Characterization of elastomer degradation in O2/Ar plasma via mass and surface morphology changes

降级(电信) 弹性体 激进的 材料科学 朗缪尔探针 离子 等离子体 分析化学(期刊) 复合材料 表面粗糙度 等离子体处理 化学 等离子体诊断 色谱法 有机化学 计算机科学 物理 电信 量子力学
作者
Nicholas Connolly,Michael Hysick,D. Eitan Barlaz,R.G. Garza,Gilberto Lunardi,D. N. Ruzic
出处
期刊:Journal of vacuum science & technology [American Vacuum Society]
卷期号:42 (2)
标识
DOI:10.1116/6.0003240
摘要

The degradation of fluoroelastomer, perfluoroelastomer (FFKM), and fluorosilicone materials were compared between three O2/Ar plasma conditions: full plasma (ions plus radicals), radical only, and ion only. These elastomer materials are used extensively in plasma processing equipment used to manufacture semiconductors, and understanding the plasma environments that enhance degradation will inform material choice and further material development. Langmuir probe measurements were made to quantify the electron temperature and plasma density; radical probe measurements were made to quantify the oxygen radical density. The results suggested that plasma radicals were required to drive significant mass loss rates, with ions speeding up the mass loss rate further in the full plasma case. Additionally, it was determined that plasma radicals were the main driver of surface changes of the elastomer, with similar surface roughening in plasma versus radical only conditions and less significant roughening in ion-only conditions. The O2/Ar plasma discharge had an electron temperature of 4.6 ± 0.1 eV and a plasma density of 2.9 ± 0.07 × 1016 m−3. It was observed that the fluorosilicone material had the lowest mass loss rate, the unfilled FFKM had the highest mass loss rate, and the silica-filled FFKM had the lowest mass loss rate among the FFKMs tested. The presence of oxygen radicals during exposure conditions significantly changed surface roughness.
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
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
Prudence应助liuyuan采纳,获得10
1秒前
1秒前
李健应助一树采纳,获得10
2秒前
安静的翼发布了新的文献求助10
3秒前
天人旧馆发布了新的文献求助10
3秒前
3秒前
善学以致用应助苹果亦巧采纳,获得50
5秒前
今后应助山风兰采纳,获得10
5秒前
闾丘明雪发布了新的文献求助10
5秒前
5秒前
xwm完成签到,获得积分10
6秒前
师无完成签到,获得积分10
6秒前
Akim应助Chow采纳,获得10
6秒前
大个应助tejing1158采纳,获得10
8秒前
二东发布了新的文献求助10
8秒前
哇咔啦啦完成签到,获得积分10
9秒前
世间多长发布了新的文献求助10
9秒前
9秒前
文洵发布了新的文献求助10
10秒前
10秒前
研友_LX7Qg8发布了新的文献求助10
11秒前
共享精神应助妥妥酱采纳,获得10
11秒前
修辛发布了新的文献求助10
11秒前
科研通AI6.2应助代代代代采纳,获得10
12秒前
小二郎应助小猫牛角包采纳,获得10
12秒前
无极微光应助clyhg采纳,获得20
12秒前
科研通AI6.2应助灿guo采纳,获得10
12秒前
大模型应助哇咔啦啦采纳,获得10
13秒前
13秒前
13秒前
优秀不愁发布了新的文献求助10
14秒前
15秒前
曹静完成签到,获得积分10
18秒前
优秀不愁发布了新的文献求助10
18秒前
欣慰的小甜瓜完成签到 ,获得积分10
20秒前
softial发布了新的文献求助10
22秒前
22秒前
24秒前
哆哆发布了新的文献求助10
24秒前
卤鸭完成签到,获得积分10
25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
Kinesiophobia : a new view of chronic pain behavior 2000
Research for Social Workers 1000
Mastering New Drug Applications: A Step-by-Step Guide (Mastering the FDA Approval Process Book 1) 800
The Social Psychology of Citizenship 600
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5912306
求助须知:如何正确求助?哪些是违规求助? 6832201
关于积分的说明 15785522
捐赠科研通 5037355
什么是DOI,文献DOI怎么找? 2711658
邀请新用户注册赠送积分活动 1662012
关于科研通互助平台的介绍 1603930