Leaky 2T Dynamic Random-Access Memory Devices Based on Nanometer-Thick Indium–Gallium−Zinc-Oxide Films for Reservoir Computing

IF 5.3 2区 材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY ACS Applied Nano Materials Pub Date : 2024-10-01 DOI:10.1021/acsanm.4c0450110.1021/acsanm.4c04501
Junwon Jang, Seongmin Kim, Suyong Park, Soomin Kim, Sungjun Kim* and Seongjae Cho*, 
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Abstract

This paper explores the integration of indium–gallium–zinc oxide (IGZO)-based 2-transistor 0-capacitor dynamic random-access memory (2T0C DRAM, or shortly, 2T DRAM) into reservoir computing for advanced semiconductor artificial intelligence (AI) applications. The short-term memory characteristics of IGZO 2T DRAM enable rapid read–write speeds essential for processing time-varying input data. Experimental results confirm high on/off ratios and leaky retention behaviors. The study also examines paired-pulse facilitation (PPF) phenomena, offering insights into reinforcement mechanisms for cognitive computing. Finally, the reservoir computing approach achieves notable pattern recognition accuracy with a 4-bit pulse scheme, showcasing its effectiveness in complex data sets.

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基于纳米厚氧化铟镓锌薄膜的漏电 2T 动态随机存取存储器件,用于存储计算
本文探讨了如何将基于铟镓锌氧化物(IGZO)的双晶体管 0 电容动态随机存取存储器(2T0C DRAM,简称 2T DRAM)集成到先进半导体人工智能(AI)应用的水库计算中。IGZO 2T DRAM 的短期存储器特性可实现快速读写速度,这对处理随时间变化的输入数据至关重要。实验结果证实了高导通/关断比和漏电保持行为。研究还考察了成对脉冲促进(PPF)现象,为认知计算的强化机制提供了启示。最后,水库计算方法通过 4 位脉冲方案实现了显著的模式识别精度,展示了其在复杂数据集中的有效性。
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来源期刊
CiteScore
8.30
自引率
3.40%
发文量
1601
期刊介绍: ACS Applied Nano Materials is an interdisciplinary journal publishing original research covering all aspects of engineering, chemistry, physics and biology relevant to applications of nanomaterials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important applications of nanomaterials.
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