Highly sensitive two dimensional tactile sensor using multi-walled carbon nanotube

Takuya Nozaki, Ken Suzuki, Hideo Miura

Research output: Contribution to conferencePaperpeer-review

3 Citations (Scopus)

Abstract

A highly sensitive two-dimensional strain sensor, which consists of area-arrayed bundles of multi walled carbon nanotubes (MWCNTs), has been developed by applying micro electro mechanical systems (MEMS) technology. The spatial resolution of the developed sensor was 0.5 mm which is superior to that of human finger, 1mm. Since the shape of the grown MWCNTs varies widely depending on the average thickness of the catalyst layer and the growth temperature, the optimum growth condition was investigated for forming the bundles of MWCNTs with vertical alignment and longer length. The change of the electrical resistance of the grown MWCNTs bundle was measured by applying a compression test in the strain range from 0% to -50%. It was found that the electrical resistance of the MWCNTs bundle increased almost linearly with the applied compressive strain and its strain sensitivity was about 100%/%-strain (gauge factor: 100). The MWCNT bundles with the aspect ration of 20 were grown by using the optimal growth conditions. This bundle structure showed the high load sensitivity of 10 mN as was expected. In addition, two-dimensional deformation distribution of the area-arrayed bundles was observed under the application of the concentric circular load.

Original languageEnglish
DOIs
Publication statusPublished - 2014 Jan 1
EventASME 2014 International Mechanical Engineering Congress and Exposition, IMECE 2014 - Montreal, Canada
Duration: 2014 Nov 142014 Nov 20

Other

OtherASME 2014 International Mechanical Engineering Congress and Exposition, IMECE 2014
Country/TerritoryCanada
CityMontreal
Period14/11/1414/11/20

ASJC Scopus subject areas

  • Mechanical Engineering

Fingerprint

Dive into the research topics of 'Highly sensitive two dimensional tactile sensor using multi-walled carbon nanotube'. Together they form a unique fingerprint.

Cite this