Method of classification and quantitative analysis of vein quartz using LIBS and chemometric techniques
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DOI:
https://doi.org/10.32523/2616-6771-2024-147-2-48-60Keywords:
vein quartz, laser induced breakdown spectroscopy (LIBS), mathematical design of experiment, partial least squares regression (PLSR), principal component analysis (PCA), atomic absorption spectroscopy (AAS), silicate analysisAbstract
Vein quartz often becomes the subject of chemical analysis. Laser-induced breakdown spectroscopy (LIBS) is faster, cheaper, and more environmentally friendly compared to traditional silicate analysis. This study demonstrates the feasibility of using LIBS in combination with design of experiment and chemometric methods for the classification analysis of amorphous quartz and the quantitative determination of several constant impurities. The combination of objects and methods used in this work has not been previously published. Vein quartz samples were collected from various geographically distant locations. The sample preparation for LIBS involved cutting and polishing a flat surface of the quartz specimen. The LIBS instrument settings were optimized using design of experiment method. The concentrations of several trace elements in the training and control sets of samples were determined using atomic absorption spectroscopy (AAS). The spectra and analytical data of the training set were used for multivariate calibration using Partial Least Squares Regression (PLS-R). Sample classification was performed using Principal Component Analysis (PCA). It was shown that in the score plot in the space of the first three principal components, the samples confidently group according to their sources of origin. The results were validated on a test set of samples. The accuracy of quantitative determination of Mg, Ca, Na, K, Al, Ti using LIBS exceeded 90%. A method for the quantitative determination of several elements in quartz and an approach to identifying the place of origin of a sample are proposed.
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Copyright (c) 2024 V.N. Fomin, S.K. Aldabergenova, N.K. Kelesbek, D.A. Kaykenov, M.A. Turovets
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.