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Investigation of a micromachined electric field mill to maximize the electrostatic field sensitivity

Authors: Zhou, Yu;

Investigation of a micromachined electric field mill to maximize the electrostatic field sensitivity

Abstract

This thesis includes the modification and optimization to an electric field mill based on micromachining technology. The sensor was originally designed to overcome the disadvantages of the conventional macroscopic field mill. Although it achieved all these listed above with a minimum detectable field strength at 42 V/m, some drawbacks are yet to be settled. In order to overcome these drawbacks, modifications are studied and put forward. Metal coating of the sensor surface could lead to a good electrical grounding that addresses the charging problem. Non-resonant working design was established with a shutter displacement around 5μm. Finite element simulations were set up to look into the optimizations of the structure parameters of the sensor, focusing on the shutter and electrodes. Moreover, the fabrication process was also studied with attempts of each step carried out in the NSFL of University of Manitoba.

Country
Canada
Related Organizations
Keywords

FEM simulation, MEFM

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green