Leaky 2T Dynamic Random-Access Memory Devices Based on Nanometer-Thick Indium–Gallium−Zinc-Oxide Films for Reservoir Computing
Junwon Jang, Seong‐Min Kim, Seong‐Min Kim, Suyong Park, Soo-Min Kim, Soo-Min Kim, Sungjun Kim, Sungjun Kim, Seongjae Cho · ACS Applied Nano Materials · 2024
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.