# Tailoring stresses in piezoresistive microcantilevers for enhanced surface stress sensing: insights from topology optimization

https://mdr.nims.go.jp/datasets/6c2caa08-750a-48d3-8f03-e53cc1a59c0f

## File

- [JJAP_final.pdf](https://mdr.nims.go.jp/filesets/611eb0da-72f8-4407-af26-cf157561a673/download) ([Detail](https://mdr.nims.go.jp/filesets/611eb0da-72f8-4407-af26-cf157561a673.md))

## Id

6c2caa08-750a-48d3-8f03-e53cc1a59c0f

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-10-17T01:38:57.681920Z

## Updated at

2025-01-23T03:30:11.095231Z

## Published at

2025-01-23T03:30:12.159874Z

## Doi

https://doi.org/10.48505/nims.4867

## First published url

https://doi.org/10.35848/1347-4065/ad1939

## Date published

2024-01-01

## Recorded date published

2024-1-1

## Resource type

journal_article

## Manuscript type

accepted_manuscript

## Collection



## Title

- title: 'Tailoring stresses in piezoresistive microcantilevers for enhanced surface
    stress sensing: insights from topology optimization'
  title_type: original
  lang: en

## Description

- description: In assessing piezoresistive microcantilever sensitivity for surface
    stress sensing, the key is its capacity to translate surface stress into changes
    in resistance. This change hinges on the interplay between stresses and piezoresistivity.
    Traditional optimization has been constrained by rudimentary 1D models, overlooking
    potentially superior designs. Addressing this, we employed topology optimization
    to optimize Si(100) microcantilevers with a p-type piezoresistor. This led to
    optimized designs with up to 30% enhanced sensitivity over conventional designs.
    A recurrent "double-cantilever" configuration emerged, which optimizes longitudinal
    stress and reduces transverse stress at the piezoresistor, resulting in enhanced
    sensitivity. We developed a simplified model to analyze stress distributions in
    these designs. By adjusting geometrical features in this model, we identified
    ideal parameter combinations for optimal stress distribution. Contrary to conventional
    designs favoring short cantilevers, our findings redefine efficient surface stress
    sensing, paving the way for innovative sensor designs beyond the conventional
    rectangular cantilevers.
  description_type: abstract
  lang: und

## Creator

- name: Chao Zhuang
  role: author
  orcid: https://orcid.org/0000-0002-4469-5364
  organization: National Institute for Materials Science
- name: Kosuke Minami
  role: author
  orcid: https://orcid.org/0000-0003-4145-1118
  organization: National Institute for Materials Science
- name: Kota Shiba
  role: author
  orcid: https://orcid.org/0000-0001-7775-0318
  organization: National Institute for Materials Science
- name: Genki Yoshikawa
  role: author
  orcid: https://orcid.org/0000-0002-9136-8964
  organization: National Institute for Materials Science

## Contact agent



## Publisher

organization: IOP Publishing

## Managing organization



## Keyword

- subject: Topology optimization
  schema: not_defined
- subject: nanomechanical sensors
  schema: not_defined

## Rights

- description: This is the Accepted Manuscript version of an article accepted for
    publication in Japanese Journal of Applied Physics.  IOP Publishing Ltd is not
    responsible for any errors or omissions in this version of the manuscript or any
    version derived from it.  The Version of Record is available online at https://dx.doi.org/10.35848/1347-4065/ad1939
  identifier: https://creativecommons.org/licenses/by-nc-nd/4.0/

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo

start_date: 2024-01-23
end_date: 2025-01-23

## Journal

- title: Japanese Journal of Applied Physics
  issn: '13474065'
  volume: '63'
  issue: '1'
  article_number: '015005'

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## Funding

- identifier: 20K20554
  funder_name: Japan Society for the Promotion of Science

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## Fileset

- id: 611eb0da-72f8-4407-af26-cf157561a673
  filename: JJAP_final.pdf
  content_type: application/pdf
  size: 2435873
  md5: 730405fb2700fcd3fcf08ae26aa5aac5

## Thumbnail

fileset_id: 611eb0da-72f8-4407-af26-cf157561a673
filename: JJAP_final.pdf