Back to Search Start Over

Plasmon resonance based gold nanoparticle doped optical fibre strain sensing

Authors :
Wang, X. (author)
Benedictus, R. (author)
Groves, R.M. (author)
Wang, X. (author)
Benedictus, R. (author)
Groves, R.M. (author)
Publication Year :
2022

Abstract

Strain-based structural health monitoring (SHM) relies on high performance strain sensing methods. Gold nanoparticle (NP) doped fibre optic sensors not only have the potential to increase the intensity of the backscattered signal to increase the signal to noise ratio but also have plasmon resonance peaks in the visible light range. The spectral peak shift of the plasmon resonance may be used for strain sensing. In this paper, the spectral peak shift of the plasmon resonance of an optical fibre containing gold NPs under axial strain was analysed. A modified Lorentz-Drude (LD) model with the T-matrix method was used and the spectral peak shifts of spheroidal NPs under strain were calculated. An approximate analytical expression was derived for faster calculation. The modelling presented in this paper shows that the ratio of the change of the peak wavelength to the strain can be related to the refractive index (RI) change of the optical fibre under strain, the shape change of the gold NP, and the RI change of the gold NP. The peak shift was also observed experimentally in an optical adhesive containing gold NPs under compression. The peak shifts were analysed at different RI of the optical fibres, 1.35, 1.45, 1.55 and 1.65 respectively, in order to cover the range of RI of fused silica and some polymer materials. The results confirm experimentally that the applied axial strain can induce the peak wavelength shift by the NPs. By choosing a different optical fibre or the properties of the NPs, the wavelength change ratio has the potential to be tuned, which may be used for highly sensitive strain sensing.<br />Structural Integrity & Composites

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1327983472
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1016.j.optlastec.2022.108272