Low-level fusion of FT-ICR MS data sets for the characterization of nitrogen and sulfur compounds in vacuum gas oils
Résumé
Eighteen vacuum gas oils have been analyzed by Fourier transform ion cyclotron resonance mass spectrometry considering 6 replicates in three different ionization modes (ESI(+), ESI(-) and APPI(+)) to characterize the nitrogen and sulfur compounds contained in these samples. Classical data analysis has been first performed on generated data sets using DBE (Double Bond Equivalents) versus number of carbon atoms (#C) plots in order to observe similarities and differences within the nitrogen and sulfur-containing molecular classes from samples produced by different industrial processes. In a second step, three-way arrays have been generated for each ionization mode considering three dimensions: DBE related to aromaticity, number of carbon atoms related to alkylation and sample. These three-way arrays have then be concatenated using low-level data fusion strategy to obtain a new tensor with three new modes: aromaticity, alkylation, and sample. The PARAFAC method has then been applied for the first time to this three-way data structure. A two components decomposition has allowed us to highlight unique samples with unexpected reactivity behaviors throughout hydrotreatment. The obtained loadings led to the identification of the variables responsible for this specific character. This original strategy has provided a fast visualization tool able to highlight simultaneously the impact of the three ionization modes in order to explain the differences between the samples and compare them.
Domaines
Physique [physics]
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Low-Level Fusion.pdf (1.44 Mo)
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Low-Level Fusion sup mat.pdf (469.39 Ko)
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