Analysis of gas chromatography-mass spectrometry library search results with edited and quantitative 13C nuclear magnetic resonance spectra

Laude, David A.; Cooper, John R.; Wilkins, Charles L.

doi:10.1021/ac00297a053

Cited by 7 publications

(5 citation statements)

References 18 publications

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“…Subjected to the NMR analysis, a total of 43 resonances with 17 methyl, 17 methylene, 7 methine, and 2 quarternary carbons were observed. A total of 14 These are listed, along with quantitative data, in Table V. GC/MS was used in an attempt to confirm the NMR results for distillate II.…”

Section: Resultsmentioning

confidence: 99%

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Identification of organic mixture components without separation: quantitative and edited carbon-13 nuclear magnetic resonance spectrometry data for analysis of petroleum distillates

Laude¹,

Wilkins²

1986

Anal. Chem.

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A new method for the analysls of unknown mlxtures whlch Incorporates unlque features of quantitative and edlted ''C nuclear magnetic resonance (NMR) spectra Is descrlbed. Chromatographic separalbn and subsequent ldentlflcatbn by match with a spectroscopic data base spectrum Is not required for quantltative analysts of mixture components. Instead, equlvalent Informath Is obtalned by creating subspectra from resonances with equlvalent peak areas wlthln a quantitative NMR spectrum. IdentHbaUon Is accompRshed by comparison of edited spectra with mu#ipric#y data derlved dlrectly from the chemical structure of potentlal components. Analysis of petroleum drstWlates wlthhr the class of low bofflng (C,-C,) hydrocarbon compounds is Considered here. A 207-component library Is created and utilized In the analysls of two fractlons for which 7 and 14 compounds are successfully identlfied.In general, analysis of organic mixtures is a two-step procedure requiring isolation of mixture components followed by identification of the pure materials. Computer-assisted methods employing chromatographic separation, followed by detection using infrared or mass spectrometers, which provide information-rich spectra for library searches of spectral data bases, are common. However, gas chromatography/mass spectrometry (GC/MS) and gas chromatography/infrared spectrometry (GC/IR), which are among the more successful implentations, suffer from a number of shortcomings. GC separation is not always possible because of sample nonvolatility or lack of sufficient chromatographic selectivity. Furthermore, present spectral libraries are incomplete and often contain spectra obtained under nonstandard conditions. In this paper an alternate approach to mixture analysis, incorporating unique features of 13C nuclear magnetic resonance (NMR) spectrometry to eliminate the need for chromatographic separation and library data bases, is described. Instead, individual components are "separated" within a quantitative 13C NMR spectrum of the mixture and identified by comparison of quantitative and multiplicity-containing 13C NMR data with a library of "predicted" NMR spectra, derived solely from chemical structure. Initial studies of the method as applied to the analysis of petroleum distillates were successful; a total of 7 and 14 components were unambiguously identified for two low-boiling fractions.The separation of components by 13C NMR is dependent upon the equivalent response achieved for all carbon nuclei under quantitative NMR conditions. Under these conditions, peak areas for all resonances within a molecule must equal some integer multiple of the area corresponding to a single nucleus. The minimum number of components in a mixture then quickly can be determined from the quantitative spectrum by counting the number of peak subsets with dissimilar peak intensities. The reliability of such a procedure is dependent upon the accuracy of peak integration and minimization of peak overlap. The contributions to integration error from both spectral and data process...

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Section: Resultsmentioning

confidence: 99%

“…Figure 3 shows the quantitative I3C NMR spectra for the distillates. Petroleum distillate I previously was characterized by GC/MS and was found to contain seven major components (14). Table IV details the information for 23 peaks including ten methyl, nine methylene, three methine, and one quaternary carbons.…”

Section: I1 I11mentioning

confidence: 99%

Identification of organic mixture components without separation: quantitative and edited carbon-13 nuclear magnetic resonance spectrometry data for analysis of petroleum distillates

Laude¹,

Wilkins²

1986

Anal. Chem.

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“…For a given library, it is difficult to determine what the best hit list should be for a specific target compound. In this regard, Laude and Wilkins have used other spectral evidence to assess the correctness of hit lists (13), while Delaney (14) has introduced a method for comparing hit lists from a search to the results of a "standard" search. Neither method, however, finds the compounds in a library that are most structurally similar to the target compound.…”

Section: Largest Cluster Diameter (Ppm) Least Number Of Linesmentioning

confidence: 99%

Application of visual spectral matching techniques to automated carbon-13 nuclear magnetic resonance library searching

Carpenter¹,

Small²

1988

Anal. Chem.

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Library searching procedures for 13C nuclear magnetic resonance spectra are described based on the Implementation of visual spectral matching techniques. A mapping algorithm Is used to match spectral lines despite differences In chemical shifts due to solvent effects and experimental artifacts. In addition, reverse search capabilities are developed to aid the Investigator In analyzing mixture spectra, as well as complex spectra not contained In the library. A discussion of the unique, Interpretive features of the search Is provided, and results are presented to Illustrate the performance of the search.

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“…In recent publications (9)(10)(11), alternative interpretation schemes for mixture analysis based upon use of 13C NMR were proposed and their applications to qualitative analysis of petroleum distillates (9), qualitative and quantitative analysis of organic wastes (10), and interpretation of gas chromatography-mass spectrometry data (11) described. All relied on interpretation of NMR data obtained from unseparated mixtures, where the wide 13C NMR spectral bandwidth (typically, over 15 000 Hz for a 7.0-T spectrometer) relative to the spectral line width (well under 1 Hz) minimizes overlap of resonances.…”

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confidence: 99%

Direct mixture analysis using carbon-proton J-resolved nuclear magnetic resonance

Wilkins¹,

Ha²,

Lee³

1988

Anal. Chem.

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Analysis of gas chromatography-mass spectrometry library search results with edited and quantitative 13C nuclear magnetic resonance spectra

Cited by 7 publications

References 18 publications

Identification of organic mixture components without separation: quantitative and edited carbon-13 nuclear magnetic resonance spectrometry data for analysis of petroleum distillates

Identification of organic mixture components without separation: quantitative and edited carbon-13 nuclear magnetic resonance spectrometry data for analysis of petroleum distillates

Application of visual spectral matching techniques to automated carbon-13 nuclear magnetic resonance library searching

Direct mixture analysis using carbon-proton J-resolved nuclear magnetic resonance

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