1213
Anal. Chem. 1986, 58, 1213-1217
Analysis of Gas Chromatography/Mass Spectrometry Library Search Results with Edited and Quantitative I3C Nuclear Magnetic Resonance Spectra David A. Laude, Jr., John R. Cooper, and Charles L. Wilkins* Department of Chemistry, University of California-Riverside, Riverside, California 92521
Quantitative and edited 13C NMR spectra are used to Improve the reiiablllty of GC/MS library search results for three mixtures of four to seven components. Combination of relatlve peak heights and carbon type for each mixture permits correlatlon wlth comparable 13C NMR data predicted for each permutatlon of the mass spectral search results. Of the 16 compounds analyzed, six incorrectly Identified by GC/MS alone are correctly ldenttfied by uslng combined MS and NMR data. This approach does not require 13C NMR ilbrary $pectra wlth the aigorlthms employed.
As with most spectrometric methods, the conventional approach to the analysis of unknown mixtures by nuclear magnetic resonance (NMR) spectrometry requires the isolation and individual analysis of each compound. Without separation, proton and proton-decoupled 13C NMR spectra of mixtures provide limited information as to the number and identities of components. Unfortunately, off-line chromatographic separation followed by NMR analysis is inefficient and error-prone. On-line analysis, as with liquid chromatography/nuclear magnetic resonance (LC/NMR), is a t present constrained by mismatch between column capacity and NMR sensitivity (1-3). As a consequence, NMR analyses of mixtures primarily have been applied to the analysis of bulk properties of samples, e.g., fuels and polymers (4-6). The method of choice for unknown mixtures, even for nonvolatile compounds that require derivatization reactions, remains gas chromatography/mass spectrometry (GC/MS). A variety of NMR pulse techniques allow editing of 13C NMR spectra to provide identification of methyl (CH,), methylene (CH,), methine (CH), and quaternary (Q) carbons (7-11). Although typically used only for structural analysis, it is possible to use the information from these editing techniques, coupled with quantitative 13CNMR spectra, to great advantage in the analysis of mixtures. In the particular application presented here, quantitative and edited NMR data are used in conjunction with GC/MS data to identify components of simple mixtures by filtering incorrect mass spectral library search results obtained from poor library or sample mass spectra, or contaminated mass spectra from unresolved chromatographic peaks. Figure 1 is a flow chart of the combined MS/NMR algorithm logic. A data matrix derived from the NMR spectra, when correlated with the predicted NMR data set from GC/MS results, significantly reduces the combinations of MS search results that correspond to the identities of the unknown mixture components. Of the 16 components in the three mixtures analyzed, six incorrectly eliminated by the MS library search are positively identified by MS/NMR. The use of GC/infrared (GC/IR) spectral data, obtained in both on-line and off-line combination with GC/MS data, proves invaluable in the confirmation of mass spectra search results, particularly in the analysis of structural isomers (12-16). Likewise, isomer analysis by NMR is also possible 0003-2700/86/0358-12 13$0 1.50/0
because spectral features are dependent upon molecular symmetry. Unlike GC/IR applications, however, the use of NMR data does not necessarily require chromatographic separation when used in combination with GC/MS. This is possible because the line widths of decoupled 13CNMR resonances are narrow relative to the frequency range of 13CNMR spectra. With line widths of less than 1.0 Hz, the resolution of all spectral elements may be achieved with some certainty for simple mixtures at high magnetic fields. For example, the 44 individual resonances of the equivalent carbons in an 11component petroleum distillate are easily resolved in a 13C NMR spectrum a t 75.4 MHz. A further advantage of the particular MS/NMR analysis presented here is that because chemical shift values are not used, 13CNMR library spectra are not required. Instead, relative peak intensity and carbon-type data derived from edited and quantitative spectra yield sufficient information for evaluation of GC/MS search results.
EXPERIMENTAL SECTION GC/MS. A Hewlett-Packard 5880A gas chromatograph coupled to a HP5970 mass selective detector (MSD) was used for all GC/MS analysis. A Hewlett-Packard Model 216 computer executing standard HP software (version 2.0) was used for data acquisition and processing. For each eluting GC peak, a mass spectrum containing the 10 most significant (mass vs. abundance) peaks was obtained and subjected to a library search of the 38790 compound EPA-NIH mass spectral library. The 10 compounds with the highest correlation-based similarity indexes from the search were then used in further analysis with NMR data. NMR. A Nicolet NTC-300 spectrometer with a standard Nicolet 5-mm 13C NMR probe was used for all experiments. For each mixture three spectra were required to obtain the necessary edited and quantitative data: (1)a gated decoupled 13Cspectrum with a recycle time in excess of 527, to ensure quantitative peak intensities, (2) an edited 13C spectrum using the distortionless enhanced polarization transfer pulse sequence (DEPT) assuming an average lJCHof 138 Hz and 6' = 3 ~ / 4to produce upright CH, and CH carbons and inverted CH, carbons, and (3) a 13C DEPT spectrum assuming an average lJCH of 138 Hz with 6' = a/2 to observe only CH carbons. The NMR spectra of mixture 1 (vide infra) are contained in Figure 2 with additional spectral parameten included in the caption. The lengthy experiment times for quantitative spectra are substantially reduced by using relaxation reagents or flow-NMR methods (17). Tables of carbon type and intensity summarize information deduced from the spectra. Relative peak areas for each resonance were obtained by using the Nicolet-developed software provided with the NTC-300 spectrometer. Measurement error was below 5% provided spectral signal-to-noiseratio was adequate and at least 8-10 data points defined each peak. Because quaternary carbons were not observed by using the DEPT sequence, they were inferred by their absence from the DEPT spectrum with 6' = 3a/4 and presence in the quantitative spectrum. CH,carbons were determined by comparison of DEPT spectra with 6' = 3 ~ / 4 and 6' = a/2. CH and CH, spectra were observed directly as explained above. It should be mentioned that several pulse sequences developed for spectral editing permit direct observation of quaternary carbons and are therefore more reliable than the 0 1986 American Chemical Society
ANALYTICAL CHEMISTRY, VOL. 58, NO. 6, MAY 1986
1214
_ _ 1 _ -
Table I. Top Three Mass Spectral Library search Results and Predicted Decoupled I3C NMR Spectra for the Four-Component Mixture -
search position
GC peak 1
heptane* 3-methylhexane 2-bromopentane
5
6 5
1 2 3
l-bromo-2,2-dimethylpropane* 1-chloro-2-methylbutane 2,2-dimethylpropanethiol
5 5 5
3 5 3
1 2
l,2-dimethylbenzene 1,4-dirnethylbenzene* 1,3-dimethylbenzene
8 8 8
4
1 2
benzoic acid, ethyl ester* 2-hydroxy-1-phenylethanone
3
P-formylbenzoic acid
1
2
3
2
3
3
4
total carbons
compd name'
predicted 13C spectrum total predicted resonances CH3 CH2
7 7
4
2 2 1, 1
2, 2, 1 1, 1, 1, 1 1, 1, 1
1
3
1 1, 1 1
1
1, 1
3
3 5
2 2 2
9
7
1
8 8
6
Q
CH
1 1
2, 2 4 2, 1, 1
2 2 2
2, 2, 1 2, 2, 1
1, 1 1, 1
5x1
1,1,1
1 1
8
"Asterisk refers to correct identity of compound. __i_
Table 11. Edited and Quantitative 13CNMR Datafor Four-Component Mixture
j ] T A B U L A T E CARBON-
f
f
resonance 1 2
3 4
5
RESULTS TO CREATE
6 7
8 9 \
10
TYPE MATRICES
11
12
I
re1 freq, PPm
165.3 134.2 132.4 130.9 129.6 128.9 128.1 60.4 47.1 32.2 32.0 29.4 27.2
AREAS WITH PREDICTED
13 14
1
15 16
22.9 20.8 14.3
17
14.1
I
N RESULT COMBINATION
E
3
CORRECT COMBINATION OF M S S E A R C H RESULTS
Figure 1. Flow chart of logic for the MS/NMR algorithm.
indirect approach used above (8, 9). Samples. Three mixtures were analyzed by both GC/MS and NMR. A four-component sample (mixture 1) contained (by waight) 30% heptane, 41 % l-bromo-2,2-dimethylpentane, 11% 1,4-dimethylbenzene, and 18% benzoic acid, ethyl ester. A five-componentphenol sample (mixture 2) contained 18% phenol, 15% m-cresol, 13% 2,6-dimethylphenol,37% 1,4-dimethylphenol, and 17% pentachlorophenol. The sample was dissolved 1:l in methanol for NMR analysis. The third sample (mixture 3), a previously uncharacterized low-boiling petroleum distillate (bp = 35-60 O C ) obtained from Aldrich, was used as an unknown.
RESULTS AND DISCUSSION A flow chart of the combined MS/NMH. algorithm logic is presented in Figure 1. Rather than utilize chemical shift information, which would require NMR library spectra for comparison, only carbon type and relative intensity data are employed. In essence, the predicted 13C NMR spectra for individual GC/MS search results are synthesized and then combined to form a predicted 13C NMR spectrum for the mixture; correlation values from a comparison of predicted and actual 13C spectra are obtained for all permutations of
carbon typea
Q Q
CH
Q
CH CH CH CH2 CH2 CH2
Q
CH2 CH3 CH2 CH3 CH, CH3
re1 intensb 92 152 100 94
185 320 191
88 226 442
201 205 670 421 144 94
420
"Carbon type determined from edited laC spectra in Figure 2b,c. Quantitative data determined from peak areas in Figure 2a with peak 3 assigned an arbitrary area of 100. search results for each GC peak. Carbon type and intensity are readily derived for each mass spectral search result by inspection of the chemical structure, although this procedure may be automated through the use of a character table data base which provides efficient digital storage of molecular structure (18). The NMR edited and quantitative data are actually used independently in the present algorithm. Following production of each predicted NMR matrix, a simple correlation of the number of quaternary, methine, methylene, and methyl carbons in the predicted and actual NMR spectra is made. Surprisingly, this procedure alone eliminated all but 13 of the 1032 combinations of mass spectral search results considered for the three mixtures analyzed. Quantitative NMR data were used to eliminate any remaining ambiguity in determining the correct GC/MS search results. To better describe the algorithm, the detailed analysis of a four-component mixture by MS/NMR is presented in Tables I-IV. Table I includes the three best matches from the mass spectral library search for the four compounds. Although and benzoic acid, ethyl heptane, l-bromo-2,2-dimethylpropane, ester are correctly identified, 1,4-dimethylbenzene is found in the second search position behind its structural isomer
ANALYTICAL CHEMISTRY, VOL. 58, NO. 6, MAY 1986 ~~
1215
~~
Table 111. Predicted 13C NMR Data from Four-Component Mixture with MS/NMR Correlation Value of 1-00 GC peak combination 1 search position:
1
2
3
4
1
1 3 1
2 2
1
CH3: 2 CH2: 2, 2, 1 CH:
Q:
2 search position:
1 1 2 2,2,1
CHB: CH,: CH:
Q:
1
3 search position:
3
CH3: 1 , l CH2: 1, 1, 1 CH:
C)
Q:
4 search position: ‘
3
Q:
100
50
1 3 1 1
CH3: 1 , l CH,: 1, 1, 1 CH:
150
3 3 1
3 3 1 1
4 2
2 2 4 2 2 2 4 2
2 2 4 2
1 1 2, 2, 1 1,l
predicted 13CNMR resonances 4 5 4 4
1
1 1 2, 2, 1 1,l
4 5 4 4
2 1 2, 2, 1 1,l
4 5 4 4
2 1 2, 2, 1 1,l
4 5 4 4
0 ppm
Flgure 2. NMR spectra of a synthetic four-component mixture with 32K data acquired over a f 8 O O O Hz spectral width: (a) quantitative spectrum with 60 scans using a gated decoupled pulse sequence with a recycle time of 100 s,(b) DEPT subspectrum assuming average JCH value of 138 Hz with $ = 3 ~ / 4 .A total of 24 transients were acquired with a recycle time of 4.0 s. Upright resonances correspond to CH3 and CH carbons, and inverted resonances are CH2 carbons. Quaternary carbons are suppressed. (c)DEPT subspectrum with conditions identical to b except 0 = a/2. Resonances correspond to CH only; CH,, CH,, and Q are suppressed.
1,2-dimethylbenzene. Also included in Table I is a compilation of the predicted 13C NMR spectra for each search result, categorized by number and relative intensity of each carbon type. Table I1 contains the 13C NMR spectral information obtained from the three spectra in Figure 2. These data indicate the presence of four quaternary, four methine, five methylene, and four methyl carbons in the mixture. Correlation of the 13C NMR data with the 81 permutations of the top three search results yielded only four combinations with identical breakdowns of carbon resonances (Table 111). Quantitative NMR data allows further reduction of the possible identities indicated by the MS search results. As seen in Table 111, the relative ratios of carbon types are not equal for all four combinations. In particular, combinations 1 and 2 are equivalent in this regard, as are 3 and 4. Table IV summarizes the attempted fit of peak ratios for each carbon type within a combination to the actual quantitative NMR data in Table 11. Although some ambiguity exists in assignment of predicted ratios to actual NMR data for individual search results, when combined, the number of potential matches is reduced. In Table IV, for example, combinations 3 and 4 are immediately eliminated because the third search result for mixture component 1,with equal intensities for two CH3and three CH2resonances, is inconsistent with the NMR data. Thus, only two possible combinations of mass spectral search results match the NMR data matrix; included is the correct combination of heptane, l-bromo-2,2-dimethylpropane, 1,4-dimethylbenzene, and ethylbenzoate. The alternate combination of search results, in which l-bromo-2,2-dimethylpropane is replaced by 2,2-dimethylpropanethiol, would produce a qualitatively identical 13C NMR spectrum for the mixture, in terms of peak intensity and carbon type.
Table IV. Fit of Four-Component Mixture Quantitative NMR Data to GC/MS Library Search Results GC search peak position CH3 CH2
CH
&“
potential matches for 13C NMR data
GC/MS Search Results 1 and 2 17/14, 10, 9 or 12/0/0* 0 1 13/9 or 12/0/11 4 2 15/0/6/2 16/0/7 or 511 or 4 2, 2, 1 1, 1 161817, 5, 314, 1
1
1
2
2, 2, 1 0
2 3
lor3 2
3 2
1 0
4
1
1
1
0
GC/MS Search Results 3 and 4 1 2 3
3 lor3 2
1, 1 1, 1, 1 0 3 1 0 2 0 4
4
2
0
1
0 1 2
cannot match
1319 or 12/0/11 15/0/6/2 16/0/7 or 514 or 1 2, 2, 1 1, 1 01817, 5, 314, 1
‘Number corresponds to relative 13Cpeak intensity within predicted spectrum; “,” separates individual resonances within carbon type; a “0” indicates no resonances within carbon type. *Number refers to resonances in Table 11; “or” is used to denote ambiguity between peaks within carbon type; “I” separates carbon types per CH?/CHI/CH/Q. Therefore, it is not possible to further resolve this particular mixture analysis by using the present MS/NMR technique. A five-component phenol mixture, mixture 2, was also analyzed by the combined MS/NMR algorithm. Based upon mass spectral results alone, only one of the five compounds, 3-methylphenol, is correctly identified by virtue of being the closest mass spectral match. The other four compounds are found in second or third search positions behind compounds with nearly identical mass spectra. An analysis similar to that detailed for mixture 1 was performed yielding a composite NMR spectrum consisting of two methyl, 12 methylene, and 10 quaternary carbon resonances. Only five permutations of GC/MS search results yield similar predicted composite spectra from the edited data. The use of quantitative NMR data permits unambiguous identification of the correct permutation of the five phenols by eliminating the four permutations containing compounds with inconsistent relative spectral peak heights.
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ANALYTICAL CHEMISTRY, VOL. 58, NO. 6, MAY 1986
Table V. Top Three GC/MS Library Search Results and Predicted Decoupled 13CNMR Spectra for Petroleum Distillate
GC peak 1
2
3
search position
3 1
pentane*
5
3
2 3
1-chloro-2-methylpropane
4
3
2-methylpentane
6
5
6 10
4
11
6
cyclopentane* methylcyclobutane ethylcyclopropane
5 5 5
1 4 4
2-chloro-3-methylbutane 2,3-dimethylbutane* 2-methylpentane
5
4 2
2-methylpentane* pentane 2-methylpropane
1 2
1 2
3 5
1 2
3 6
1 2
3 7
li
total carbons
%methylbutane* 9-isopropyldibicyclo[3.3.lInon-2-one 3,6-octadecadicynoicacid, methyl ester
1 2
3 4
compound namen
predicted NMR spectrum total predicted resonances
1 2 3
2,2-dimethylbutane* (etheny1oxy)isooctane undecane
5
4
12
12
19
19
Q 1, 1, 1
5x1
1
9
6 6
5
1
6 5
5 3
1
4
2
1
3-methylpentane* 4-methyl-1-hexane
6 7
4
l-(ethenyloxy)-2-methylpropane
6
1 1, 1 1. 1
5 5
Asterisk refers to probable compound identity.
Finally, MS/NMR analysis was also applied to a petroleum distillate fraction with a boiling point range of 35-60 "C. The 13C NMR spectra yielded a total of ten methyl, eight methylene, four methine, and one quaternary carbon resonances. Seven chromatographic peaks are resolved in the GC/MS analysis. The top three library search results for each component along with predicted NMR spectra are listed in Table V. The search results indicate the distillate contains a range of C4-Cs structural isomers. A consideration of the source of the sample suggests the search result of 2-chloro-3-methylbutane for GC peak five is suspect. Both the quantitative NMR data and GC reconstruction indicate that pentane is predominant in the mixture, comprising 60% of the sample. The mixture is thus an excellent test of the dynamic range of the method, as several components are present a t less than 5% of the pentane concentration. Again, predicted NMR spectra for compounds selected by the mass spectral search algorithm are compared with the actual edited NMR data. Perfect correlation values are obtained for the four combinations listed in Table VI. Of these, combinations 2 and 4 are quantitatively equivalent and, in fact, correspond to the identical search results, with pentane and 2-methylpentane reversing search positions for GC peaks 2 and 6. Combinations 1 and 3 are easily eliminated based upon the quantitative NMR data. As expected, 2-chloro-3methylpentane is replaced by 2-methylpentane for GC peak 6, while the other search results are confirmed. It is apparent that a two-step procedure involving first the elimination of mass spectral results based on carbon type and then quantitative analysis easily could be combined to produce a much more efficient algorithm. This would be accomplished by weighting the NMR carbon-type data with relative spectral peak areas, while weighting predicted NMR spectra from the GC/MS search results with relative chromatographic peak areas from the GC/MS reconstruction. Unfortunately, reconstructed GC peaks must be corrected for differences in instrument response that arise predominantly because of variations in ionization cross sections for different compounds.
Table VI. Predicted 13C NMR Data from Petroleum Distillate with MS/NMR Correlation Value of 1.00 GC peak
combination 1 search
1
2
3
4
5
6
7
1
1
1
1
1
2
1
position: CH,: 2, 1 2 3, 1 2, 1 2 2, 1 CH2: 1 2 , 1 1 5 2, 1 2 CH: 1 1, 1 1
Q:
2" search
1
1
2
position: CH3: 2, 1 2 3, 1 CH2: 1 2 , 1 1 5 CH: 1
4
1
1
Q:
1
2
1
2, 1 2, 1 1, 1 2 1 1
3
1
10 8
4
1 2, 1 2 1
1
10 8 4 1
1 1
8 4 1
1
3 search 1 1 1 1 3 3 position: CH,: 2, 1 2 3, 1 2, 1 3 CH,: 1 2 , l 1 5 1 , l CH: 1 1 1 4 search
10
1
1
4:
predicted 13c resonances
2
2
1
position: CH,: 2, 1 2, 1 3, 1
CH,: 1 CH:
Q:
li
1
1,l 1
1
4
5 2
1
2 2, 1 2, 1 2 1
10
8 4 1
Correct combination based upon quantitative I3C NMR data.
Typical organic molecules vary by as much as an order of magnitude in ionization efficiency (19,20). Uncorrected, this variation would not permit integration of carbon type and quantitative data. If cross sections were available for each mass spectral library component then a further weighting of the GC peak area would permit the integrated analysis. Unfortunately, these data are unlikely to become available
ANALYTICAL CHEMISTRY, VOL. 58, NO. 6, MAY 1986
Table VII. Ten Highest Correlation Values for Four-Component Mixture Using Combined Carbon-Type and Quantitative Data search position peak 2 peak 3
rank
peak 1
In
1 1 1 1
1 3 1 3
1
4
1 1 1
1
2 3
4 5 6 7 8 9 10
3 1
1 1
peak4
2 2 2 2 2 3
3
3 1 1
4
2
correlation value 0.991b 0.991 0.985 0.985 0.966 0.959 0.959 0.957 0.957 0.956
1 1 2
2 1 1 1 1 1 1
Search positions in rank 1 correspond to actual mixture components. b Correlation value is obtained from comparison of actual and predicted 13CNMR spectra based upon quantitative and carbon-type data. NMR carbon type data is weighted based upon relative peak intensities in Table 11. Mass spectral data is weighted by relative peak areas from the GC reconstruction and assumes identical cross sections for each compound. The correlation coef-
Table VIII. Comoarison of GC/MS Search Results with MS/NMR Result;
mixture four component phenol distillate total
GC/MS" MSINMR~ no. of inincomponents correct correct correct correct 4
3
1
4
0
5 7
1 6
4 1
5 7
0 0
16
10
6
16
0
Correct and incorrect identification based upon closest mass spectral library search match. If multiple search result combinations were obtained, the lowest total resulting from summation of mass spectral search positions was assumed to be correct. (I
in the near future. However, if a mixture contains similar types of compounds it is possible to perform the analysis by assuming that the cross sections are essentially equal. This assumption is valid for both the four-component and petroleum distillate mixtures analyzed here. The four-component mixture was reanalyzed integrating quantitative and carbon-type data in the MS/NMR algorithm. Comparisons of actual and predicted NMR matrices yield a correlation value that directly indicates the best combination of mass spectral search results. Table VI1 lists the 10 highest ranked combinations. As expected, the search results with the highest
1217
correlation value match the results obtained from the less efficient, but more general, approach summarized in Tables I11 and IV. For the three trial mixtures analyzed, the combined MS/ NMR algorithm is highly reliable. Table VI11 summarizes the results for both GC/MS search results alone and as part of the MS/NMR algorithm, clearly illustrating the potential value of 13C NMR in conjunction with GC/MS for mixture analysis. Several limitations, which would decrease the reliability of NMR analysis, should be mentioned. Neither peak overlap in GC separation nor NMR spectra occurred for the three trial mixtures. Either would introduce uncertainty in the data that is not considered in the rudimentary algorithms employed, thus limiting the number of components in a mixture that can be safely analyzed. However, these constraints should be overcome with the development of more elaborate algorithms to be described in future work.
LITERATURE CITED (1)
Bayer, E.; Albert, K.; Nieder, M.; Gram, E.; Wolff, G ; Rindlisbacher, M.
Anal. Chem. 1982, 54, 1747-1750. (2) Dorn, H. C. Anal. Chem. 1984, 56, 747A-758A. (3) Laude, D. A., Jr.; Wilkins, C. L. Anal. Chem 1984, 56, 2471-2475. (4) Ivtn, K. J. Pure Appl. Chem. 1983, 55, 1529-40 (5) Irvin, K. J. Anal. Chem. 1982, 54, 1896-1898. (6) Forsyth, D. A.; Hedlger, M.; Mahmoud, S.S.; Glessen, B. Anal. Chem. 1082, 54, 1896-1898. (7) Doddrell, D. M.; Pegg, D. T.; Bendall, M. R. J . Magn. Reson. 1982, 48,323-327. (8) Bendall, M. R.; Pegg, D. T . J . Magn. Reson. 1983, 53, 272-296. (9) Sorenson, 0. W. J . Magn. Reson. 1983, 55,347-354. (10) Schenker, K. V.; von Philipsborn, W. J . Magn. Reson. 1985, 6 1 , 294-305. (11) Blldsoe, H.; Danstrup, S.;Jakobsen, H. J. J. Magn. Reson. 1983, 53, 154-1 62. (12) Shafer, K. H.; Hayes, t. L.; Brasch, J. W.; Jakobsen, R. J. Anal. Chem. 1084, 56,237-240. (13) Chin, K. S.; Biemann, K.; Krishnan, K.; Hill, S . L. Anal. Chem. 1984, 56, 1610-1615. (14) Wllklns, C. L.; Giss, G. N.; White, R. L.; Brissey, G. M.; Onyiriuka, E. C. Anal. Chem. 1982, 54,2280-2264. (15) Laude, D. A., Jr.; Brissey, G. M.; Ijames, C. F.; Brown, R. S.;Wilkins, C. L. Anal. Chem. 1984, 56, 1163-1168. (16) Laude, D. A., Jr.; Johlman, C. L.; Cooper, J. R.; Wilkins, C. L. Anal. Chem. 1085, 57, 1044-1049. (17) Laude, D. A., Jr.; Lee, Robert, W. K.; Wilkins, C. L. Anal. Chem. 1085, 57, 1286-1296. (18) Computer Representation and Manipulation of Chemical Information ; WiDke, W. T.. Heller, S. R., Feldman, R. J.. Eds.; Wilev-Interscience: New York, 1974. (19) Beran, J. A,; Kevan, L. J . Phys. Chem. 1969, 7 3 , 3866-3876. (20) Lame, F. W.; Franklin, J. L.; Field, F. H. J . Am. Chem. SOC. 1957, 79,6129-6132.
RECEIVED for review November 7, 1985. Accepted January 7,1986. Support from the National Science Foundation under Grant CHE-82-08073and a Department Research Instrument Grant CHE-82-03497 are gratefully acknowledged. Partial support under a cooperative research agreement CR-811730-01 with the Environmental Monitoring Systems Laboratory, Las Vegas, of the U.S. Environmental Protection Agency is also acknowledged.
