Electron ionization mass spectral fragmentation of derivatized 4,5- and 5,6-epoxysterols

Electron ionization (EI) mass spectral fragmentation routes of twelve 5-bromo-2,4-di-o-(m- and p-) chloro- (bromo-)benzyl-thiouracils and 6-methyluracils are investigated. The compounds studied are analyzed using gas chromatography/mass spectrometry (GC/MS). Fragmentation pathways, whose elucidation is assisted by accurate mass measurements and metastable transitions, are discussed. Correlation between the abundances of the selected fragment ions of the compounds investigated is discussed. The data obtained make grounds for distinction of structural isomers.

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Electron ionization mass spectral fragmentation study of sulfation derivatives of polychlorinated biphenyls

Chemistry Central Journal ◽

10.1186/1752-153x-3-5 ◽

2009 ◽

Vol 3 (1) ◽

Cited By ~ 10

Author(s):

Xueshu Li ◽

Larry W Robertson ◽

Hans-Joachim Lehmler

Keyword(s):

Polychlorinated Biphenyls ◽

Electron Ionization ◽

Ionization Mass ◽

Mass Spectral Fragmentation ◽

Mass Spectral ◽

Derivatives Of

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Electron ionization mass spectral fragmentation of cholestane-3β,4α,5α-triol and cholestane-3β,5α,6α/β-triol bis- and tris-trimethylsilyl derivatives

Rapid Communications in Mass Spectrometry ◽

10.1002/rcm.2005 ◽

2005 ◽

Vol 19 (14) ◽

pp. 1921-1927 ◽

Cited By ~ 5

Author(s):

J.-F. Rontani ◽

C. Aubert

Keyword(s):

Electron Ionization ◽

Ionization Mass ◽

Mass Spectral Fragmentation ◽

Mass Spectral ◽

Trimethylsilyl Derivatives

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Electron ionization mass spectrometry of aryl- and fluoroalkyl-substituted palladium(II) β-diketonates and monothio-β-diketonates

Canadian Journal of Chemistry ◽

10.1139/v94-163 ◽

1994 ◽

Vol 72 (5) ◽

pp. 1302-1311 ◽

Cited By ~ 1

Author(s):

Mark L. J. Reimer ◽

John B. Westmore ◽

Manoranjan Das

Keyword(s):

Mass Spectra ◽

Electron Ionization ◽

Electron Ionization Mass Spectrometry ◽

Ionization Mass ◽

Aryl Group ◽

Mass Spectral ◽

Transition Series ◽

Electron Ionization Mass Spectra ◽

Positive Ion ◽

Sulfur Donor

Positive ion electron ionization mass spectra are presented for palladium(II) β-diketonates and monothio-β-diketonates of the general form PdII[RC(X)CHC(O)R′]2, where R = phenyl, 4-methoxyphenyl, 2-thienyl, or 2-naphthyl; R′ = trifluoromethyl, pentafluoroethyl, or n-heptafluoropropyl; and X = O or S. The mass spectral behavior is in sharp contrast to that of metals of the first transition series. The spectra of the β-diketonates are dominated by metal-containing ions that arise by migration of the R group from the ligand (L) to palladium, but there is no evidence for fluorine-to-metal transfer. These findings are consistent with HSAB theory. The strong tendency of palladium to form bonds with unsaturated carbon also leads to remarkably abundant metal-containing ions that arise by losses of CO or aryloxy radicals from [PdRL]+• ions. In contrast, in decompositions of ions in the spectra of the monothio-β-diketonates, migration of the R group is suppressed; competition for palladium dπ electrons by the sulfur donor makes palladium a poorer aryl group acceptor.

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Predicting in silico electron ionization mass spectra using quantum chemistry

Journal of Cheminformatics ◽

10.1186/s13321-020-00470-3 ◽

2020 ◽

Vol 12 (1) ◽

Author(s):

Shunyang Wang ◽

Tobias Kind ◽

Dean J. Tantillo ◽

Oliver Fiehn

Keyword(s):

Quantum Chemistry ◽

In Silico ◽

Mass Spectra ◽

Large Scale ◽

Computation Time ◽

Molecular Size ◽

Electron Ionization ◽

Ionization Mass ◽

Compound Identification ◽

Mass Spectral

Abstract Compound identification by mass spectrometry needs reference mass spectra. While there are over 102 million compounds in PubChem, less than 300,000 curated electron ionization (EI) mass spectra are available from NIST or MoNA mass spectral databases. Here, we test quantum chemistry methods (QCEIMS) to generate in silico EI mass spectra (MS) by combining molecular dynamics (MD) with statistical methods. To test the accuracy of predictions, in silico mass spectra of 451 small molecules were generated and compared to experimental spectra from the NIST 17 mass spectral library. The compounds covered 43 chemical classes, ranging up to 358 Da. Organic oxygen compounds had a lower matching accuracy, while computation time exponentially increased with molecular size. The parameter space was probed to increase prediction accuracy including initial temperatures, the number of MD trajectories and impact excess energy (IEE). Conformational flexibility was not correlated to the accuracy of predictions. Overall, QCEIMS can predict 70 eV electron ionization spectra of chemicals from first principles. Improved methods to calculate potential energy surfaces (PES) are still needed before QCEIMS mass spectra of novel molecules can be generated at large scale.

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