Geometric Shape Recognition with an Ultra-High Density Perovskite Nanowire Array-Based Artificial Vision System
Swapnadeep Poddar, Zhesi Chen, Shivam Kumar, Daquan Zhang, Yucheng Ding, Zhenghao Long, Zichao Ma, Qianpeng Zhang, Zhiyong Fan
- 发表年份
- 2024
- 引用次数
- 8
摘要
Artificial vision systems (AVS) have potential applications in visual prosthetics and artificially intelligent robotics, and they require a preprocessor and a processor to mimic human vision. Halide perovskite (HP) is a promising preprocessor and processor due to its excellent photoresponse, ubiquitous charge migration pathways, and innate hysteresis. However, the material instability associated with HP thin films hinders their utilization in physical AVSs. Herein, we have developed ultrahigh-density arrays of robust HP nanowires (NWs) rooted in a porous alumina membrane (PAM) as the active layer for an AVS. The NW devices exhibit gradual photocurrent change, responding to changes in light pulse duration, intensity, and number, and allow contrast enhancement of visual inputs with a device lifetime of over 5 months. The NW-based processor possesses temporally stable conductance states with retention >105 s and jitter <10%. The physical AVS demonstrated 100% accuracy in recognizing different shapes, establishing HP as a reliable material for neuromorphic vision systems.
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