Unraveling the nature of sensing in electrostatic MEMS gas sensors

响应度 微电子机械系统 流离失所(心理学) 材料科学 介电常数 电场 光电子学 电介质 光电探测器 物理 心理学 量子力学 心理治疗师
作者
Yasser S. Shama,Sasan Rahmanian,Hamza Mouharrar,Rana Abdelrahman,Alaaeldin Elhady,Eihab Abdel‐Rahman
出处
期刊:Microsystems & Nanoengineering [Springer Nature]
卷期号:10 (1) 被引量:1
标识
DOI:10.1038/s41378-024-00688-3
摘要

Abstract This paper investigates the fundamental sensing mechanism of electrostatic MEMS gas sensors. It compares among the responsivities of a set of MEMS isopropanol sensors before and after functionalization, and in the presence and absence of electrostatic fields when operated in static and dynamic detection modes. In the static mode, we found that the sensors do not exhibit a measurable change in displacement due to added mass. On the other hand, bare sensors showed a clear change in displacement in response to isopropanol vapor. In the dynamic mode, functionalized sensors showed a measurable frequency shift due to the added mass of isopropanol vapor. In the presence of strong electrostatic fields, the measured frequency shift was found to be threefold larger than that in their absence in response to the same concentration of isopropanol vapor. The enhanced responsivity of dynamic detection allows the sensors to measure the vapor mass captured by the functional material, which is not the case for static detection. The detection of isopropanol by bare sensors in static mode shows that change in the medium permittivity is the primary sensing mechanism. The enhanced responsivity of dynamic mode sensors when operated in strong electrostatic fields shows that their sensing mechanism is a combination of a weaker added mass effect and a stronger permittivity effect. These findings show that electrostatic MEMS gas sensors are independent of the direction of the gravitational field and are, thus, robust to changes in alignment. It is erroneous to refer to them as ‘gravimetric’ sensors.
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
圈圈发布了新的文献求助10
刚刚
顾矜应助无聊先知采纳,获得10
刚刚
刚刚
刚刚
1秒前
1秒前
1秒前
咕咕咕完成签到,获得积分10
1秒前
经法发布了新的文献求助10
2秒前
晚亭完成签到,获得积分10
2秒前
欲望被鬼举报戚薇求助涉嫌违规
3秒前
yangyang发布了新的文献求助10
3秒前
优雅的琳发布了新的文献求助10
4秒前
时光发布了新的文献求助10
4秒前
yuki完成签到,获得积分10
4秒前
南逸然完成签到,获得积分10
4秒前
4秒前
5秒前
HongJiang发布了新的文献求助10
5秒前
5秒前
筱谭完成签到 ,获得积分10
5秒前
guanze完成签到 ,获得积分10
6秒前
zho关闭了zho文献求助
6秒前
ding应助起承转合采纳,获得10
6秒前
7秒前
蛋炒饭不加蛋完成签到,获得积分10
7秒前
酷炫素完成签到,获得积分10
7秒前
阿金发布了新的文献求助10
8秒前
Jasper应助帅气鹭洋采纳,获得10
8秒前
8秒前
明天更好发布了新的文献求助10
8秒前
9秒前
科研通AI5应助小柠檬采纳,获得10
9秒前
YY完成签到,获得积分10
9秒前
10秒前
科研通AI5应助stt采纳,获得10
10秒前
LDM发布了新的文献求助10
10秒前
上官若男应助乐正成危采纳,获得10
11秒前
小二郎应助有魅力傲菡采纳,获得10
11秒前
追寻夜香完成签到,获得积分10
11秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 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 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527469
求助须知:如何正确求助?哪些是违规求助? 3107497
关于积分的说明 9285892
捐赠科研通 2805298
什么是DOI,文献DOI怎么找? 1539865
邀请新用户注册赠送积分活动 716714
科研通“疑难数据库(出版商)”最低求助积分说明 709678