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Numerical retrieval of thin aluminium layer properties from SPR experimental data
1Project Group for Automatic Mesh Generation and Advanced Methods, Gamma3 Project (UTT-INRIA), University of Technology of Troyes, 12 rue Marie Curie-BP 2060, 10010 Troyes Cedex, France. dominique.barchiesi@utt.fr
Optics Express
|April 20, 2012
Summary
Particle Swarm Optimization solved the inverse problem for Surface Plasmon Resonance (SPR) measurements of thin aluminum layers. This method determined optical and geometric parameters, fitting experimental data under various material assumptions.
Area of Science:
- Optoelectronics and Photonics
- Materials Science
- Computational Physics
Background:
- Surface Plasmon Resonance (SPR) is a sensitive optical technique for characterizing thin films.
- Solving the inverse problem in SPR is crucial for accurate material property determination.
- Kretschmann configuration is a standard setup for exciting surface plasmons.
Purpose of the Study:
- To solve the inverse problem for SPR measurements on thin aluminum layers.
- To determine optical and geometrical parameters of aluminum thin films.
- To investigate the influence of material hypotheses (pure, oxidized metal) and layer thickness on optical properties.
Main Methods:
- Utilized Particle Swarm Optimization (PSO) to solve the inverse problem.
- Analyzed experimental reflection coefficients in both s and p polarizations.
- Compared results for four aluminum samples under three material models: pure metal, metal-oxide mixture, and metal coated with oxide.
Main Results:
- Successfully determined optical indices and geometrical parameters for aluminum thin films.
- Achieved best fit for experimental SPR data under different material assumptions.
- Quantified the impact of metal layer thickness on its optical characteristics.
Conclusions:
- Particle Swarm Optimization is an effective method for solving the SPR inverse problem.
- The study provides insights into the optical properties of aluminum layers, considering oxidation.
- Accurate parameter retrieval is essential for understanding thin film behavior in SPR applications.
