Liu Sixian, Wu Zhixin, He Zhilong, Chen Weilin, Zhong Xiaolong, Guo Bingjie, Liu Shuzhi, Duan Hongxiao, Guo Yanbo, Zeng Jianmin, Liu Gang
National Key Laboratory of Advanced Micro and Nano Manufacture Technology, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China.
Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China.
ACS Appl Mater Interfaces. 2024 May 1;16(17):22303-22311. doi: 10.1021/acsami.4c04398. Epub 2024 Apr 16.
The advancement of artificial intelligent vision systems heavily relies on the development of fast and accurate optical imaging detection, identification, and tracking. Framed by restricted response speeds and low computational efficiency, traditional optoelectronic information devices are facing challenges in real-time optical imaging tasks and their ability to efficiently process complex visual data. To address the limitations of current optoelectronic information devices, this study introduces a novel photomemristor utilizing halide perovskite thin films. The fabrication process involves adjusting the iodide proportion to enhance the quality of the halide perovskite films and minimize the dark current. The photomemristor exhibits a high external quantum efficiency of over 85%, which leads to a low energy consumption of 0.6 nJ. The spike timing-dependent plasticity characteristics of the device are leveraged to construct a spiking neural network and achieve a 99.1% accuracy rate of directional perception for moving objects. The notable results offer a promising hardware solution for efficient optoneuromorphic and edge computing applications.
人工智能视觉系统的发展在很大程度上依赖于快速准确的光学成像检测、识别和跟踪技术的发展。受限于响应速度和低计算效率,传统的光电信息设备在实时光学成像任务以及高效处理复杂视觉数据的能力方面面临挑战。为解决当前光电信息设备的局限性,本研究引入了一种利用卤化物钙钛矿薄膜的新型光忆阻器。制造过程包括调整碘化物比例以提高卤化物钙钛矿薄膜的质量并最小化暗电流。该光忆阻器具有超过85%的高外部量子效率,从而导致低至0.6 nJ的能耗。利用该器件的脉冲时间依赖可塑性特性构建了一个脉冲神经网络,并实现了对移动物体99.1%的方向感知准确率。这些显著成果为高效的光神经形态和边缘计算应用提供了一个有前景的硬件解决方案。