Direct-Write NiO RRAM Cells

电阻随机存取存储器 非阻塞I/O 计算机科学 光电子学 材料科学 电气工程 化学 工程类 生物化学 电压 催化作用
作者
Jordan P. Howard-Jennings,Riadh Al-Haidari,Emuobosan Enakerakpo,Abdullah Obeidat,Kevin Bell,Tom Rovere,Stephen Gonya,Mohammed Alhendi,Mark D. Poliks
标识
DOI:10.1109/ectc51529.2024.00114
摘要

As electronic devices and their internal components have become more advanced, conventional computer memory technologies – which are a key component of all electronics – have struggled to fully keep up with this advancement. Meeting the demands of computer memory in modern electronics requires a zero-sum game approach of optimizing several, often competing performance benchmark criteria. Resistive random-access memory (RRAM) is an emerging nonvolatile memory (NVM) technology with great appeal due to its ease of fabrication, low programming voltage, fast read/write times, compatibility with existing CMOS platforms, and demonstrated scalability into tiny dimensions thus enabling a higher density and smaller footprint. We fabricated NiO-based RRAM cells using aerosol jet printing to investigate the performance of direct-writing as an alternative method for RRAM cell fabrication compared to conventional techniques (e.g. sputtering, layer deposition, etc.). A fabricated NiO-based RRAM cell, with a NiO layer thickness of 0.426 μm and a cell area of 0.154 mm 2 , demonstrated a clearly separated high and low resistance state when a dual voltage sweep was applied across the two cell electrode terminals. Preliminary results show that NiO-RRAM aerosol jet printed cells can exhibit resistive switching, indicating that direct write methods can be used to fabricate many cells per batch with material layer thicknesses that, while thicker than what can be achieved using conventional techniques, are just as functional.

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
Kyle发布了新的文献求助10
1秒前
1秒前
兰先生完成签到,获得积分10
2秒前
miksa发布了新的文献求助10
3秒前
Lynn完成签到 ,获得积分10
3秒前
素简完成签到,获得积分10
3秒前
Guo应助科研通管家采纳,获得10
3秒前
乐乐应助科研通管家采纳,获得10
3秒前
上官若男应助科研通管家采纳,获得10
3秒前
凛睦完成签到,获得积分10
3秒前
隐形曼青应助科研通管家采纳,获得10
3秒前
3秒前
清秀凡霜完成签到,获得积分0
4秒前
4秒前
SGQT完成签到,获得积分10
5秒前
活力的映易完成签到,获得积分10
5秒前
Daisy完成签到,获得积分10
6秒前
allton发布了新的文献求助10
7秒前
酷波er应助kamenashi采纳,获得10
7秒前
默默尔安完成签到 ,获得积分10
7秒前
鲤鱼青雪完成签到,获得积分10
8秒前
炙热的冰萍完成签到,获得积分10
8秒前
深情安青应助PMME采纳,获得10
8秒前
lshao完成签到 ,获得积分10
10秒前
innyjiang完成签到,获得积分10
10秒前
Andy完成签到 ,获得积分10
10秒前
Alfred完成签到,获得积分10
11秒前
yolo完成签到,获得积分10
11秒前
dyd完成签到,获得积分10
12秒前
cxlhzq完成签到,获得积分10
12秒前
i羽翼深蓝i完成签到,获得积分10
12秒前
暮夕梧桐完成签到,获得积分10
12秒前
12秒前
再学一分钟完成签到,获得积分10
13秒前
芋头读文献完成签到,获得积分10
14秒前
LIN2QI完成签到,获得积分10
14秒前
嬴政飞完成签到,获得积分10
16秒前
冯梦梦完成签到,获得积分10
16秒前
新野完成签到,获得积分10
17秒前
yongtao完成签到,获得积分10
17秒前
高分求助中
(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
Introduction to Helicopter and Tiltrotor Flight Simulation, Second Edition 2500
卤化钙钛矿人工突触的研究 2000
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Software that combines deep learning,3D reconstruction and CFD to analyze the state of carotid arteries from ultrasound imaging 600
Bounds for Statistical Estimation in Semiparametric Models 500
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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6498212
求助须知:如何正确求助?哪些是违规求助? 8294177
关于积分的说明 17697032
捐赠科研通 5594166
什么是DOI,文献DOI怎么找? 2917600
邀请新用户注册赠送积分活动 1894551
关于科研通互助平台的介绍 1755161