Use of multiplex network analysis in ESI(±) FT-ICR MS data fusion to differentiate crude oils from the same basin

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dc.contributor.authorLucena P.G.C.
dc.contributor.authorCarregosa J.C.
dc.contributor.authorEberlin M.N.
dc.contributor.authorWisniewski A.
dc.contributor.authorSantos J.M.
dc.date.accessioned2025-04-01T06:18:00Z
dc.date.available2025-04-01T06:18:00Z
dc.date.issued2025
dc.description.abstract© 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.
dc.description.volume384
dc.identifier.doi10.1016/j.fuel.2024.133894
dc.identifier.issnNone
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/40335
dc.relation.ispartofFuel
dc.rightsAcesso Restrito
dc.subject.otherlanguageChemometrics
dc.subject.otherlanguageClustering analysis
dc.subject.otherlanguageCrude oils
dc.subject.otherlanguageGeochemistry
dc.subject.otherlanguageSARA fractionation
dc.subject.otherlanguageThermal evolution
dc.titleUse of multiplex network analysis in ESI(±) FT-ICR MS data fusion to differentiate crude oils from the same basin
dc.typeArtigo
local.scopus.citations0
local.scopus.eid2-s2.0-85211050963
local.scopus.subjectChemometrices
local.scopus.subjectClustering analysis
local.scopus.subjectFT-ICR MS
local.scopus.subjectGeochemicals
local.scopus.subjectMolecular compositions
local.scopus.subjectMultiplex networks
local.scopus.subjectPhysical-chemical properties
local.scopus.subjectPolar compounds
local.scopus.subjectSARA fractionation
local.scopus.subjectThermal evolution
local.scopus.updated2025-04-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85211050963&origin=inward
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