Ferroelectrically-enhanced Schottky barrier transistors for Logic-in-Memory applications

肖特基势垒 晶体管 材料科学 计算机科学 光电子学 电气工程 工程类 电压 二极管
作者
Daniele Nazzari,Lukas Wind,Masiar Sistani,Dominik Mayr,Kihye Kim,W. Weber
出处
期刊:Cornell University - arXiv [Cornell University]
标识
DOI:10.48550/arxiv.2404.19535
摘要

Artificial neural networks (ANNs) have had an enormous impact on a multitude of sectors, from research to industry, generating an unprecedented demand for tailor-suited hardware platforms. Their training and execution is highly memory-intensive, clearly evidencing the limitations affecting the currently available hardware based on the von Neumann architecture, which requires frequent data shuttling due to the physical separation of logic and memory units. This does not only limit the achievable performances but also greatly increases the energy consumption, hindering the integration of ANNs into low-power platforms. New Logic in Memory (LiM) architectures, able to unify memory and logic functionalities into a single component, are highly promising for overcoming these limitations, by drastically reducing the need of data transfers. Recently, it has been shown that a very flexible platform for logic applications can be realized recurring to a multi-gated Schottky-Barrier Field Effect Transistor (SBFET). If equipped with memory capabilities, this architecture could represent an ideal building block for versatile LiM hardware. To reach this goal, here we investigate the integration of a ferroelectric Hf$_{0.5}$Zr$_{0.5}$O$_2$ (HZO) layer onto Dual Top Gated SBFETs. We demonstrate that HZO polarization charges can be successfully employed to tune the height of the two Schottky barriers, influencing the injection behavior, thus defining the transistor mode, switching it between n and p-type transport. The modulation strength is strongly dependent on the polarization pulse height, allowing for the selection of multiple current levels. All these achievable states can be well retained over time, thanks to the HZO stability. The presented result show how ferroelectric-enhanced SBFETs are promising for the realization of novel LiM hardware, enabling low-power circuits for ANNs execution.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
1秒前
1秒前
2秒前
伍姝慧发布了新的文献求助10
2秒前
医学生完成签到,获得积分10
2秒前
bkagyin应助还真不错采纳,获得10
3秒前
3秒前
树树发布了新的文献求助10
4秒前
lin01发布了新的文献求助20
6秒前
氘代乙腈是不贵的呀完成签到,获得积分10
6秒前
6秒前
yyy完成签到,获得积分20
6秒前
6秒前
lixinglei应助现代半莲采纳,获得20
7秒前
7秒前
Vi发布了新的文献求助10
8秒前
慕青应助yh采纳,获得30
8秒前
9秒前
9秒前
v0id应助大宝采纳,获得10
10秒前
Ma完成签到,获得积分10
10秒前
心随完成签到,获得积分10
10秒前
华仔应助天真的南露采纳,获得20
10秒前
12秒前
金金发布了新的文献求助10
13秒前
魏伯安发布了新的文献求助30
13秒前
小巧风华发布了新的文献求助10
13秒前
14秒前
树树完成签到,获得积分10
14秒前
汉堡包应助南忆采纳,获得10
15秒前
典雅君浩完成签到 ,获得积分10
17秒前
18秒前
老实善愁完成签到,获得积分10
19秒前
努力得分发布了新的文献求助10
19秒前
20秒前
Lucas应助整齐的慕卉采纳,获得10
20秒前
薖上发布了新的文献求助10
21秒前
Eating发布了新的文献求助10
21秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 2000
Advanced Weaponeering Fourth Edition, Volume 2 1000
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7553990
求助须知:如何正确求助?哪些是违规求助? 9136498
关于积分的说明 19527398
捐赠科研通 7145288
什么是DOI,文献DOI怎么找? 3260797
关于科研通互助平台的介绍 2427234
邀请新用户注册赠送积分活动 2249806