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Raman quantification of (R)-(+)-limonene in mineral oil: An integrated PCA/PLS and DFT-PED approach
Joaquín Hernández-Fernández1, Jhojan Salcedo-Castellar2
1Chemistry Program, Department of Natural and Exact Sciences, University of Cartagena, San Pablo Campus, Cartagena de Indias 130015, Colombia; Department of Natural and Exact Science, Universidad de la Costa, Barranquilla 080002, Colombia.
A new Raman spectroscopy method accurately quantifies (R)-(+)-limonene in mineral oil. This technique uses chemometric analysis and vibrational interpretation for reliable results in hydrocarbon matrices.
Area of Science:
- Analytical Chemistry
- Spectroscopy
- Computational Chemistry
Background:
- Quantifying (R)-(+)-limonene in mineral oil presents challenges due to spectral overlap with the hydrocarbon matrix.
- Identifying selective spectral regions is crucial for accurate quantification.
Purpose of the Study:
- To develop and validate a Raman spectroscopy-based method for quantifying (R)-(+)-limonene in mineral oil.
- To utilize chemometric analysis and DFT calculations for enhanced spectral interpretation and quantification.
Main Methods:
- Raman spectroscopy was employed for spectral acquisition.
- Spectral pretreatment and Principal Component Analysis/Partial Least Squares (PCA/PLS) chemometric analysis were performed.
- Density Functional Theory (DFT) calculations aided in vibrational interpretation and band assignment.
Main Results:
- The 1700-1600 cm⁻¹ spectral region, corresponding to CC stretching vibrations, showed higher analytical specificity than aliphatic CH stretching.
- The PLS model achieved excellent internal predictive performance with R² = 0.990, RMSEC = 1.70% w/w, average recovery of 104.8%, and mean relative error of 4.8%.
- PCA demonstrated concentration-dependent spectral organization, indicating method reliability.
Conclusions:
- The developed Raman spectroscopy method is suitable for formulation-level quantification of limonene in hydrocarbon-rich matrices.
- DFT-assisted vibrational interpretation and chemometric analysis are effective for analyzing complex mixtures.
- Further validation is recommended for external robustness and lower concentration applicability.
