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초록
This work demonstrates a physical reservoir using a back-end-of-line compatible thin-film transistor (TFT) with tin monoxide (SnO) as the channel material for neuromorphic computing. The electron trapping and time-dependent detrapping at the channel interface induce the SnO<middle dot>TFT to exhibit fading memory and nonlinearity characteristics, the critical assets for physical reservoir computing. The three-terminal configuration of the TFT allows the generation of higher-dimensional reservoir states by simultaneously adjusting the bias conditions of the gate and drain terminals, surpassing the performances of typical two-terminal-based reservoirs such as memristors. The high-dimensional SnO TFT reservoir performs exceptionally in two benchmark tests, achieving a 94.1% accuracy in Modified National Institute of Standards and Technology handwritten number recognition and a normalized root-mean-square error of 0.089 in Mackey-Glass time-series prediction. Furthermore, it is suitable for vertical integration because its fabrication temperature is <250 degrees C, providing the benefit of achieving a high integration density.
키워드
- 제목
- High-Dimensional Physical Reservoir with Back-End-of-Line-Compatible Tin Monoxide Thin-Film Transistor
- 저자
- Mun, Sahngik A.; Jang, Yoon Ho; Han, Janguk; Shim, Sung Keun; Kang, Sukin; Lee, Yonghee; Choi, Jinheon; Cheong, Sunwoo; Lee, Soo Hyung; Ryoo, Seung Kyu; Han, Joon-Kyu; Hwang, Cheol Seong
- 발행일
- 2024-08
- 유형
- Article
- 권
- 16
- 호
- 32
- 페이지
- 42884 ~ 42893