Capitalizing on &nbsp;the intrinsic anisotropy of PdSe<sub>2</sub> and contact engineering, we have constructed a bionic light-adaptive visual neural network capable of perceiving and recognizing images in complex lighting environments. When enhanced by a residual-generating adversarial network, the system achieves remarkable recognition accuracies of 98% and 97% under dim and bright adaptation conditions, respectively. This research offers a streamlined, versatile, and scalable approach for developing energy-efficient, highly integrated, and multi-dimensional imaging recognition capabilities in environment-adaptive and polarization-sensitive bionic vision devices.

Nano ResearchVol. 18(8)
Openalex Percentile: Top 20%
Advanced Sensor and Energy Harvesting Materials
1.35
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