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 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.
Authors
- Lingan Kong (ORCID: https://orcid.org/0000-0001-5300-3174)
- Chunlei Zhang (ORCID: https://orcid.org/0000-0003-3243-2521)
- Pei Lin (ORCID: https://orcid.org/0000-0002-3300-5241)
- Xiankai Lin (ORCID: https://orcid.org/0009-0004-7010-3360)
- Qijie Liang (ORCID: https://orcid.org/0000-0003-4252-7997)
- Ziling Chen (ORCID: https://orcid.org/0000-0003-1749-7394)
- Wenbo Li (ORCID: https://orcid.org/0000-0003-0741-9210)
- Shihong Ma (ORCID: https://orcid.org/0009-0003-3810-071X)
- Guitian Qiu
- Junli Du
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