Microelectromechanical systems (MEMS) have been already successfully commercialized for around 20 years. The design of novel MEMS sensors currently targets two important features: smaller dimensions and higher reliability. As the characteristic size of the mechanical components of the devices decreases, uncertainties in the mechanical and geometrical properties induced by the microfabrication process become more and more important. To address these issues, an on-chip testing device has been proposed to avoid any visual inspection for the read-out. The electromechanical responses of ten nominally identical specimens have been recorded, and experimental data have shown a significant scattering due to the presence of relevant uncertainty sources. To interpret the response of the device, an analytical reduced-order model of the whole device has been developed. A genetic algorithm has then been adopted to identify features of the mechanical and geometrical uncertainties in the batch of test structures.

Assessment of micromechanically-induced uncertainties in the electromechanical response of MEMS devices

MIRZAZADEH, RAMIN;MARIANI, STEFANO
2016

Abstract

Microelectromechanical systems (MEMS) have been already successfully commercialized for around 20 years. The design of novel MEMS sensors currently targets two important features: smaller dimensions and higher reliability. As the characteristic size of the mechanical components of the devices decreases, uncertainties in the mechanical and geometrical properties induced by the microfabrication process become more and more important. To address these issues, an on-chip testing device has been proposed to avoid any visual inspection for the read-out. The electromechanical responses of ten nominally identical specimens have been recorded, and experimental data have shown a significant scattering due to the presence of relevant uncertainty sources. To interpret the response of the device, an analytical reduced-order model of the whole device has been developed. A genetic algorithm has then been adopted to identify features of the mechanical and geometrical uncertainties in the batch of test structures.
The 3rd International Electronic Conference on Sensors and Applications (ECSA 2016)
978-3-03842-408-6
on-chip testing; reduced-order modelling; uncertainty assessment; polysilicon film; Young’s modulus; overetch; geometrical offset.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1006351
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