Research on the quantitative analysis for detection sulfate using laser Raman spectroscopy

Sicheng Ma; Chidong Xu

doi:10.1117/12.2690267

17 August 2023 Research on the quantitative analysis for detection sulfate using laser Raman spectroscopy

Sicheng Ma, Chidong Xu

Proceedings Volume 12757, 3rd International Conference on Laser, Optics, and Optoelectronic Technology (LOPET 2023); 127571X (2023) https://doi.org/10.1117/12.2690267
Event: 3rd International Conference on Laser, Optics and Optoelectronic Technology (LOPET 2023), 2023, Kunming, China

Abstract

Sulfate is an important anion in marine research and is closely associated with numerous marine phenomena. Laser Raman spectroscopy is a nondestructive, non-contact molecular fingerprint spectroscopy that can identify as well as quantify substances, and is suitable for the detection and quantification of substances in solution. In this paper, the Raman spectra of different concentrations of sodium sulfate solutions were measured under laboratory conditions and quantified by four methods: internal standard normalization method, multiple linear regression, random forest and XGBoost, respectively, to establish models and analyze the results. The results show that multiple linear regression, random forest, and XGBoost can improve the accuracy based on the internal standard normalization method, while random forest has the best results with a mean percentage error of 4.9867%, mean square error of 4.68932, and R²= 0.98813, which proves the superiority of machine learning methods for quantitative analysis of Raman spectra based on target substances in seawater quantitative analysis of substances in seawater.

Citation Download Citation

Sicheng Ma and Chidong Xu "Research on the quantitative analysis for detection sulfate using laser Raman spectroscopy", Proc. SPIE 12757, 3rd International Conference on Laser, Optics, and Optoelectronic Technology (LOPET 2023), 127571X (17 August 2023); https://doi.org/10.1117/12.2690267

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