Use of multiplex network analysis in ESI(±) FT-ICR MS data fusion to differentiate crude oils from the same basin
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Data de publicação
2025
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0
Autores
Lucena P.G.C.
Carregosa J.C.
Eberlin M.N.
Wisniewski A.
Santos J.M.
Carregosa J.C.
Eberlin M.N.
Wisniewski A.
Santos J.M.
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© 2024 Elsevier LtdUnderstanding the molecular composition of crude oils in terms of the polar compounds present is critical for obtaining geochemical information and elucidating physical–chemical properties. This study contributed to understanding the geochemical characteristics of the Sergipe-Alagoas basin, Brazil, by analysis of ultra-high resolution Fourier transform ion cyclotron resonance mass spectrometry with electrospray ionization (ESI FT-ICR MS) data, acquired in ESI(−) and ESI(+) modes, for fourteen representative crude oils. The oils were categorized using a multiplex network (MN) method, employing composite score and Manhattan distance metrics, applied to the fused ESI(±) FT-ICR MS dataset. Data processing using the MN approach revealed novel patterns in the detected ions, when compared to conventional data assessments. The mid-level data fusion approach was optimized and the InfoMap clustering algorithm showed five distinct clusters, considering the asphaltenes + resins and polar-MeOH fractions. The MN clusters were also interpreted concerning the geochemical approach using terpane and sterane biomarkers ratios to reveal patterns based on their source organic matter and thermal maturity is well established. Expanding on this, two new ratios were explored, based on N2/N and NS/N species from analysis in ESI(+). These ratios showed significant correlations (p < 0.05) with the classical diagnostic ratios. The findings indicated that MN data processing is more effective in geochemically differentiating oils from the same basin and considered similar when compared with basic hierarchical clustering analysis (HCA), highlighting the potential of the developed data processing method.
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Assuntos Scopus
Chemometrices , Clustering analysis , FT-ICR MS , Geochemicals , Molecular compositions , Multiplex networks , Physical-chemical properties , Polar compounds , SARA fractionation , Thermal evolution