用于神经形态计算的超低功耗 IGZO 光电突触晶体管

IF 7.3 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Li Zhu, Sixian Li, Junchen Lin, Yuanfeng Zhao, Xiang Wan, Huabin Sun, Shancheng Yan, Yong Xu, Zhihao Yu, Chee Leong Tan, Gang He
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引用次数: 0

摘要

受生物视觉系统的启发,具有图像感知、记忆保持和预处理能力的光电突触为开发高性能人工感知视觉计算系统提供了一条大有可为的途径。其中,基于氧化物的光电突触晶体管以其持久的光电导特性和易于集成而著称,在这方面具有巨大的潜力。在这项研究中,我们利用铟镓锌氧化物作为半导体层,高k ZrAlOx 作为栅极电介质层,设计出了具有光子记忆功能的低功耗高性能突触晶体管。关键的生物突触功能,包括兴奋性突触后电流、成对脉冲促进以及从短期可塑性到长期可塑性的过渡,都通过光脉冲调制得以复制。即使在工作电压低至 0.0001 V 的情况下,这种模拟仍能持续,并表现出明显的光子突触反应,每次突触事件的能量消耗低至 0.0845 fJ。此外,还利用光电突触装置模拟了与人脑类似的 "学习-遗忘-再学习 "行为以及莫尔斯电码编码。最后,还构建了一个 3 × 3 设备阵列,以展示其在图像识别和存储方面的优势。这项研究为开发易于集成的超低功耗光电突触提供了有效策略,在形态视觉系统、仿生机器人和人工智能领域具有巨大潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ultra-low power IGZO optoelectronic synaptic transistors for neuromorphic computing

Inspired by biological visual systems, optoelectronic synapses with image perception, memory retention, and preprocessing capabilities offer a promising pathway for developing high-performance artificial perceptual vision computing systems. Among these, oxide-based optoelectronic synaptic transistors are well-known for their enduring photoconductive properties and ease of integration, which hold substantial potential in this regard. In this study, we utilized indium gallium zinc oxide as a semiconductor layer and high-k ZrAlOx as a gate dielectric layer to engineer low-power high-performance synaptic transistors with photonic memory. Crucial biological synaptic functions, including excitatory postsynaptic currents, paired-pulse facilitation, and the transition from short-term to long-term plasticity, were replicated via optical pulse modulation. This simulation was sustained even at an operating voltage as low as 0.0001 V, exhibiting a conspicuous photonic synaptic response with energy consumption as low as 0.0845 fJ per synaptic event. Furthermore, an optoelectronic synaptic device was employed to model “learn-forget-relearn” behavior similar to that exhibited by the human brain, as well as Morse code encoding. Finally, a 3 × 3 device array was constructed to demonstrate its advantages in image recognition and storage. This study provides an effective strategy for developing readily integrable, ultralow-power optoelectronic synapses with substantial potential in the domains of morphological visual systems, biomimetic robotics, and artificial intelligence.

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来源期刊
Science China Information Sciences
Science China Information Sciences COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
12.60
自引率
5.70%
发文量
224
审稿时长
8.3 months
期刊介绍: Science China Information Sciences is a dedicated journal that showcases high-quality, original research across various domains of information sciences. It encompasses Computer Science & Technologies, Control Science & Engineering, Information & Communication Engineering, Microelectronics & Solid-State Electronics, and Quantum Information, providing a platform for the dissemination of significant contributions in these fields.
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