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

  • Jang, Junwon; 
  • Kim, Seongmin; 
  • Park, Suyong; 
  • Kim, Soomin; 
  • Kim, Sungjun; 
  • 외 1명
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초록

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. [GRAPHICS]

키워드

neuromorphic system; reservoir computing; capacitorlessdynamic random-access memory; two-transistor DRAM; artificial synaptic array; In-Ga-Zn-O
제목
Leaky 2T Dynamic Random-Access Memory Devices Based on Nanometer-Thick Indium-Gallium-Zinc-Oxide Films for Reservoir Computing
저자
Jang, Junwon; Kim, Seongmin; Park, Suyong; Kim, Soomin; Kim, Sungjun; Cho, Seongjae
DOI
10.1021/acsanm.4c04501
발행일
2024-10
유형
Article
저널명
ACS Applied Nano Materials
권
7
호
19
페이지
22430 ~ 22435