Cargando…
Design of freeform geometries in a MEMS accelerometer with a mechanical motion preamplifier based on a genetic algorithm
This paper describes a novel, semiautomated design methodology based on a genetic algorithm (GA) using freeform geometries for microelectromechanical systems (MEMS) devices. The proposed method can design MEMS devices comprising freeform geometries and optimize such MEMS devices to provide high sens...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433402/ https://www.ncbi.nlm.nih.gov/pubmed/34567713 http://dx.doi.org/10.1038/s41378-020-00214-1 |
_version_ | 1783751370545823744 |
---|---|
author | Wang, Chen Song, Xiaoxiao Fang, Weidong Chen, Fang Zeimpekis, Ioannis Wang, Yuan Quan, Aojie Bai, Jian Liu, Huafeng Schropfer, Gerold Welham, Chris Kraft, Michael |
author_facet | Wang, Chen Song, Xiaoxiao Fang, Weidong Chen, Fang Zeimpekis, Ioannis Wang, Yuan Quan, Aojie Bai, Jian Liu, Huafeng Schropfer, Gerold Welham, Chris Kraft, Michael |
author_sort | Wang, Chen |
collection | PubMed |
description | This paper describes a novel, semiautomated design methodology based on a genetic algorithm (GA) using freeform geometries for microelectromechanical systems (MEMS) devices. The proposed method can design MEMS devices comprising freeform geometries and optimize such MEMS devices to provide high sensitivity, large bandwidth, and large fabrication tolerances. The proposed method does not require much computation time or memory. The use of freeform geometries allows more degrees of freedom in the design process, improving the diversity and performance of MEMS devices. A MEMS accelerometer comprising a mechanical motion amplifier is presented to demonstrate the effectiveness of the design approach. Experimental results show an improvement in the product of sensitivity and bandwidth by 100% and a sensitivity improvement by 141% compared to the case of a device designed with conventional orthogonal shapes. Furthermore, excellent immunities to fabrication tolerance and parameter mismatch are achieved. |
format | Online Article Text |
id | pubmed-8433402 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-84334022021-09-24 Design of freeform geometries in a MEMS accelerometer with a mechanical motion preamplifier based on a genetic algorithm Wang, Chen Song, Xiaoxiao Fang, Weidong Chen, Fang Zeimpekis, Ioannis Wang, Yuan Quan, Aojie Bai, Jian Liu, Huafeng Schropfer, Gerold Welham, Chris Kraft, Michael Microsyst Nanoeng Article This paper describes a novel, semiautomated design methodology based on a genetic algorithm (GA) using freeform geometries for microelectromechanical systems (MEMS) devices. The proposed method can design MEMS devices comprising freeform geometries and optimize such MEMS devices to provide high sensitivity, large bandwidth, and large fabrication tolerances. The proposed method does not require much computation time or memory. The use of freeform geometries allows more degrees of freedom in the design process, improving the diversity and performance of MEMS devices. A MEMS accelerometer comprising a mechanical motion amplifier is presented to demonstrate the effectiveness of the design approach. Experimental results show an improvement in the product of sensitivity and bandwidth by 100% and a sensitivity improvement by 141% compared to the case of a device designed with conventional orthogonal shapes. Furthermore, excellent immunities to fabrication tolerance and parameter mismatch are achieved. Nature Publishing Group UK 2020-11-30 /pmc/articles/PMC8433402/ /pubmed/34567713 http://dx.doi.org/10.1038/s41378-020-00214-1 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wang, Chen Song, Xiaoxiao Fang, Weidong Chen, Fang Zeimpekis, Ioannis Wang, Yuan Quan, Aojie Bai, Jian Liu, Huafeng Schropfer, Gerold Welham, Chris Kraft, Michael Design of freeform geometries in a MEMS accelerometer with a mechanical motion preamplifier based on a genetic algorithm |
title | Design of freeform geometries in a MEMS accelerometer with a mechanical motion preamplifier based on a genetic algorithm |
title_full | Design of freeform geometries in a MEMS accelerometer with a mechanical motion preamplifier based on a genetic algorithm |
title_fullStr | Design of freeform geometries in a MEMS accelerometer with a mechanical motion preamplifier based on a genetic algorithm |
title_full_unstemmed | Design of freeform geometries in a MEMS accelerometer with a mechanical motion preamplifier based on a genetic algorithm |
title_short | Design of freeform geometries in a MEMS accelerometer with a mechanical motion preamplifier based on a genetic algorithm |
title_sort | design of freeform geometries in a mems accelerometer with a mechanical motion preamplifier based on a genetic algorithm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433402/ https://www.ncbi.nlm.nih.gov/pubmed/34567713 http://dx.doi.org/10.1038/s41378-020-00214-1 |
work_keys_str_mv | AT wangchen designoffreeformgeometriesinamemsaccelerometerwithamechanicalmotionpreamplifierbasedonageneticalgorithm AT songxiaoxiao designoffreeformgeometriesinamemsaccelerometerwithamechanicalmotionpreamplifierbasedonageneticalgorithm AT fangweidong designoffreeformgeometriesinamemsaccelerometerwithamechanicalmotionpreamplifierbasedonageneticalgorithm AT chenfang designoffreeformgeometriesinamemsaccelerometerwithamechanicalmotionpreamplifierbasedonageneticalgorithm AT zeimpekisioannis designoffreeformgeometriesinamemsaccelerometerwithamechanicalmotionpreamplifierbasedonageneticalgorithm AT wangyuan designoffreeformgeometriesinamemsaccelerometerwithamechanicalmotionpreamplifierbasedonageneticalgorithm AT quanaojie designoffreeformgeometriesinamemsaccelerometerwithamechanicalmotionpreamplifierbasedonageneticalgorithm AT baijian designoffreeformgeometriesinamemsaccelerometerwithamechanicalmotionpreamplifierbasedonageneticalgorithm AT liuhuafeng designoffreeformgeometriesinamemsaccelerometerwithamechanicalmotionpreamplifierbasedonageneticalgorithm AT schropfergerold designoffreeformgeometriesinamemsaccelerometerwithamechanicalmotionpreamplifierbasedonageneticalgorithm AT welhamchris designoffreeformgeometriesinamemsaccelerometerwithamechanicalmotionpreamplifierbasedonageneticalgorithm AT kraftmichael designoffreeformgeometriesinamemsaccelerometerwithamechanicalmotionpreamplifierbasedonageneticalgorithm |