Dai Qinyong, Pei Mengjiao, Guo Jianhang, Hao Ziqian, Li Yating, Lu Kuakua, Chen Xu, Ai Chao, Wang Qijing, Shi Yi, Li Yun
National Laboratory of Solid-State Microstructures, School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, P. R. China.
J Phys Chem Lett. 2024 Dec 12;15(49):12068-12075. doi: 10.1021/acs.jpclett.4c03217. Epub 2024 Nov 26.
The rapid advancement of artificial intelligence has driven the demand for hardware solutions of neuromorphic pathways to effectively mimic biological functions of the human visual system. However, current machine vision systems (MVSs) fail to fully replicate retinal functions and lack the ability to update weights through all-optical pulses. Here, by employing rational interface charge engineering via varying the charge trapping layer thickness of PMMA, we determine that the ferroelectric polarization of our ferroelectric neuristors can be flexibly manipulated through light or electrical pulses. This capability enables dynamic modulation of the device's optoelectronic characteristics, facilitating a complete MVS. As front-end sensors, devices with the thickest PMMA (∼32 nm) demonstrate autonomous light adaptation while those with the thinnest PMMA (∼2 nm) exhibit bidirectional photoresponse characteristics akin to those of bipolar cells. Furthermore, as components of a back-end processor, the conductances of these devices with a moderate thickness (∼12 nm) can be updated linearly through all-optical pulses. Our MVS, constructed with these neuristors, achieved an impressive recognition accuracy of 93% in handwritten digit recognition tasks under extreme lighting conditions. This work offers an effective strategy for the development of energy-efficient and highly integrated intelligent MVSs.
人工智能的快速发展推动了对神经形态通路硬件解决方案的需求，以有效模拟人类视觉系统的生物学功能。然而，当前的机器视觉系统（MVS）未能完全复制视网膜功能，并且缺乏通过全光脉冲更新权重的能力。在此，通过改变聚甲基丙烯酸甲酯（PMMA）电荷俘获层的厚度进行合理的界面电荷工程，我们确定了铁电神经晶体管的铁电极化可以通过光脉冲或电脉冲灵活操控。这种能力使得器件的光电特性能够动态调制，从而推动了完整MVS的实现。作为前端传感器，具有最厚PMMA（约32纳米）的器件表现出自主光适应能力，而具有最薄PMMA（约2纳米）的器件则展现出类似于双极细胞的双向光响应特性。此外，作为后端处理器的组件，这些具有中等厚度（约12纳米）的器件的电导可以通过全光脉冲进行线性更新。我们用这些神经晶体管构建的MVS在极端光照条件下的手写数字识别任务中实现了93%的惊人识别准确率。这项工作为开发节能且高度集成的智能MVS提供了一种有效策略。
