Classification Analysis of Bituminous Coals Using a Combination of GC-MS and Chemometric Methods
DOI:
https://doi.org/10.31489/2959-0663/2-26-6Keywords:
chemometrics, gas chromatography, PCA, hierarchical cluster analysis, k-means, coal classification, PDDoE, Kazakhstani depositsAbstract
A comprehensive approach to the analysis of organic matter in bituminous coals from Kazakhstani deposits was developed, based on a combination of liquid extraction, gas chromatography with mass spectrometric detection (GC-MS), and chemometric data processing. A triple extraction system of dichloromethane–chloroform–tetrachloromethane (1:1:1) was proposed for sample preparation, providing representative extraction of aliphatic, aromatic and heteroatomic components without additional extract concentration. Chromatographic profiles of 120 coal extracts from four sources in Central and Northern Kazakhstan were analyzed. Optimization of the chromatographic separation conditions was carried out using probabilistic-deterministic design of experiment, which made it possible to establish robust relationships between the instrument parameters (column heating rate, carrier gas pressure) and the chromatogram characteristics. Chemometric data processing using principal component analysis (PCA), hierarchical cluster analysis (HCA), and k-means method revealed reproducible grouping of samples based on chromatographic profile similarity. Compact clusters corresponding to conventionally designated coal sources were formed in the principal component space, which is confirmed by the clustering results. The obtained results demonstrate the applicability of GC-MS and the chemometric approach for coal classification analysis and provide the foundation for the creation of a database of chromatographic fingerprints of the organic phase of coals.
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Copyright (c) 2026 Vitaliy N. Fomin, Assanali A. Aynabayev, Saule K. Aldabergenova, Dauletkhan A. Kaykenov, Milana A. Turovets
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