@inproceedings{aaa29ff6d7124d69a59204e18d75bed9,
title = "Ultra-Low Power Robust 3bit/cell Hf0.5Zr0.5O2 Ferroelectric FinFET with High Endurance for Advanced Computing-In-Memory Technology",
abstract = "Scaled ferroelectric FinFET devices were fabricated with post fin formation surface engineering (SE) to remove the line-edge roughness (LER) from the silicon surface by dry etching. This facilitated 3bit/cell operations in 10 nm Hf0.5Zr0.5O2 based ferroelectric FinFETs along with on-state current (ION) to off-state current (IOFF) ratio of 106, extrapolated 10-year retention and endurance above 1011 cycles. Further, we have evaluated its performance in all ferroelectric neural network, where ferroelectric FinFETs are used as synaptic devices or neurons for weight storage. Synaptic core built with optimized devices achieve software-comparable 97.91\% inference accuracy on MNIST data and multi-layer perceptron network.",
author = "Sourav De and Lu, \{Darsen D.\} and Le, \{Hoang Hiep\} and Soumen Mazumder and Lee, \{Yao Jen\} and Tseng, \{Wei Chih\} and Qiu, \{Bo Han\} and Baig, \{Md Aftab\} and Sung, \{Po Jung\} and Su, \{Chung Jun\} and Wu, \{Chien Ting\} and Wu, \{Wen Fa\} and Yeh, \{Wen Kuan\} and Wang, \{Yeong Her\}",
note = "Publisher Copyright: {\textcopyright} 2021 JSAP; 41st Symposium on VLSI Technology, VLSI Technology 2021 ; Conference date: 13-06-2021 Through 19-06-2021",
year = "2021",
language = "English",
series = "Digest of Technical Papers - Symposium on VLSI Technology",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 Symposium on VLSI Technology, VLSI Technology 2021",
address = "United States",
}