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Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station

Characterization of SiN Integrated Optical Phased Arrays on a Wafer-Scale Test Station

Published on: April 1, 2020

Optimization of off-null ellipsometry in sensor applications.

Guoliang Wang¹, Hans Arwin, Roger Jansson

¹Department of Physics and Measurement Technology, Laboratory of Applied Optics, Linköping University, SE-581 83, Linköping, Sweden. guowa@ifm.liu.se

|April 13, 2004

Summary

This summary is machine-generated.

This study optimizes ellipsometric sensor angles for maximum signal change in sensing layers. It analytically derives optimal conditions, showing ellipsometry

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Area of Science:

Optical sensing technologies
Ellipsometry and reflectometry
Surface characterization

Background:

Ellipsometric sensor systems rely on precise angle settings for optimal performance.
Understanding intensity changes is crucial for accurate sensing layer property analysis.
Reflectance variations can influence the sensitivity of optical sensing methods.

Purpose of the Study:

To optimize azimuth angle settings in an off-null ellipsometric system.
To maximize intensity changes in response to sensing layer property variations.
To compare the effectiveness of ellipsometry versus reflectometry for sensing applications.

Main Methods:

Analytical derivation of optimal azimuth angles under linear parameter change assumptions.
Investigating optimization with and without considering s-reflectance changes.
Numerical verification of derived optimal conditions.

Main Results:

Optimal azimuth angle conditions were analytically determined for maximum intensity modulation.
The study identified conditions for both scenarios: considering and ignoring s-reflectance changes.
Numerical examples validated the derived optimal conditions.

Conclusions:

Optimized ellipsometric sensor configurations enhance sensitivity to sensing layer properties.
Ellipsometry offers advantages over reflectometry for specific sensing layer characterizations.
Analytical and numerical methods confirm the effectiveness of the proposed optimization strategy.