Research of data retention for charge trapping memory by first-principles

俘获 空位缺陷 材料科学 兴奋剂 杂质 电荷(物理) 从头算 凝聚态物理 电介质 原子物理学 光电子学 物理 量子力学 生态学 生物
作者
Xianwei Jiang,Shibin Lu,Dai Guang-Zhen,Jiayu Wang,Bo Jin,Chen Jun-ning
出处
期刊:Chinese Physics [Science Press]
卷期号:64 (21): 213102-213102 被引量:1
标识
DOI:10.7498/aps.64.213102
摘要

In this paper, the influence of charge trapping memory storage feature is studied by doping the substitutional impurity Al and introducing oxygen vacancy within HfO2. HfO2 is widely used in trapping layer of charge trapping memory, for it belongs to high dielectric constant materials with the abilities to shrink the device size and improve the device performance. Materials studio and Vienna Ab-initio Simulation Package are used to investigate the influence of doping Al on the formation of the oxygen vacancy in HfO2 as a trapping layer. At the same time, the interaction energy of two defects at different distances is calculated. Results show that doping the substitutional impurity Al reduces the formation energy of oxygen vacancies in HfO2, and the reduced formation energy of the three-fold-coordinated O vacancy is larger than that of the four-fold-coordinated O vacancy. After having studied three different defect distances between the substitutional impurity Al and the three-fold-coordinated O vacancy, the results indicate that the system acquires the largest charge trapping energy, the most of quantum states, the smallest population number, and the longest Al–O bond length when the distance between the defects is 2.107 Å. Studying the bond length changes of the three systems after writing a hole, we obtain a result that the change of Al–O bond length is the smallest when the distance between defects is 2.107 Å. In conclusion, the data retention in the trapping layer of monoclinic HfO2 can be improved by doping the substitutional impurity Al. This work will provide a theoretical guidance for the performance improvement in the data retention of charge trapping memory.

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
SophieLiu发布了新的文献求助10
1秒前
灵巧幻露完成签到,获得积分10
1秒前
婉婉完成签到,获得积分10
2秒前
Eternal完成签到,获得积分10
2秒前
3秒前
pigpromax发布了新的文献求助10
3秒前
尊敬依珊完成签到 ,获得积分10
3秒前
桐桐应助锦葵科的棉花采纳,获得10
3秒前
raiychemj完成签到,获得积分10
3秒前
林天完成签到,获得积分10
4秒前
chenjie完成签到,获得积分10
4秒前
4秒前
害怕的忆梅完成签到,获得积分10
5秒前
wjh完成签到,获得积分10
5秒前
leishenwang完成签到,获得积分10
6秒前
daiyue完成签到 ,获得积分10
6秒前
6秒前
小马过河完成签到,获得积分10
6秒前
在水一方应助chenhui采纳,获得10
6秒前
6秒前
7秒前
清清完成签到,获得积分10
7秒前
7秒前
SophiaS完成签到,获得积分10
7秒前
hlb发布了新的文献求助10
8秒前
NDKND完成签到,获得积分10
8秒前
8秒前
Twonej应助kingripple采纳,获得10
8秒前
满意血茗完成签到,获得积分10
8秒前
只想休息完成签到,获得积分10
9秒前
丘比特应助研友_nqylan采纳,获得10
9秒前
10秒前
合适的铃铛完成签到,获得积分10
10秒前
linlin发布了新的文献求助10
10秒前
puppynorio完成签到,获得积分10
10秒前
FashionBoy应助lzy采纳,获得10
10秒前
云为晓完成签到,获得积分10
11秒前
LQ完成签到,获得积分10
11秒前
kaele完成签到,获得积分10
11秒前
yy完成签到,获得积分10
12秒前
高分求助中
Clinical Epidemiology: The Essentials, 6e 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
The Graphene Handbook (2019 Edition) 800
Adhesion Science: Principles & Practice 800
Signals, Systems, and Signal Processing 610
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 600
久松真一著作集〈第5巻〉禅と芸術 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 6555791
求助须知:如何正确求助?哪些是违规求助? 8340026
关于积分的说明 17867426
捐赠科研通 5673712
什么是DOI,文献DOI怎么找? 2940398
邀请新用户注册赠送积分活动 1916238
关于科研通互助平台的介绍 1786623