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Developing Correction Methods by Revisiting the Concept of Effective Thickness in Attenuated Total Reflection
Thomas G Mayerhöfer1,2, Jürgen Popp1,2
1Spectroscopy and Imaging, Leibniz Institute of Photonic Technology (IPHT), Jena, Germany.
This study presents a refined method for calculating effective thickness in attenuated total reflection (ATR) spectroscopy, improving accuracy for organic and biological samples. The new approach enhances ATR correction schemes and aids spectral analysis.
Area of Science:
- Spectroscopy
- Physical Chemistry
- Materials Science
Background:
- Attenuated total reflection (ATR) spectroscopy is crucial for analyzing samples with low absorption.
- The effective thickness concept, introduced by Hansen and Harrick, is vital for quantitative ATR analysis.
- Existing methods for effective thickness derivation can be complex and may lack precision for certain materials.
Purpose of the Study:
- To develop a more straightforward derivation of effective thickness in ATR spectroscopy.
- To improve estimations of effective thickness for s- and p-polarized light.
- To enhance existing ATR correction schemes and introduce a novel spectral correction method.
Main Methods:
- A novel derivation of effective thickness following Hansen's approach, incorporating an intermediate approximation.
- Application of Fresnel's equations for validation, particularly for organic and biological materials.
- Development of a Kramers-Kronig transformed absorbance-based correction scheme.
Main Results:
- A more straightforward derivation of effective thickness was achieved.
- Improved estimations for effective thicknesses with s- and p-polarized light were obtained.
- A new correction scheme utilizing Kramers-Kronig transformed absorbance was introduced, addressing spectral shifts.
Conclusions:
- The new derivation provides more accurate effective thickness estimations, especially for organic and biological samples.
- The enhanced ATR correction scheme improves quantitative analysis in ATR spectroscopy.
- The Kramers-Kronig based correction shows potential for advanced spectral analysis, including pattern recognition and identification.
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