Concentration dependence of Kubelka-Munk function and apparent absorbance button sample holder infrared spectra

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Materials Science

Background:

• Diffuse reflection infrared spectroscopy (DRIS) is a valuable technique for analyzing solid samples.
• Quantifying analytes in solid matrices using DRIS often involves mathematical transformations of spectral data.
• The Kubelka-Munk (KM) function and apparent absorbance are common transformations used for quantitative analysis.

Purpose of the Study:

• To evaluate the linearity and sensitivity of the Kubelka-Munk function and apparent absorbance formats for quantitative analysis of solid samples using diffuse reflection infrared spectroscopy.
• To compare the performance of these two spectral transformation methods across varying concentrations and matrix compositions, including samples with high clay content.

Main Methods:

• Infrared spectra were collected using a button sample holder in diffuse reflection mode.
• Two types of sample powders were prepared: caffeine dispersed in potassium chloride, and copper thiosulfate mixed with kaolinite and potassium chloride.
• Spectral data were processed using both Kubelka-Munk and apparent absorbance functions.
• Vibration band area and peak intensity were plotted against analyte concentration to assess linearity and sensitivity.

Main Results:

• For caffeine and copper thiosulfate, Kubelka-Munk calibration functions generally showed linear trends, while apparent absorbance functions were curved.
• Both formats exhibited similar sensitivities over narrow concentration ranges, yielding linear plots.
• In samples with high kaolinite (clay) content, plots of vibration band area versus concentration were linear over wider ranges than those obtained using the Kubelka-Munk function.

Conclusions:

• Both Kubelka-Munk and apparent absorbance methods are viable for quantitative analysis in diffuse reflection infrared spectroscopy, with comparable sensitivities in certain conditions.
• The presence of high clay content can influence the linearity of quantitative analysis, suggesting that band area analysis may be more robust in complex matrices.
• The choice of spectral transformation and analysis method (e.g., band area vs. peak intensity) should consider the sample matrix composition for optimal quantitative results.