ao-56-16-4757.pdf (1.77 MB)
Interfacial surface roughness determination by coherence scanning interferometry using noise compensation
journal contribution
posted on 2017-06-08, 10:49 authored by Hiro Yoshino, Michael WallsMichael Walls, Roger SmithThe capability of coherence scanning interferometry has been extended recently to include the determination of the interfacial surface roughness between a thin film and a substrate when the surface perturbations are less than ∼10 nm∼10 nm in magnitude. The technique relies on introducing a first-order approximation to the helical complex field (HCF) function. This approximation of the HCF function enables a least-squares optimization to be carried out in every pixel of the scanned area to determine the heights of the substrate and/or the film layers in a multilayer stack. The method is fast but its implementation assumes that the noise variance in the frequency domain is statistically the same over the scanned area of the sample. This results in reconstructed surfaces that contain statistical fluctuations. In this paper we present an alternative least-squares optimization method, which takes into account the distribution of the noise variance-covariance in the frequency domain. The method is tested using results from a simulator and these show a significant improvement in the quality of the reconstructed surfaces.
Funding
Engineering and Physical Sciences Research Council (EPSRC) (EP/J017361/1, EP/M014797/1).
History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
Applied OpticsVolume
56Pages
4757 - 4765Citation
YOSHINO, H., WALLS, M. and SMITH, R., 2017. Interfacial surface roughness determination by coherence scanning interferometry using noise compensation. Applied Optics, 56 (16), pp. 4757-4765.Publisher
Optical Society of AmericaVersion
- VoR (Version of Record)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/Acceptance date
2017-04-25Publication date
2017-05-31Copyright date
2017Notes
This is an Open Access article published by OSA and distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), https://creativecommons.org/licenses/by/4.0/ISSN
1559-128XeISSN
2155-3165Publisher version
Language
- en