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Published in: Microsystem Technologies 2/2018

29-06-2017 | Technical Paper

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

Authors: S. H. A. Rahman, N. Soin, F. Ibrahim

Published in: Microsystem Technologies | Issue 2/2018

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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.

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Metadata
Title
Load deflection analysis of rectangular graphene diaphragm for MEMS intracranial pressure sensor applications
Authors
S. H. A. Rahman
N. Soin
F. Ibrahim
Publication date
29-06-2017
Publisher
Springer Berlin Heidelberg
Published in
Microsystem Technologies / Issue 2/2018
Print ISSN: 0946-7076
Electronic ISSN: 1432-1858
DOI
https://doi.org/10.1007/s00542-017-3477-7

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