Electro-Mechanical Co-optimization of MEMS Devices in Python

Rui Esteves, Chen Wang, Joana Vaz Pinto, Michael Kraft

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This paper describes a novel methodology for electro-mechanical co-optimization of microelectromechanical systems (MEMS) devices. It facilitates a MEMS design flow at system-level, in which mechanical and electrical domains interact with each other to achieve an optimal system performance. The proposed design methodology is fully based on Python, featuring a single platform, open-source as well as low computational cost. A simple open-loop MEMS accelerometer is presented to demonstrate the effectiveness of the design methodology. It improved the accelerometer in terms of the product of sensitivity and resonant frequency by 44% and sensitivity by 110%.

Original languageEnglish
Title of host publicationIEEE Sensors, SENSORS 2020 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)9781728168012
Publication statusPublished - 25 Oct 2020
Event2020 IEEE Sensors, SENSORS 2020 - Virtual, Rotterdam, Netherlands
Duration: 25 Oct 202028 Oct 2020

Publication series

NameProceedings of IEEE Sensors
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISSN (Print)1930-0395
ISSN (Electronic)2168-9229


Conference2020 IEEE Sensors, SENSORS 2020
CityVirtual, Rotterdam


  • FEM
  • genetic algorithm
  • mechanical modelling
  • MEMS
  • Python


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