Negative Capacitance Gate Stack and Landau FET-based Voltage Amplifiers and Circuits: Impact of Ferroelectric Thickness and Domain Variations
MICROELECTRONICS JOURNAL(2023)
Abstract
This article analyzes the impact of ferroelectric hafnium zirconium oxide (HZO) thickness (tFE) and domain number (N) variations on the negative capacitance (NC) effect in metal/HZO/metal gate stack and its implications on Landau FET-based device-circuit co-design through simulations. As tFE decreases, the NC effect weakens, resulting in less S-shaped hysteresis loops for charge and polarization versus voltage characteristics. The study highlights the trade-off between energy dissipation and NC effect voltage window in ferroelectric devices and the importance of balancing both. We developed Landau FET-based voltage amplifiers (VA), including passive VA (PVA) and active VA (AVA), and compared to existing counterparts such as P(VDF-TrFE)-PVA and PZT-AVA, across low and high frequencies. The proposed PVA shows a 22.60% and 54.31% increase in amplification (ANC) at low and high frequencies, respectively, compared to P(VDF-TrFE)-PVA. The AVA exhibits a 17.86% increase in ANC at low frequencies compared to PZT-AVA but no ANC at higher frequencies due to symmetry-breaking. The Landau FET-based inverter shows a sharp state transition than the CMOS inverter, but this sharpness depends on tFE, N, and the degree of NC effect. The Landau FET-based fan-out-4 inverter with 7.7 nm tFE and N = 16 is 25.49% faster than the Si MOSFET inverter. Moreover, the impact of tFE and N on the performance of the proposed 5-stage ring oscillator (RO) is investigated concerning state-of-the-art CMOS RO counterparts. The 5-stage RO using Landau FET-based inverters showed (1.26–18.9) times higher oscillation frequency (fOSC) and (17.93–5.71) times reduced power dissipation compared to the existing CMOS ROs. Finally, we examined how process variations impact the fOSC in the proposed 5-stage Landau FET-based RO. The findings indicate a standard deviation of 0.39 GHz in the distribution of fOSC. These findings highlight the interplay between tFE scaling, N variations, and transient NC effect, advancing Landau FET-based devices for future NC electronics.
MoreTranslated text
Key words
Ferroelectric,Hysteresis,Inverter,Landau FET,Negative capacitance effect,Ring oscillator,Voltage amplifier
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper