A Self-Powered Organic Vision Sensor Array for Photopic Adaptation
With the rapid development of artificial intelligence, it is essential to develop a bionic vision sensor that boasts low power consumption, self-adaptability, and broadband sensing for efficient image preprocessing. We employed an organic p-type semiconductor, poly(3-hexylthiophene-2,5-diyl) (P3HT), in conjunction with an Al electrode to engineer a Schottky junction. This design leverages the photogating effect due to the charge trapping by defects at the P3HT/Al interface, endowing this self-powered, two-terminal device with photopic adaptability. The 1.9 eV bandgap of P3HT enables substantial light absorption within the visible spectrum, yielding a significant photocurrent. By assembling 50 photoelectric sensors into a 10 × 5 array, we successfully demonstrated an image formation process that emulates photopic adaptation, specifically in recognizing letters. This easily fabricated, self-powered retinomorphic photoelectric device has great potential to mimic retinal structures, thereby heralding a new frontier in visual sensory devices.
Authors
- Junhao Chu (ORCID: https://orcid.org/0000-0003-1867-9296)
- Shenglan Hao (ORCID: https://orcid.org/0000-0001-8821-4449)
- Guangdi Feng
- Hui Peng (ORCID: https://orcid.org/0000-0002-9062-2799)
- Bobo Tian (ORCID: https://orcid.org/0000-0002-4251-2755)
- Chun‐Gang Duan (ORCID: https://orcid.org/0000-0002-5380-4980)
- Qiuxiang Zhu (ORCID: https://orcid.org/0000-0002-3515-315X)
- Yannan Dai
- Wei Li (ORCID: https://orcid.org/0000-0001-8400-8074)
- Jianquan Liu (ORCID: https://orcid.org/0000-0001-5309-5128)
Institutions
- Chongqing Normal University (CN)
- Fudan University (CN)
- Institute of Microelectronics (CN)
- Shanghai Institute of Technical Physics (CN)
- Shanxi University of Traditional Chinese Medicine (CN)
- Infrared Laboratories (United States) (US)
- Shanghai Center for Brain Science and Brain-Inspired Technology (CN)
- State Key Laboratory of Infrared Physics
- East China Normal University (CN)
Publication Details
- Journal
- Nano Letters
- Published
- 2025-02-10
- DOI
- https://doi.org/10.1021/acs.nanolett.4c06090
- Citations
- 5
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 3.65
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Chongqing
- National Key Research and Development Program of China
- Fundamental Research Funds for the Central Universities
- Science and Technology Innovation Plan Of Shanghai Science and Technology Commission