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Description
Biofuels derived from microalgae provide a sustainable alternative to fossil fuels, yet high production costs remain a significant barrier 1. Optimizing photobioreactors for biofuel production necessitates a detailed understanding of algal biomass, especially its organic components. Raman spectroscopy is a valuable tool for this analysis [2], however, distinguishing individual molecular conformers in complex mixtures remains challenging. This study employs Raman spectroscopy combined with statistical analysis to differentiate fatty acid conformers, using myristic acid as a model system. Density Functional Theory (DFT) calculations (B3LYP-D3/6-311++G**) with solvent effects (water) were used to simulate Raman spectra, achieving a balance between computational efficiency and accuracy. Statistical techniques enabled the classification of myristic acid conformers into chain, v-shaped, and twisted structures, with distinctive vibrational features identified at ~2900 cm$^{-1}$ (CH$_2$/CH$_3$ vibrations) and below 1200 cm$^{-1}$ (backbone motions) [3]. This approach enhances the precision of spectral analysis, offering a robust framework for the rapid identification of fatty acids in algal biomass, with implications for biofuel development.
REFERENCES
1 Y. Ye, W. Guo, H. H. Ngo, W. Wei, D. Cheng, X. T. Bui, N. B. Hoang, H. Zhang, Science of The Total Environment 935 (2024) 172863, https://doi.org/10.1016/j.scitotenv.2024.172863.
[2] K. Czamara, K. Majzner, M. Z. Pacia, K. Kochan, A. Kaczor, M. Baranska, Journal of Raman Spectroscopy 46 (1) (2015) 4–20, https://doi.org/10.1002/jrs.4607.
[3] T. Miteva, H. Friha, T. L. Hidouche, S. Suc, J. Palaudoux, M. Mogren Al-Mogren, E. Laure-Zins, M. Hochlaf, Spectrochimica Acta A (2025), accepted.
