Optimization of off-null ellipsometry for air/solid interfaces

Abstract

The optimization of off-null ellipsometry is described with emphasis on the improvement of sample thickness sensitivity. Optimal conditions are dependent on azimuth angle settings of the polarizer, compensator, and analyzer in a polarizer-compensator-sample-analyzer ellipsometer arrangement. Numerical simulation utilized offers an approach to present the dependence of the sensitivity on the azimuth angle settings, from which optimal settings corresponding to the best sensitivity are derived. For a series of samples of SiO 2 layer (thickness in the range of 1.8-6.5 nm) on silicon substrate, the theory analysis proves that sensitivity at the optimal settings is increased 20 times compared to that at null settings used in most works, and the relationship between intensity and thickness is simplified as a linear type instead of the original nonlinear type, with the relative error reduced to ϳ1͞100 at the optimal settings. Furthermore the discussion has been extended toward other factors affecting the sensitivity of the practical system, such as the linear dynamic range of the detector, the signal-to-noise ratio and the intensity from the light source, etc. Experimental results from the investigation of SiO 2 layer on silicon substrate are chosen to verify the optimization.

Protein microarray biosensors based on imaging ellipsometry techniques and their applications

“…Slight variations of thickness can be remarkably distinguished by imaging ellipsometry, and the results are represented as grayscale images (Jin, 2008). The grayscale value is approximately linearly proportional to the thickness of the molecular film (Chen et al, 2007a). The control system is responsible for combining the microarray reactor with the imaging ellipsometer and functions to control the hardware's mechanical motion and obtain results in images.…”

“…Over the past 16 years, commercial products based on single wavelength and spectroscopic imaging ellipsometry, made by the Nanofilm Company (http://www.nanofilm.de/; Gedig et al, 2008), have entered the market, and many significant improvements (e.g., the off-null sampling method (Chen et al, 2007a), spectroscopic technique , automatic control, microarray surface modification Jin, 2003a, 2004a, b), micro-fluidic reactors (Jin and Wang, 2002;Wang et al, 2006), bio-system optimization, and protein interaction databases) have been introduced into BIE to improve its performance and feasibility. Therefore, BIE has been developed into an automatic device for quantitative and high-throughput protein analysis ).…”

A Compact Imaging Ellipsometer for Label-free Biosensor

“…The angle of incidence is set at 75° close to the quasi-Brewster angle of Si substrate. With an optimal azimuth setting of polarization elements P, C and A for a high contrast of imaging, the detected intensity is approximately linearly proportional to the thickness corresponding to the surface concentration [8], which provides a thickness resolution in a 0.1 nm order and a lateral resolution in micron. The field of view reaches to several square centimeters.…”

Approach to Quantitative Detection of CD146 with a Label-free Protein Biosensor Based on Imaging Ellipsometry

“…It can be utilized for the visualization of ultra-thin films and slight surface concentration change. Here, it is used to quantify the thickness distribution of protein layers [6,15]. A slight variation of thickness can be remarkably distinguished by imaging ellipsometry and the result is represented by images in grayscale format (8 bits, 0-117 255 grayscale or 10 bits, 1024 grayscale).…”

“…A slight variation of thickness can be remarkably distinguished by imaging ellipsometry and the result is represented by images in grayscale format (8 bits, 0-117 255 grayscale or 10 bits, 1024 grayscale). The grayscale value is approximately linearly proportional to the thickness corresponding to the surface concentration [15].…”