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...