Demonstration of 64 Conductance States and Large Dynamic Range in Si-doped HfO2 FeFETs under Neuromorphic Computing Operations

Yu Yun Wang, Kuang-Chi Wang, Cheng Hung Wu, Ting Yu Chang, Nicolo Ronchi, Kaustuv Banerjee, Geert Van den Bosch, Jan Van Houdt, Tian-Li Wu

研究成果: Paper同行評審

摘要

Doped HfO2 Ferroelectric Field-Effect Transistors (FeFETs), which enable a low power operation, multilevel states tunability, and CMOS process compatibility , are promising candidates for neuro-inspired computing [1]. Currently, the 32 levels of conductance states under the neuromorphic computing in Zr-doped FeFETs and MOSCAPs have been successfully demonstrated [2]. In this work, Si-doped HfO2 FeFETs are fabricated and characterized, showing a promising neuromorphic functionalities with up to 64-states and large dynamic range Furthermore, two different pulsing schemes are used for extracting the device-level neuromorphic functionalities, suggesting that the programming pulses significantly influence the neuromorphic performance of the device.
原文English
頁數2
DOIs
出版狀態Published - 4月 2022
事件2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022 - Hsinchu, Taiwan
持續時間: 18 4月 202221 4月 2022

Conference

Conference2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022
國家/地區Taiwan
城市Hsinchu
期間18/04/2221/04/22

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