Xie Pengshan, Xu Yunchao, Wang Jingwen, Li Dengji, Zhang Yuxuan, Zeng Zixin, Gao Boxiang, Quan Quan, Li Bowen, Meng You, Wang Weijun, Li Yezhan, Yan Yan, Shen Yi, Sun Jia, Ho Johnny C
Department of Materials Science and Engineering, City University of Hong Kong, Hong Kong, China.
Hunan Key Laboratory for Super-microstructure and Ultrafast Process, School of Physics, Central South University, Changsha, Hunan, China.
Nat Commun. 2024 Sep 27;15(1):8298. doi: 10.1038/s41467-024-52563-4.
Wearable visual bionic devices, fueled by advancements in artificial intelligence, are making remarkable progress. However, traditional silicon vision chips often grapple with high energy losses and challenges in emulating complex biological behaviors. In this study, we constructed a van der Waals P3HT/GaAs nanowires P-N junction by carefully directing the arrangement of organic molecules. Combined with a Schottky junction, this facilitated multi-faceted birdlike visual enhancement, including broadband non-volatile storage, low-light perception, and a near-zero power consumption operating mode in both individual devices and 5 × 5 arrays on arbitrary substrates. Specifically, we realized over 5 bits of in-memory sensing and computing with both negative and positive photoconductivity. When paired with two imaging modes (visible and UV), our reservoir computing system demonstrated up to 94% accuracy for color recognition. It achieved motion and UV grayscale information extraction (displayed with sunscreen), leading to fusion visual imaging. This work provides a promising co-design of material and device for a broadband and highly biomimetic optoelectronic neuromorphic system.
在人工智能进步的推动下,可穿戴视觉仿生设备正在取得显著进展。然而,传统的硅视觉芯片在模拟复杂生物行为时常常面临高能量损耗和挑战。在本研究中,我们通过精心引导有机分子的排列构建了范德华力作用下的聚3-己基噻吩/砷化镓纳米线P-N结。结合肖特基结,这实现了多方面的类鸟视觉增强,包括宽带非易失性存储、低光感知以及在单个器件和任意衬底上的5×5阵列中的近零功耗工作模式。具体而言,我们利用正负光电导率实现了超过5位的内存中传感和计算。当与两种成像模式(可见光和紫外线)配对时,我们的储层计算系统在颜色识别方面展现出高达94%的准确率。它实现了运动和紫外线灰度信息提取(用防晒霜显示),从而实现融合视觉成像。这项工作为宽带和高度仿生的光电神经形态系统提供了一种有前景的材料与器件协同设计方案。