亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Selective molecular gas phase etching in layered high aspect-ratio nanostructures for semiconductor processing. I. Modeling framework and simulation

材料科学 纳米结构 蚀刻(微加工) 半导体 纳米技术 气相 半导体纳米结构 光电子学 化学 物理化学 图层(电子)
作者
Zach Zajo,David S. L. Mui,Ji Zhu,Mark Kawaguchi,Eric S. G. Shaqfeh
出处
期刊:Journal of vacuum science & technology [American Vacuum Society]
卷期号:43 (1) 被引量:2
标识
DOI:10.1116/6.0004155
摘要

The need for precise control of nanoscale geometric features poses a challenge in manufacturing advanced gate-all-around nanotransistors. The high material selectivity required in fabricating these transistors makes thermal gas etching much more appealing in comparison to liquid phase and plasma-based etching techniques. The selective thermal etching by F2 of silicon–germanium (SiGe) stacks comprised of alternating layers of silicon (Si) and SiGe is explored in this context for semiconductor manufacturing applications. We propose and develop computer simulations as a tool to predict the etch profile evolution over time in such an etching process. The tool is based on a mathematical model that considers the transport processes and surface interactions involved in the gas phase etching process—which at the nanoscale is primarily Knudsen diffusion in the free molecular flow regime. Thus, the transport model is formulated as a boundary integral equation, which takes into account the direct flux of etchant molecules that any given point on the exposed surface receives from the bulk gas phase as well as the re-emission flux from other parts of the structure itself. We compared the applicability of two different surface reaction models—a model where the local etch rate is linear in the flux at a point and a Langmuir adsorption/reaction model—to connect the net flux received at a point on the surface to the local etch rate. This paper precedes Paper II of this series, which describes the experimental methods and comparison with model predictions of F2 etching in high aspect ratio Si–SiGe stacked nanostructures.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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。
建议保存本图,每天支付宝扫一扫(相册选取)领红包
实时播报
caoju完成签到,获得积分10
3秒前
Jasper应助AA采纳,获得10
4秒前
9秒前
华仔应助一两二两三两斤采纳,获得10
11秒前
SciGPT应助王大壮采纳,获得10
14秒前
小白果果发布了新的文献求助10
15秒前
九星完成签到 ,获得积分10
22秒前
AX完成签到,获得积分10
38秒前
小鸟芋圆露露完成签到 ,获得积分10
42秒前
49秒前
55秒前
NexusExplorer应助科研通管家采纳,获得10
55秒前
浮游应助科研通管家采纳,获得10
56秒前
浮游应助科研通管家采纳,获得10
56秒前
ceeray23应助科研通管家采纳,获得10
56秒前
ceeray23应助科研通管家采纳,获得10
56秒前
浮游应助科研通管家采纳,获得10
56秒前
浮游应助科研通管家采纳,获得10
56秒前
bkagyin应助科研通管家采纳,获得10
56秒前
56秒前
56秒前
59秒前
1分钟前
FashionBoy应助机灵的幼菱采纳,获得10
1分钟前
1分钟前
西安浴日光能赵炜完成签到,获得积分10
1分钟前
霸气剑通发布了新的文献求助10
1分钟前
大胆发布了新的文献求助10
1分钟前
爆米花应助霸气剑通采纳,获得10
1分钟前
decade发布了新的文献求助10
1分钟前
科研通AI6应助瀅瀅采纳,获得10
1分钟前
obito完成签到,获得积分10
1分钟前
1分钟前
1分钟前
1分钟前
4114发布了新的文献求助10
1分钟前
Nomb1发布了新的文献求助10
1分钟前
Rich_WH发布了新的文献求助10
1分钟前
1分钟前
怡然剑成完成签到 ,获得积分10
1分钟前
高分求助中
Learning and Memory: A Comprehensive Reference 2000
Predation in the Hymenoptera: An Evolutionary Perspective 1800
List of 1,091 Public Pension Profiles by Region 1541
The Jasper Project 800
Holistic Discourse Analysis 600
Beyond the sentence: discourse and sentential form / edited by Jessica R. Wirth 600
Binary Alloy Phase Diagrams, 2nd Edition 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5502750
求助须知:如何正确求助?哪些是违规求助? 4598475
关于积分的说明 14464193
捐赠科研通 4532042
什么是DOI,文献DOI怎么找? 2483808
邀请新用户注册赠送积分活动 1467025
关于科研通互助平台的介绍 1439644