Load deflection analysis of rectangular graphene diaphragm for MEMS intracranial pressure sensor applications

Rahman, Siti Hajar Abd and Soin, Norhayati and Ibrahim, Fatimah (2018) Load deflection analysis of rectangular graphene diaphragm for MEMS intracranial pressure sensor applications. Microsystem Technologies, 24 (2). pp. 1147-1152. ISSN 0946-7076,

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Official URL: https://doi.org/10.1007/s00542-017-3477-7

Abstract

There is a need to establish an ultra-small micro pressure sensors in dynamic performance for intracranial monitoring which can reduce the risk of inflammation and infection and allow for its insertion through a catheter into small vessels and cavities. The need for small, lightweight and highly sensitive sensors seem to be aligned with the properties owned by graphene based sensor that have been overwhelmingly researched for their applications in biomedical engineering, sensor technology and electronic applications. The work described in this report aims to fill this gap and presents the deflection analysis and internal stress of pressurized rectangular graphene diaphragm having various b/a (length/width) ratio and thicknesses. The sensing structure of MEMS intracranial pressure sensor consists of a rectangular graphene diaphragm suspended over a cavity that is formed on silicon substrate. The deflection and sensitivity analysis was done using COMSOL Multiphysics software by applying various micron thicknesses of multilayered graphene. For the rectangular graphene diaphragm with b/a ratio of 2 and 4, results shows that the internal stress is associated with the thickness of the graphene diaphragm and the effect of thickness become less significant when thickness reaching 0.25 µm for graphene diaphragm with b/a ratio of 6. Due to the influence of this internal force, multilayer graphene diaphragms with higher thickness are more sensitive than monolayer. This study has shown the feasibility of graphene diaphragm in piezoresistive MEMS intracranial pressure sensor application.

Item Type: Article
Funders: UNSPECIFIED
Uncontrolled Keywords: Deflection analysis; Electronic application; Graphene-based sensors; Intra-cranial pressure; Micro pressure sensors; Multi-layered graphene; Multilayer graphene; Sensor applications
Subjects: R Medicine
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 17 Apr 2019 07:45
Last Modified: 17 Apr 2019 07:45
URI: http://eprints.um.edu.my/id/eprint/20961

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