Pushing the analytical limits: new insights into complex mixtures using mass spectra segments of constant ultrahigh resolving power

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• dc.contributor.author Palacio Lozano, Diana Catalina
• dc.contributor.author Gavard, Remy
• dc.contributor.author Arenas Diaz, Juan P.
• dc.contributor.author Thomas, Mary J.
• dc.contributor.author Stranz, David D.
• dc.contributor.author Mejía-Ospino, Enrique
• dc.contributor.author Guzman, Alexander
• dc.contributor.author Spencer, Simon E.F.
• dc.contributor.author Rossell, David
• dc.contributor.author Barrow, Mark P.
• dc.date.accessioned 2020-05-25T07:13:08Z
• dc.date.available 2020-05-25T07:13:08Z
• dc.date.issued 2019
• dc.description.abstract A new strategy has been developed for characterization of the most challenging complex mixtures to date, using a combination of custom-designed experiments and a new data pre-processing algorithm. In contrast to traditional methods, the approach enables operation of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) with constant ultrahigh resolution at hitherto inaccessible levels (approximately 3 million FWHM, independent of m/z). The approach, referred to as OCULAR, makes it possible to analyze samples that were previously too complex, even for high field FT-ICR MS instrumentation. Previous FT-ICR MS studies have typically spanned a broad mass range with decreasing resolving power (inversely proportional to m/z) or have used a single, very narrow m/z range to produce data of enhanced resolving power; both methods are of limited effectiveness for complex mixtures spanning a broad mass range, however. To illustrate the enhanced performance due to OCULAR, we show how a record number of unique molecular formulae (244 779 elemental compositions) can be assigned in a single, non-distillable petroleum fraction without the aid of chromatography or dissociation (MS/MS) experiments. The method is equally applicable to other areas of research, can be used with both high field and low field FT-ICR MS instruments to enhance their performance, and represents a step-change in the ability to analyze highly complex samples.
• dc.description.sponsorship This work was supported by a Newton Fund award (reference number 275910721), Research Agreement No. 5211770 UIS-ICP, and COLCIENCIAS (project No. FP44842-039-2015). Juan P. Arenas thanks COLCIENCIAS for the Scholarship. Rémy Gavard and Mary Thomas thank EPSRC for a PhD studentship through the EPSRC Centre for Doctoral Training in Molecular Analytical Science (grant number EP/L015307/1). David Rossell was partially supported by Ramon y Cajal Fellowship RYC-2015-18544 from Ministerio de Economia y Competitividad (Government of Spain) and by a "Ayudas Fundacion BBVA a Equipos de Investigacion Cientifica en Big Data 2017" award from the BBVA Foundation.
• dc.format.mimetype application/pdf
• dc.identifier.citation Palacio Lozano DC, Gavard R, Arenas-Diaz JP, Thomas MJ, Stranz DS, Mejía-Ospino E et al. Pushing the analytical limits: new insights into complex mixtures using mass spectra segments of constant ultrahigh resolving power. Chem Sci. 2019;10(29):6966-78. DOI: 10.1039/c9sc02903f
• dc.identifier.doi http://dx.doi.org/10.1039/c9sc02903f
• dc.identifier.issn 2041-6520
• dc.identifier.uri http://hdl.handle.net/10230/44658
• dc.language.iso eng
• dc.publisher Royal Society of Chemistry
• dc.relation.ispartof Chemical Science. 2019;10(29):6966-78
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/RYC2015-18544
• dc.rights © This article is licensed under a Creative Commons Attribution 3.0 Unported Licence (http://creativecommons.org/licenses/by/3.0/)
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/3.0/
• dc.subject.other Indicadors ambientals
• dc.subject.other Anàlisi -- Mètodes
• dc.title Pushing the analytical limits: new insights into complex mixtures using mass spectra segments of constant ultrahigh resolving power
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion