Prediction of sublayer depth in turbid media using spatially offset Raman spectroscopy

Area of Science:

• Spectroscopy
• Optics
• Analytical Chemistry

Background:

• Conventional Raman spectroscopy is limited in analyzing optically thick or turbid media due to shallow light penetration.
• Characterizing subsurface layers in complex materials remains a significant analytical challenge.

Purpose of the Study:

• To demonstrate the feasibility of monitoring layer depth in turbid media using Spatially Offset Raman Spectroscopy (SORS).
• To enhance the characterization capabilities for optically thick samples beyond conventional Raman limits.

Main Methods:

• Utilized Spatially Offset Raman Spectroscopy (SORS) for deep light penetration into turbid media.
• Employed multivariate analysis, including three-dimensional parallel factor analysis (PARAFAC), to resolve spectral data.
• Integrated depth information as an additional dimension in SORS experiments.

Main Results:

• Successfully monitored the depth of optically thick layers in turbid media.
• Characterized sample layers at least twice as thick as possible with conventional Raman spectroscopy.
• Achieved typical relative accuracies between 5% and 10% for depth measurements.
• Resolved pure spectra of individual layers with high accuracy using 3D multivariate techniques.

Conclusions:

• SORS combined with multivariate analysis provides a robust method for depth profiling in turbid media.
• The technique significantly extends the depth penetration capability compared to conventional Raman spectroscopy.
• Incorporating depth information enhances spectral resolution and accuracy for layered materials.