A Miniaturized Chemical Vapor Detector Using MEMS Flexible Platform

According to the Canadian Cancer Society, lung cancer is the one of the leading causes of cancer death. It has been shown that cancer survival chance depends on factors including the availability of early detection and diagnostic tools such as miniaturized and sensitive gas sensor. This can detect the released volatiles in addition to be implementable in portable electronics, which decisively improves the patient’s survival rate. Therefore, in this thesis and in an effort to develop high-sensitive and miniaturized gas sensor, a microelectromechanical systems (MEMS) platform is utilized. In this work, a sensitive gas sensor is proposed by employing capacitive micromachined ultrasonic transducer (CMUT) configuration due to its high sensitivity, low LOD and reversibility. The comprehensive analytical model is proposed for this circular bilayer CMUT-based gas sensor for the first time, which includes all the known critical design parameters of the sensor. The model also includes effects of membrane softening and residual stress of the top membrane and the sensing component. The model is further followed by conducting FEA simulations, to investigate eect of critical parameters on center resonant frequency of the device. The achieved results for FEA simulations are compared with the proposed model, which shows less than 5% average variation. Both model and simulations verify that maximum sensitivity occurs at smaller radius, thinner membrane and structural material with lower density. The simulations results are utilized to maximize the sensitivity of the gas sensor in a sample frequency range of 5MHz and 25MHz. The proposed device has a 500nm functionalized polysilicon membrane with 300nm polyisobutylene (PIB) while the cavity height is 500nm and 30V DC bias voltage is applied. The proposed and designed CMUT-based gas sensor offers a 222Hz/zg sensitivity (∆f /∆m) in the aforementioned frequency range.

Name thesis:degree_name

M.A.Sc.

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Grantor

University of Windsor

Year dc:date.issued

2019

Author dc:creator

• Nazemi, Haleh

Advisor dc:contributor.advisor

• Emadi, Arezoo

Contributors dc:contributor

• mita@uwindsor.ca

Licence

• http://creativecommons.org/licenses/by-nc-nd/4.0/

Language dc:language.iso

en_CA

Handle dc:identifier.uri

https://hdl.handle.net/20.500.14776/7203

OAI identifier oai:identifier

oai:uwindsor.scholaris.ca:20.500.14776/7203