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解锁神经形态视觉:基于铟镓锌氧化物(IGZO)的具有可见光谱范围灵敏度的光电忆阻器的进展。

Unlocking Neuromorphic Vision: Advancements in IGZO-Based Optoelectronic Memristors with Visible Range Sensitivity.

作者信息

Pereira Maria Elias, Deuermeier Jonas, Martins Rodrigo, Barquinha Pedro, Kiazadeh Asal

机构信息

i3N/CENIMAT, Department of Materials Science, NOVA School of Science and Technology and CEMOP/UNINOVA, NOVA University Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal.

出版信息

ACS Appl Electron Mater. 2024 Jul 5;6(7):5230-5243. doi: 10.1021/acsaelm.4c00752. eCollection 2024 Jul 23.

Abstract

Optoelectronic memristors based on amorphous oxide semiconductors (AOSs) are promising devices for the development of spiking neural network (SNN) hardware in neuromorphic vision sensors. In such devices, the conductance state can be controlled by both optical and electrical stimuli, while the typical persistent photoconductivity (PPC) of AOS materials can be used to emulate synaptic functions. However, due to the large band gap of these materials, sensitivity to visible light (red/green/blue) is difficult to accomplish, which hinders applications requiring color discrimination. In this work, we report a 4 μm hydrogen-doped (H-doped) indium-gallium-zinc oxide (IGZO) optoelectronic memristor that emulates all of the important rules of SNNs such as short- to long-term memory transition (STM-LTM), paired-pulse facilitation (PPF), spike-time-dependent plasticity (STDP), and learning and forgetting capabilities. By the incorporation of hydrogen gas in the sputtering deposition of IGZO, visible sensitivity was achieved for green and blue wavelengths. Additionally, extremely high light/dark ratios of 179, 93, and 12 are demonstrated for wavelengths of 365, 405, and 505 nm, respectively, due to hydrogen-induced subgap states and device miniaturization. Therefore, the proposed device shows remarkable potential for integration with the pixel circuits of IGZO-based displays with extreme resolution for a true intelligent self-processing display.

摘要

基于非晶氧化物半导体(AOS)的光电忆阻器是用于神经形态视觉传感器中尖峰神经网络(SNN)硬件开发的有前途的器件。在这类器件中,电导状态可通过光和电刺激来控制,同时AOS材料典型的持久光电导性(PPC)可用于模拟突触功能。然而,由于这些材料的带隙较大,难以实现对可见光(红/绿/蓝)的敏感性,这阻碍了需要颜色辨别的应用。在这项工作中,我们报道了一种4μm氢掺杂(H掺杂)铟镓锌氧化物(IGZO)光电忆阻器,它模拟了SNN的所有重要规则,如短期到长期记忆转变(STM-LTM)、双脉冲易化(PPF)、脉冲时间依赖可塑性(STDP)以及学习和遗忘能力。通过在IGZO的溅射沉积中引入氢气,实现了对绿色和蓝色波长的可见光敏感性。此外,由于氢诱导的亚带隙态和器件小型化,对于365、405和505nm波长分别展示出了高达179、93和12的极高亮/暗比。因此,所提出的器件在与具有极高分辨率的基于IGZO的显示器的像素电路集成以实现真正的智能自处理显示器方面显示出显著的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6552/11270833/a27290390024/el4c00752_0001.jpg

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