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(29) Levshin, L. V.; Yuzhakov. V. I. Opt. Spektrosk, 1974, 3 4 , 503-508. (30) Zemshii, V. I.; Meshkovskii, I. K.; Sokolov, I . A. Opt. Spectrosc. ( ~ n g i r. m s i . ) 1985, 59(2), 197-199.
RECEIVED for review August 18,1986. Accepted October 27,
1986. Supported in part by the Office of Naval Research, The Upjohn Co. and the National Science Foundation through Grant CHE 83-20053. We also thank the National Science Foundation for its support of the VAX 11-780 used in this work (Grants CHE 83-09446 and CHE 84-05851).
Identification of Mixture Components in Organic Waste Materials by Carbon- 13 Nuclear Magnetic Resonance David A. Laude, Jr., a n d C h a r l e s L. Wilkins*
Department of Chemistry, University of California, Riverside, Riverside, California 92521
Carbon-13 nuclear magnetlc resonance ("C NMR) is used to determine mixture component ldentltles and relatlve concentratlons In organic waste materials wlthout prior separatlon. A quantltatlve 13C NMR spectrum provides the data used In an algorithm to extract subspectrum resonances speclflc to each mlxture component. The subspectra are then subjected to reverse searches of elther a 13C NMR slmulated spectrum llbrary or a 13C NMR chemical shlft library. The quantitative 13C NMR mlxture analysis algorithm Is appHed to seven waste solvent mlxtures procured from analytlcal and organlc laboratories. The 34 subspectra comprised of NMR resonances above the 0.5 % level In the mlxtures yleid 31 unambiguous identlflcatlons for the simulated library search and 27 unamblguous Identifications from a search of the chemical shlft library.
Characterization of bulk components in organic mixtures is essential to the management of hazardous waste materials. Ideally, any method developed for mixture analysis should permit the rapid identification and quantitative measurement of all components in the mixture, with minimal sample preparation. Although gas chromatography/mass spectrometry (GC/MS) is presently the separation/characterization method of choice for unknown mixtures, the uncertainty associated with chromatographic separation of all sample components, the nonuniform detector response of the mass spectrometer, and the need for sample volatility all impose constraints on the general application of the technique. In two recent publications ( I , 2 ) , we advocated the use of interpretation schemes for mixture analysis which incorporated 13C nuclear magnetic resonance (NMR) data. NMR is unique among the major molecular spectrometry techniques in that quantitative conditions can be achieved so that signal response is equivalent for all nuclei; coupled with a large spectral bandwidth relative to line width for 13C NMR, it becomes possible to extract the resonances specific to each compound in a mixture without prior separation. The peak intensity data from this quantitative data may be used to determine directly the relative concentrations of each compound. In addition, the well-defined relationship between a 13C NMR spectrum and chemical structure permits the implementation of elaborate computer-aided identification methods for unknowns. These properties of 13C NMR previously were exploited in procedures which utilized quantitative and multiplicity 13CNMR data to characterize petroleum distillate fractions ( I ) and to improve the reliability of GC!MS search results ( 2 ) .
In the present work quantitative 13C NMR data facilitates the isolation of pure-component subspectra from the mixture spectrum in an algorithm denoted as Q13CNMR; subsequent identification procedures include two independent reverse search algorithms: (1)comparison of subspectrum chemical shift data with a library of 13CNMR chemical shift values (3); and (2) comparison with a library of simulated 13C NMR spectra created from quantitative, multiplicity, and functional group chemical shift ranges. Selection of any identification procedure is ultimately dependent upon the compounds to be analyzed and the availability of appropriate spectral libraries and computer software. Although the preponderance of mixtures would be conveniently analyzed with algorithms employing large chemical shift library data bases, the reliability of the library search applied to unknown mixtures is suspect because of potential solvent and pH effects on chemical shift data. It is therefore of interest to contrast the search results from a chemical shift 13C NMR library with a simulated library created specifically for the mixtures to be analyzed.
EXPERIMENTAL SECTION A Nicolet NMC 300 NMR spectrometer operating at 75.497 MHz for 13C nuclei was used for all measurements. Two commercial Nicolet probes, a 5-mm fixed-frequency 13Cprobe and a 12-mm wide-band (*H to 31P)probe, were used without modification. Processing of spectral data was performed on a Nicolet 1280 computer with Nicolet-developed software. Quantitative, multiplicity, and chemical shift data extracted from the spectra were used in Fortran programs written for the Q13CNMR analysis and executed on a Digital Equipment Corp. MicroVAX 11. Implementation of the mixture analysis algorithm requires the acquisition of quantitative 13C NMR data for the tabulation of relative peak areas. The quantitative NMR measurement is achieved when the recycle time between scans exceeds five times the longest spin-lattice relaxation time (I",-) in the sample and the nuclear Overhauser effect (NOE) is quenched (4). In order to satisfy these conditions in an efficient manner, chromium triacetylacetonate(Cr(acac)dwas added to each mixture to achieve a 0.05 M concentration. A delay of between 5 and 15 s, depending upon the sample, was imposed between scans to ensure a leveling of T,and NOE for each nucleus. Reliable determination of relative peak areas from quantitative spectra is essential to the success of the algorithm. To ensure that measurement errors are minimized (less than 2%), adequate peak definition is required. These requirements were satisfied by choosing data acquisition parameters such that at least 8 to 10 points defined each peak with signal to noise (S/N) in excess of 20 to 1. Transients (32K and 64K) were acquired for spectra in which resonances encompassed a 200 ppm (k7500 Hz)region. The application of a line-broadening function (0.5-3.0 Hz) also increased the number of data points defining each peak for situations when maximum spectral resolution was not essential.
0003-2700/87/0359-0576$01.50/0G 1987 American Chemical Society
ANALYTICAL CHEMISTRY, VOL. 59, NO. 4, FEBRUARY 15, 1987
577
Table I. Simulated Library Subset of the Identified Spectra for Mixtures 1 and 6 in Table V no. of carbons
compd name tert-butyl alcohol sec-butylamine tartaric acid 1-chlorobutane methylcyclopropane bromobenzene acetophenone
3 4 5 12
CH2
2 4 2
33 13, 1 3
14
4
14, 1 4 ,
6
4
13 13
6
4 6
141
8 environment CH3-CHZ-CH-
13 >CHN
