Chemometrics in comprehensive two-dimensional liquid chromatography: A study of the data structure and its multilinear behavior
Comprehensive multidimensional chromatographic techniques, such as GC×GC coupled to FID or MS and LC×LC coupled to UV or MS, have gained popularity in recent years. From the analytical perspective, these techniques allow obtaining higher peak capacities and resolution power, as well as adding selectivity from the second orthogonal dimension. From the chemometric point of view, these multidimensional techniques generate highly complex datasets, which present several challenges for their analysis. On the one hand, the selection of the appropriate chemometric data analysis tool requires the understanding of the underlying data structure and its multilinear behavior. On the other hand, peak resolution in complex samples is still a challenge, because of their possible overlapping in one or two chromatographic dimensions despite the increased resolution power. In this work, a comprehensive two-dimensional liquid chromatography method hyphenated simultaneously to PDA and MS detectors was employed for the analysis of a mixture of 31 pharmaceutical compounds. Chemometric evaluation of the obtained two-dimensional chromatograms focuses on two different goals. First, the assessment of the multilinear behavior of the high-dimensional data for each of the two detection modes (LC×LC-UV and LC×LC-MS) and, also, for the multiset data obtained by fusion of the data coming from both detectors. In addition, the chemometric resolution of peaks of overlapping compounds was evaluated using the multivariate curve resolution alternating least squares (MCR-ALS) method. Finally, the advantages of data fusion from UV and MS detectors were discussed, such as the increased ability for compound identification.
| Main Authors: | , , |
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| Format: | artículo biblioteca |
| Language: | English |
| Published: |
Elsevier
2020-06-15
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| Subjects: | Comprehensive, Two-dimensional liquid chromatography, Multilinear, Multivariate curve resolution, Multiset, |
| Online Access: | http://hdl.handle.net/10261/216598 |
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