Anal. Chem. 1992, 6 4 , 210-218
210
(11) Verma, S . ; Pomerantz, S. C.; Sethi, S. K.; McCloskey, J. A. Anal. Chem. 1986, 5 8 , 2898-2902. (12) Bentz. B. L.; Gale, P. J. Inf. J. Mass Specfrom. Ion Processes 1987, 78, 115-130. (13) Smith. R. D.: Loo. J. A,: Edmonds. C. G.:. Barinaa. _ . C. J.:. Udseth. H. R. Anal. ‘Chem’. 1900, 62, 882-899. (14) Karas, M.; Bahr. U. Trends Anal. Chem. 1990, 9 , 321-325. (15) Guglielmetti, G.; Andriollo, N.;Cassani, G.; Vincenti, M. Biomd. Environ. Mass Spectrom. 1989, 18, 352-354. (16) Leyden, D. E.; Cox, R. X. Analytical Applications of NMR; John Wiley & Sons: New York, 1977; Chapter 7. (17) Domon, B.; Costello, C. E. Glycoconjugate 1988. 5 , 397-409. ~I
(18) Jennings, K. R. Gas Phase Ion Chemistry; Bowers, M. T., Ed.; Academic: New York, 1979; Vol. 2.
RECEIVED for review Mav 6. 1991. AcceDted October 4. 1991. The present work was partly conducted within the contract “Programma Nazionale di Ricerca per la Chimica”, entrusted to Istituto Guido Donegani SPA-Novara by the Italian “ ~ i dell,Universit& ~ i ~ e ~della~ Ricerca ~ scientifica e Tecnologica”.
Novel Triangle Scheme for Classification of Gas Chromatographic Phases Based on Solvatochromic Linear Solvation Energy Relationships Jianjun Li, Yunke Zhang, a n d Peter W. Carr* Department of Chemistry, University of Minnesota, 207 Pleasant Street Southeast, Minneapolis, Minnesota 55455
The purpose of this work was to apply llnear solvation energy relatlonshlps (LSERs) with a new set of GC-based solute parameters (log L ”, r?T;”, and a:) to characterize and classify gas chromatographic stationary phases. The phases studied include the most representatlve phases, as identified by several chemometrlc methods, a variety of common capillary stationary phases, and a few new exceptionally bask hydrogen-bond-acceptor stationary phases. By use of a large number of test solutes, which span an extremely wide range in size, dlpolarlty, and hydrogen-bond-donor and -acceptor strength, we have been able to define the dlspersive, dipolar, and hydrogen-bond-acceptor strengths of the above phases. Solute retention on all phases Is well correlated ( r > 0.995) with quantltatlve scales of solute properties. The results of the correlational studles were substantiated by direct spectroscopic studles of the dipolarity of the stationary phases. The results indicate that there are no GC phases that are strong hydrogen-bond donors but there are many quite strong hydrogen-bond-acceptor (basic) phases. Thus it makes little sense, as has been done In the past, to use phase acidity as a classifying parameter. The results can be summarized in a novel type of phase classification “triangle” in whlch the apices represent the dispersive-cavlty, dipolar and hydrogen-bond-accepting properties of the phase, rather than the more conventional dipolar and hydrogen-bond-acceptor and -donor properties.
INTRODUCTION Due to the large number of liquids that are used as stationary phases for gas-liquid chromatography there has been a great deal of interest in developing methods that can be used to classify such materials. The most widely used of these, and perhaps that which is chemically the most appealing, is the multiple probe solute method developed by Rohrschneider (1-3) which was later extended by McReynolds ( 4 ) . This approach has been used as the basis for choosing a small set of stationary phases that should accommodate a wide variety
* To whom correspondence
should be addressed.
of samples (5). It is, however, based on Kovits retention index scheme for quantifying retention. Among others, Poole (6, 7) has criticized the McReynolds-like methods on several grounds. The primary problems are that these methods ignore interfacial adsorption effects and reference the retention of polar solutes to the retention of n-alkanes. To avoid or minimize these problems, many investigators have used polar homologue series as the basis for retention index schemes (8). Clearly, such classification schemes will depend on both the probe solutes and the reference solutes. This is a most undesirable situation. Other classification methods have been investigated (6). For example, Snyder (9, 10) proposed that solvents be characterized by the relative strength of hydrogen-bonding interactions (proton donor-acceptor) and dipolar forces. Snyder developed his approach to classify liquids for liquid chromatography, but since then it has been extended to GC (11, 12). While we feel that the basic ideas in the triangle approach are reasonable and useful for LC, this work will show that it may be more accurate to modify the scheme when it is used to classify GC stationary phases. When this method is used to classify GC stationary phases, London dispersion interactions-the most important type of interaction in gas chromatography-are suppressed. London interactions dominate retention in GC, and as shown in prior work (13, 14), the strength of dispersive interaction can vary substantially from phase to phase. This results because alkane solutes are used as the reference. In order to eliminate the inconsistencies in Snyder’s approach resulting from the n-alkanes retention index system, Kersten and Poole (12)defined the selectivity parameters as the differences of the partial molar Gibbs free energy of solution for a solute in a polar phase and a nonpolar reference phase (squalane). However, they used the same three probe solutes (nitromethane, ethanol, and 1,4-dioxane) as used by others. Further, the dispersion interaction strength of a phase was combined with dipolar and hydrogen-bonding interactions. Rutan, Carr, and Snyder (15) showed that the use of these solutes results in solvent scales which are composites of dipolarity, acidity, and basicity and thus are chemically complex. Other characterization methods include the solubility parameter approach (16, 17) and direct spectroscopic measurement of the intermolecular interactions (14, 18).
0003-2700/92/0364-0210$03.00/00 1992 American Chemical Society
ANALYTICAL CHEMISTRY, VOL. 64, NO. 2, JANUARY 15, 1992
Recently, we investigated the use of solvatochromic linear solvation energy relationships (LSERs) to characterize the solute-olvent interactions in gas chromatography (19). We used the following equation for correlating a large body of retention data on a number of stationary phases:
SP
SPo + 1 log L16 + STI+ dS2
+
+ b&
CZCX~
(1)
SP can be taken as the logarithm of a capacity factor, specific retention volume, or a partition coefficient, but not a retention index. SPo is a solute-independent constant characteristic of the column under study, LI6 is the partition coefficient of the solute from the gas phase to n-hexadecane at 298 K, T ; is a solute dipolarity/polarizability parameter, S2 is an empirical polarizability correction term, a2is the solute hydrogen-bond acidity, and p2 is the solute hydrogen-bond basicity. In this study, all the constants SPo,1, s, d, a, and b are dimensionless and empirically determined regression coefficients that characterize the phase. In eq 1 the term 1 log L16 represents contributions to changes in retention due to solute-to-solute differences in cavity formation and dispersive (London) interactions. It must be acknowledged that solute-independent dispersive and cavity energies as well as the phase ratio will show up in the SPointercept term. Abraham (20)has shown that 1 is proportional to the methylene increment for solvation of a homologous series of gaseous solutes in a given solvent and is a measure of the ability of a stationary phase to separate members of a homologous series. The term S T ~is the contribution of the dipolarity/polarizability interaction to retention. For aromatic and polyhalogenated solutes, which have differential polarizabilities Telative to aliphatic molecules, a minor correction term (dS,) is often required. Finally, aa2 and bp, represent the contributions to retention resulting from solute-to-solvent and solvent-to-solute hydrogen-bond formation. Our approach, based on eq 1, is similar in method to the recent work of Abraham and his co-workers (20). However, the results are presented within the context of Snyder’s phase classification scheme which has been very widely used. The distinctive features of the LSER approach relative to the more common phase classification methods are as follows. First, a large number of solutes, which span an extremely wide range in chemical characteristics, me used as probe solutes. Second, the solute parameters (log LI6,a;, a2,and &) are fundamental properties or known combinations of properties that have been used in correlating solute-solvent interactions in a very large number of chemical systems (21-23). Although the use of the Kamlet-Taft-Abraham solvatochromic parameters (T;, a?, #) leads to poor precision in the correlation of GC retention data (19),a newly established set of chromatographically based LSER parameters (a;“, a:, &) overcomes this problem (24). With the new parameters (T;,‘, a:, &), solute retention is well correlated (average standard deviation in log k’is 0.05, r > 0.995). The s and a coefficients that characterize the stationary phase have been substantiated by independent spectroscopic measurements of the solvent properties of the stationary phases (24). Abraham and his co-workers (20,25)also used the above LSER (eq 1) in combination with their own set of hydrogen-bond acidity and basicity parameters ($, b;). They employed a slightly different equation in which the dS2of eq 1 was replaced with a related term so as to characterize stationary phases for gas chromatography. The data sets of Laffort (25) and McReynolds’ 77-stationary-phase set (20) were studied. All phases in both data sets were characterized, and their classification of the phases was in excellent agreement with the literature. In this paper, we will test the use of eq 2, which has been shown to be better than Abraham’s in correlating solute re-
211
Table I. Representative McReynolds Phases
stationary phases
abbrev
T,“C
Apiezon L bis(2-ethoxyethyl)phthalate Carbowax 1540 Carbowax 20M castowax Citroflex A-4 diethylene glycol adipate diethylene glycol succinate diglycerol dioctyl phthalate Dow Corning 550 fluid Hallcomid M18 OL Hyperose SP 80 poly(pheny1 ether) (6 rings) SE 30 SE 52 squalane sucrose octaacetate Tergitol NPX tricresyl phosphate Zonyl E 7
ApiezonL BEEP WAX 1540 WAX2OM Castowax CFA4 DEGA DEGS DIGLY DOP DC550 HCM180L Hyperose PPE6 SE30 SE52 squalane SOA TNPX TCP ZE7
120 100 100 120 120 80 120 120 120 120 120
100 100 120 120 120 80 120 120
100 100
tention, to characterize the most commonly used GC sta-
SP = SPo+ 1 log L16 +
+ dS2 + a& + b&
(2)
tionary phases. We studied McReynolds’ 77-stationary-phase set and Poole’s new gas chromatographic data collection (26, 27) (see below). For the McReynolds data set, we used the extensive body of literature results which indicate the most representative phases and then characterized and classified them accordingly. Poole’s new data collection (26, 27) of gas-liquid partition coefficients of some 30 compounds on 24 stationary phases was also studied. To substantiate the various regressions, we correlated the s coefficient in eq 2 with independent solvatochromic measurementsof the liquid-phase properties.
EXPERIMENTAL SECTION The experimentalGC data bases used here are 21 representative phases of McReynolds’ VGdata from a total of 77 phases (B), Poole’s gas-liquid partition coefficient ( K ) data for 24 phases (26), and our capacity factor (k’)data for 8 common (film thickness 1-1.5 pm) capillary columns and 6 very basic phases (19, 24). Principal component analysis (PCA) was performed with Em*sight version 2.5 software (Seattle,Washington) run on a Zenith H-386 computer. The data were auto-scaled.
RESULTS AND DISCUSSION The largest sets of gas chromatographic retention data are those of McReynolds, who determined specific retention volumes (v“,) and retention indices (I)of 376 solutes on 77 phases (28)and retention indices of 10 solutes on 226 phages (29). Many workers (30)have classified both data sets by a variety of methods. We choose to study the 2 1 most representative phases based on Leary’s nearest neighbor results (31), Massart’s numerical taxonomic scheme (32),including the unique phases identified by Wold (33),and the most frequently used liquid phases (34). These 21 phases are listed in Table I. We choose to study the low-temperaturedata sets since retention is greater and solutesolvent interactions are stronger at low temperatures. We have measured (24)solute parameters (log L16,a;‘, a:, &) for 74 of McReynolds’ 376 solutes. The parameters are given in Table 11. In Poole’s data collection, there are gas-liquid partition coefficients on 24 stationary phases for 28 solutes (27);we only have parameters for 19 of his solutes. The phases and parameters are
212
ANALYTICAL CHEMISTRY, VOL. 64, NO. 2, JANUARY 15, 1992
Table 11. Solute Parameter Values" entry no. 1 2 3 4 5 6 7
a
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 a
compd name
log L'6
methanol ethanol 1-propanol 2-propanol butanol isobutyl alcohol sec-butanol 2-methyl-2-propanol pentanol 3-methylbutanol (isopentanol) 2-methyl-1-butanol hexanol 2-hexanol 3-hexanol 2-methyl-2-pentanol 3-methyl-3-pentanol heptanol octanol nonanol cyclopentanol cyclohexanol 2-propen-1-01 acetaldehyde propyl aldehyde butyraldehyde isobutyraldehyde valeraldehyde isovaleraldehyde hex ana1 heptanal acrolein acetone 2-butanone 2-pentanone 2-hexanone 3-hexanone 2-heptanone 2-octanone 2-nonanone cyclopentanone cyclohexanone propyl formate methyl acetate ethyl acetate propyl acetate butyl acetate pentyl acetate isopentyl acetate methyl propionate propyl butyrate isobutyl isobutyrate ethyl ether propyl ether butyl ether tetrahydrofuran butane hexane octane decane dodecane tetradecane cyclohexane I-pentene benzene toluene o-xylene m-xylene p-xylene ethylbenzene dichloromethane 1,2-dichloroethane carbon tetrachloride chloroform dioxane
0.922 1.462 2.097 1.821 2.601 2.399 2.338 2.018 3.106 2.885 3.011 3.610 3.340 3.440 3.181 3.277 4.115 4.619 5.124 3.270 3.594 1.996 1.230 1.815 2.270 2.060 2.770 2.620 3.370 3.860 2.110 1.760 2.287 2.755 3.262 3.310 3.760 4.257 4.755 3.120 3.616 2.413 1.960 2.376 2.878 3.379 3.810 3.740 2.459 3.810 3.880 2.061 2.971 4.001 2.521 1.615 2.668 3.677 4.686 5.696 6.705 2.913 2.013 2.803 3.344 3.937 3.864 3.858 3.765 1.997 2.573 2.823 2.480 2.788
All parameter values except 6: are from ref 24, 6; values are from ref 40.
*r
TL
0.35 0.29 0.30 0.21 0.30 0.30 0.24 0.19 0.32 0.28 0.27 0.33 0.27 0.21 0.16 0.19 0.35 0.36 0.38 0.40 0.37 0.33 0.36 0.35 0.34 0.30 0.35 0.31 0.36 0.38 0.34 0.38 0.39 0.40 0.39 0.34 0.41 0.43 0.44 0.58 0.59 0.34 0.30 0.30 0.31 0.33 0.35 0.30 0.32 0.29 0.23 0.03 0.03 0.04 0.27 -0.17 4.16 -0.12 -0.11 -0.09 -0.07 0.00
-0.02 0.29 0.29 0.31 0.29 0.28 0.30 0.34 0.39 0.16 0.27 0.45
62
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 1.0 1.0 1.0 1.0 0.5 0.5 0.5 0.5 0.0
E. 0.35 0.29 0.32 0.29 0.31 0.31 0.28 0.25 0.32 0.34 0.35 0.34 0.28 0.30 0.29 0.27 0.33 0.35 0.34 0.28 0.31 0.38 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.05 0.00 0.16 0.00
6; 0.46 0.52 0.52 0.51 0.52 0.48 0.50 0.53 0.52 0.51 0.51 0.51 0.51 0.51 0.53 0.53 0.51 0.51 0.51 0.33 0.33 0.51 0.37 0.37 0.37 0.37 0.37 0.37 0.38 0.39 0.37 0.52 0.48 0.48 0.48 0.48 0.48 0.48 0.48 0.57 0.56 0.44 0.47 0.49 0.48 0.48 0.48 0.48 0.45 0.48 0.48 0.40 0.30 0.29 0.61 0.00 0.00 0.00 0.00 0.00 -0.01 0.00 0.02 0.10 0.11 0.12 0.12 0.12 0.11 0.06 0.08 0.04 0.04 0.79
ANALYTICAL CHEMISTRY, VOL. 64, NO. 2, JANUARY 15, 1992
Table 111. List of GC Phases Studied by Poole" phases
abbrev
squalane SE30 OV3 OV7 ov-11 OVll OV-17 OV17 ov-22 ov22 OV-25 OV25 OV-105 OV105 OV-225 OV225 OV-275 OV275 OV-330 OV330 QF-1 QF1 Carbowax 20M WAXBOM DEGS DEGS TCEP TCEP poly(pheny1 ether) (5 rings) PPE5 tetraethylammonium 4-toluenesulfonate QEAPTS tributylammonium 4-toluenesulfonate TBAPTS tetrabutylammonium 4-toluenesulfonate QBAPTS tetrabutylammonium picrate QBAPIC tetrabutylammonium methanesulfonate QBAMES N-(2-acetamido)-2-aminoethanesulfonate QBAACES 3-[[tris(hydroxymethyl)methyl]amino]-2-hydroxy- QBATAPSO 1-propanesulfonate squalane SE-30 OV-3 OV-7
From ref 26. All data were at temperature 121.4 OC.
shown in Tables I11 and IV, respectively. The 8 capillary columns were all J & W Scientific DB-series columns (Folsom, CA); the retention data and solute parameters have been published (19). Principal Component Analysis of the Data. For McReynolds' data base, there are 11compounds in Table I1 for which retention data on one or more phases were missing; therefore, the full matrix for principal component analysis is composed of 63 compounds on 21 phases. The eigenvectors/eigenvalues from this data base are shown in Table V. Principal component analysis leads to the conclusion that 99% of the information content is contained in the first three components and that five components are needed to encompass 99.8% of the variability in the data set. This finding is in good agreement with literature results (33) that indicate the need for 3 components to reproduce McReynolds' retention index data to within 30 retention index units for 10 solutes on 226 phases (29). Principal component analysis is a powerful
method in the sense that it can identify how many components are needed to explain the information in a set of experimental data; however, the principal components per se have no physical meaning. Although there have been many attempts to connect these components with known physical properties, the results have not been satisfactory (33, 35-37). The principal component analysis of Poole's data is also shown in Table V. Five components are needed to explain 99.9% of the information in the data. Correlation Results. It should be noted that a great deal of the data used in this work were not obtained under conditions of pure partition chromatography and indeed on some phases interfacial adsorption may be the dominant retention mechanism. We believe that the quality of the fits is limited by the simultaneous existence of both retention mechanisms. The correlation results using eq 2 for the McReynolds 21 phases are shown in Table VI. We see that excellent fits (average correlation coefficient is 0.997, average standard deviation in log k'is 0.044) are obtained for all phases except for the diglycerol phase. The diglycerol phase for which we expect the greatest relative contribution of interfacial adsorption shows the poorest overall fit (average standard deviation 0.16, correlation coefficient 0.96). By comparing the 1 coefficient based on just the alkanes against the 1 coefficient based on all the solutes in the same phase, we find that these two 1 coefficients on all McReynolds' phases except diglycerol (Table VII) are the same within the 95% confidence interval. Therefore, we conclude that for most of the data sets we used, the solutes are retained by a common process or by two processes in the same relative proportion. The correlation coefficient ( r > 0.995) and the number of statistically significant solute factors are in good agreement with principal component analysis. In particular the coefficients for only three parameters (log L16, A>', and a:) are significant on almost all the phases, and the coefficients for b2 and & are small or insignificant. Thus we conclude that we are able to achieve a goodness of fit with our physically well-defined solute parameters (log L16,, ' ; a and cy:), which is virtually as good as that obtained with the same number of physically meaningless but mathematically optimum components. We plotted the three significant coefficients for all the columns (see Figure 1)and arranged the columns in order of increasing s coefficient. The s and a coefficients vary from 0 to about 3. The standard errors of the fitting coefficients are only shown when they exceed the size of the symbol used
Table IV. Solute Parameter Values" entry no.
compd
log L'6
7r;sc
82
a::
a::
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
benzene n-butylbenzene 1-octyne 1-butanol 2-methyl-2-pentanol 1-octanol phenol benzonitrile 1-nitropropane 1-nitropentane nitrobenzene pyridine aniline N-methylaniline NJV-dimethylaniline dioxane anisole dihexyl ether nonanal
2.803 4.714 3.480 2.601 3.181 4.619 3.641 4.004 2.850 3.820 4.433 3.003 3.934 4.492 4.753 2.788 3.916 5.921 4.900
0.29 0.30 0.16 0.30 0.19 0.36 0.77 0.85 0.65 0.66 0.91 0.60 0.76 0.70 0.57 0.45 0.52 0.04 0.39
1 1 0 0 0 0 1 1 0 0 1 1 1 1 1 0. 1 0 0
0.00 0.00 0.04 0.31 0.29 0.35 0.69 0.00 0.00 0.00 0.00 0.00 0.20 0.14 0.00 0.00 0.00 0.00 0.00
0.10 0.11 0.04 0.52 0.53 0.51 0.23 0.40 0.18 0.20 0.21 0.90 0.42 0.31 0.26 0.79 0.22 0.29 0.40
All parameter values except 0:' are from ref 24,
219
values are from ref 40.
214
ANALYTICAL CHEMISTRY, VOL. 64, NO. 2, JANUARY 15, 1992 .
Table V. Eigenvector/Eigenvalue Report
. ~
eigenvector
eigenvalue
'70 var
% cum var
1 2 3 4 5
21 McReynolds Phases 17.8331 84.91 2.6326 12.53 0.3408 1.62 0.1035 0.49 0.0393 0.18
84.91 97.45 99.07 99.57 99.75
1 2 3 4 5
24 Poole Phases 18.7631 78.17 4.4325 18.46 0.4137 1.72 0.2582 1.07 0.0979 0.40
78.17 96.64 98.37 99.44 99.85
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
13
I4
15
16
17
10
19 20
.
.
coefficient 1 coefficient coefficient
o
s
1
I
3
f ~
-05"""""""""""~ 0 1 2 3 1 5 6
in the plot. Clearly, the coefficients are precisely defined and are able to discriminate between the various phases. The 1 coefficient only varies from 0.2 to 0.6. However, this does not mean that s or a has more influence on retention than does 1. The range in log L16 values is much larger than the range in TIS' and a: values. Consequently, even for a small 1 the log L16 has a significant effect. There are quite a few phases that have a high a coefficient and a high s coefficient, that is, phases that are both basic and polar. There are not many
7
8
9
10
1'
12
21
22
Column No. Figure 1. I , s , and a coefficients for the 21 McReynolds phases. The column numbers are the same as in Table V I .
phases that have a high a coefficient and a lows coefficient, that is, there are few basic yet weakly polar phases. The regression results for Poole's phases are shown in Table VI11 and are plotted in Figure 2. First, we observe that very good fits (average correlation coefficient is 0.996, average
Table VI. Regression Results for the McReynolds Phases" entry no.
phase
1
squalane
2
Apiezon L
3
SE30
4
SE52
5
DC550
6
Castowax
7
DOP
8
HCM180L
9
PPE6
10
CFA4
11
TNPX
12
ZE7
13
TCP
14
BEEP
15
SOA
16
WAX2OM
17
Hyperose
18
DEGA
19
WAX1540
20
DEGS
21
DIGLY
SP"
1
S
-0.251 0.030' -0.412 0.028 -0.290 0.019 -0.329 0.019 -0.331 0.022 -0.352 0.021 -0.349 0.020 -0.103 0.021 -0.515 0.025 -0.060 0.020 -0.290 0.015 -0.582 0.037 -0.364 0.018 -0.279 0.017 -0.371 0.018 -0.358 0.019 -0.529 0.024 -0.557 0.020 -0.287 0.021 -0.562 0.029 -0.660 0.081
0.742 0.009 0.598 0.006 0.522 0.005 0.530 0.005 0.536 0.006 0.561 0.005 0.573 0.005 0.630 0.005 0.542 0.006 0.641 0.006 0.494 0.004 0.490 0.009 0.584 0.004 0.552 0.004 0.393 0.004 0.429 0.004 0.438 0.006 0.406 0.004 0.464 0.005 0.332 0.006 0.235 0.019
0.237 0.046 0.379 0.063 0.408 0.031 0.466 0.031 0.781 0.035 0.941 0.034 0.959 0.032 1.052 0.041 1.305 0.041 1.339 0.031 1.448 0.031 1.478 0.068 1.539 0.027 1.646 0.030 1.822 0.035 1.823 0.044 1.905 0.046 1.935 0.062 2.087 0.041 2.277 0.062 2.279 0.133
d
0.067 0.024 0.079 0.031
-0.055 0.023 -0.046 0.017
0.077 0.022 0.107 0.021 0.123 0.031 -0,225 0.067
b
a
0.157 0.051 0.171 0.050 0.265 0.035 0.172 0.035 0.126 0.039 0.943 0.037 0.565 0.035 1.838 0.040 0.273 0.043 1.151 0.036 1.283 0.029 4.170 0.067 1.113 0.032 1.079 0.030 1.076 0.032 1.502 0.034 2.288 0.044 1.383 0.034 1.896 0.039 1.211 0.049 2.446 0.135
f -0.147 0.062
-0.179 0.047
-0.070 0.027 0.781 0.058 0.010 0.029 0.122 0.030 4.096 0.043 0.302 0.040 0.102 0.043 -0.184 0.036 0.184 0.062
sdb
r'
nd
0.056
0.996
68
0.054
0.996
73
0.042
0.997
73
0.041
0.997
73
0.047
0.996
73
0.044
0.997
72
0.041
0.997
72
0.040
0.998
69
0.053
0.996
73
0.039
0.998
69
0.032
0.998
74
0.070
0.991
70
0.035
0.998
70
0.032
0.998
70
0.036
0.997
73
0.038
0.998
74
0.048
0.997
73
0.036
0.998
71
0.043
0.997
73
0.053
0.995
70
0.160
0.958
72
Equation 2 is the regression equation employed. *Standard deviation of the fit. Correlation coefficient. dNumber of data points. 'Standard deviation of the coefficient. 'These coefficients were found to be not significantly different from zero and were omitted in the final fit. (I
215
ANALYTICAL CHEMISTRY, VOL. 84, NO. 2, JANUARY 15, 1902
Table VII. Comparison of I Coefficients
entry no.
phase
1
squlane
2
Apiezon L
3
SE30
4
SE52
5
DC550
6
Castowax
7
DOP
8
HCM180L
9
PPE6
10
CFA4
11
TNPX
12
ZE7
13
TCP
14
BEEP
15
SOA
16
WAX2OM
17
Hyperose
18
DEGA
19
WAX 1540
20
DEGS
21
DIGLY
1,/12c
1,"
12b
0.742 0.009f 0.598 0.006 0.522 0.005 0.530 0.005 0.536 0.006 0.561 0.005 0.573 0.005 0.630 0.005 0.542 0.006 0.641 0.006 0.494 0.004 0.490 0.009 0.584 0.004 0.552 0.004 0.393 0.004 0.429 0.004 0.438 0.006 0.406 0.004 0.464 0.005 0.332 0.006 0.235 0.019
0.729
1.018 0.015r 0.0249 0.563 1.061 0.004 0.014 0.501 1.043 0.005 0.015 0.507 1.045 0.005 0.014 0.516 1.039 0.003 0.012 0.549 1.022 0.012 0.024 1.028 0.557 0.004 0.012 0.627 1.005 0.010 0.018 0.512 1.059 0.006 0.017 0.659 0.973 0.004 0.010 0.497 0.993 0.005 0.012 0.478 1.025 0.008 0.026 0.572 1.020 0.009 0.018 0.549 1.005 0.007 0.015 0.392 1.003 0.003 0.013 0.437 0.981 0.005 0.015 0.431 1.016 0.003 0.015 0.409 0.992 0.006 0.018 0.480 0.966 0.005 0.015 0.340 0.977 0.005 0.024 0.430 0.547 0.002 0.045
nld
n2e
68
5
73
7
2.0
VI
4
d
1.5
Q)
73
7
73
7
73
7
72
7
72
7
69
7
.rl
0
.rl
1.0
0.5
u 0.0
-
0--4--=-470
I.-
DE- 1
DE-1901 DE-S
73
7
69
6
74
7
70
7
70
7
70
7
73
7
74
7
73
7
71
7
73
7
70
7
72
6
DE-17 DE-1701
DE-226 DE-PI0
DE-WAX
Column type Figure 3. I ,
s,a , and d coefficients for the DB-series phases.
A
(HB acceptor)
a0.0 1.0
0.2
,l
11
0.1
(Dispersion)
6.2
0.3
0.4
0.5
0.c 0.7
A
0.8
5
0.9 1.0(Dipolar)
Classification of gas chromatographic stationary-phase selectivity (see Table IX). Flgure 4.
3 . 8 - ,
3.4~2 v) 3.0 3 2.8 -
, , , , , , , , , , , ,
,
,
,
,
,
,
,
,
/
,
,
k A
s Coefficient v a Coefficient o I Coefficient
P
-0.2 -0.4
"
0
1
2
"
0
3
4
5
6
'
7
8
I
"
9
"
10 1 1
'
3
"
'
*
"
"
1
12 13 14 15 18 17 18 19 20 21 22 23 24 25
Column No. Flgue 2. I , s,and a coefficients for the 24 Pode phases. The column
numbers are the same as in Table VIII.
standard deviation in log K is 0.051) are obtained except for OV-275which again has the biggest s coefficient and smallest 1Coefficient. Second, since these phases have very large s and a coefficients, all are clearly very polar and very basic. Third,
none of the phases are acidic. A similar plot for the DB-series columns is shown in Figure 3. Triangle Approach. From the above regression results and principal component analysis, we know there are only three fairly significant coefficients for each phase. Given that only three factors are involved, we felt it should be possible to classify or represent the properties of these stationary phases in a "triangle" plot as proposed by Snyder (9). However, our results show that the important phase properties are encoded in their 1, s, and a coefficients. This is in distinct contrast to previous work where the apices of the triangle were purported to represent the phase dipolarity, basicity, and acidity. Our results show that the apices of the triangle cannot encompass phase acidity since none of the typical GC phases is substantially acidic. Thus we choose the phase 1, s, and a values as the apices of the triangle. In order t o form an equilateral triangle the data were normalized as follows: L = 1 / ( 1 s a) (3)
+ + s = s / ( l + s + a) A = a / ( l + s + a)
(4)
(5)
The resulting triangle plot is shown in Figure 4. In this plot, we included 21 McReynolds phases, 24 Poole phases, 8
216 ~~
ANALYTICAL CHEMISTRY, VOL. 64, NO. 2, JANUARY 15, 1992 ~
~~
Table VIII. Regression Results for the Poole Phases" entry no.
column
1
squalane
2
SE-30
3
OV-3
4
OV-105
5
OV-7
6
ov-11
7
OV-25
8
OV-17
9
ov-22
10
PPE5
11
QF-1
12
OV-330
13
OV-225
14
WAX2OM
15
TBAPTS
16
QBAPIC
17
DEGS
18
QBAMES
19
QBAPTS
20
QEAPTS
21
TCEP
22
QBATAPSO
23
QBAACES
24
OV-275
SPO
1
S
-0.281 0.039' -0.220 0.035 -0.171 0.033 -0.197 0.049 -0.194 0.031 -0.235 0.034 -0.112 0.065 -0.270 0.040 -0.226 0.051 -0.238 0.063 -0.110 0.064 -0.232 0.065 -0.212 0.060 -0.063 0.066 -0.148 0.083 -0.257 0.092 -0.112 0.090 -0.323 0.097 -0.302 0.093 -0.196 0.129 0.009 0.095 -0.270 0.094 -0.275 0.112 -0.220 0.133
0.591 0.008 0.502 0.007 0.506 0.007 0.499 0.010 0.513 0.007 0.518 0.007 0.471 0.013 0.518 0.009 0.494 0.011 0.532 0.013 0.415 0.013 0.474 0.013 0.450 0.012 0.404 0.013 0.415 0.015 0.437 0.019 0.310 0.018 0.415 0.020 0.414 0.019 0.303 0.025 0.279 0.021 0.290 0.019 0.292 0.023 0.229 0.029
0.138 0.037 0.323 0.028 0.471 0.026 0.518 0.039 0.606 0.025 0.756 0.027 0.849 0.060 0.851 0.032 0.910 0.049 1.109 0.050 1.235 0.059 1.353 0.053 1.464 0.050 1.599 0.057 1.836 0.063 1.891 0.075 1.904 0.076 2.064 0.078 2.071 0.076 2.138 0.107 2.184 0.077 2.208 0.086 2.347 0.102 2.450 0.105
d
a
f 0.175 0.035 0.157 0.033 0.354 0.049 0.139 0.032 0.116 0.034 0.152 0.063 0.092 0.041
b
0.074 0.017
0.071 0.027 0.046 0.023
0.233 0.063 -0.182 0.064 1.081 0.100 0.728 0.056 1.495 0.062 2.387 0.124 1.180 0.141 1.218 0.084 3.353 0.148 3.151 0.143 2.475 0.197 1.180 0.101 2.636 0.147 3.417 0.175 1.224 0.141
-0.219 0.028 -0.060 0.025 0.049 0.027 -0.060 0.035 0.081 0.037
-0.115 0.048 -0.091 0.052 -0.172 0.088 0.125 0.072
0.072 0.041 0.099 0.048
sdb
r'
nd
0.031
0.999
18
0.027
0.999
18
0.026
0.999
18
0.038
0.997
18
0.025
0.999
18
0.026
0.999
18
0.048
0.996
17
0.032
0.998
18
0.041
0.997
18
0.049
0.996
18
0.050
0.995
18
0.049
0.996
17
0.043
0.998
19
0.046
0.998
17
0.048
0.998
13
0.069
0.994
17
0.065
0.996
18
0.072
0.995
17
0.070
0.995
17
0.085
0.991
13
0.078
0.993
18
0.070
0.995
17
0.084
0.994
17
0.110
0.989
19
Equation 2 is the regression equation employed. Standard deviation of the fit. Correlation coefficient. Number of data points. 'Standard deviation of the coefficient. 'These coefficients were found to be not significantly different from zero and were omitted in the final fit.
Table IX. Classification of Gas Chromatographic Stationary-Phase Selectivity group
phases
dipolarity basicity
Apiezon L, SE30," SE30, SE52, OV-3, DB-1, DB-5 OV-7, OV-11, OV-17, DB-17, OV-25, DC-550, PPE5, PPE6, PPEGb OV-105, DOP, DB-1301, DB-1701 I11 Castowax, CFA4 IV WAXPOM, WAX1540, WAX1540,b DB-WAX, DEGS," DEGS,b DEGS, DEGA, DB-225, OV-225, V TCEP,* TCEP, QBAPIC, OV-275, TCP, BEEP, TNPX, SOA QEAPTS, TBAPTS, QBAPTS, QBAMES, QBAACES, QBATAPSO, HYPEROSE, DIGLY VI VI1 HCM180L, TEHP,' DEDA,' B P P VI11 DMDA,' MDOA' I
I1
" These are GC phases studied by both McReynolds and Poole (see Tables VI and VIII). (17) and Abraham e t al. (25). 'These are GC phases studied in ref 24.
DB columns, and a few previously reported very basic phases (19, 24). We see that the phases form several groups. Although it is arbitrary, we can separate all phases into eight groups (see Table IX). The phases are spread over the triangle, but not many phases are located in the hydrogen-
dispersion
low high medium medium high
low low medium medium medium
high low medium low low
medium low low
high high high
low low medium
These are GC phases studied by Laffort et al.
bond-acceptor corner. This is because, as noted above, there are not many phases that are highly basic but not very polar. Our basic but not very polar phases are closest to the corner of the hydrogen-bond-acceptor apex. There are four Carbowax phases: DB-WAX, Carbowax 1540 from McReynolds, Car-
ANALYTICAL CHEMISTRY, VOL. 64, NO. 2, JANUARY 15, 1992
217
bowax 20M from Poole, and a Carbowax from Laffort. They are located in one group as expected. Two very basic amine entry no. phase =solvent S ref phases form a separate group (group VIII), so do the other four very basic but moderately dipolar phases (group VII). 1 squalane -0.04" 0.138' Poole's organic salts form a separate group (group VI). There 2 C C16 0 0.08 are four phases that are not grouped with the others, squalane 3 OV3 0.471' 0.08" 4 d MDOA 0.09 0.255 1 (from McReynolds), squalane 2 (from Poole), OV-22, and 5 d DMDA 0.558 0.14 TOPO. The difference between the two squalane phases is 6 OV7 0.606b 0.19" probably due to McReynolds' use of a small amount of a 7 OVll 0.756b 0.34" wetting agent (28). 8 d TEHP 0.34 0.889 Chemical Interpretation of the Coefficients, As re9 OV17 0.851b 0.42" quired by LSER, the coefficients defined by multiple re10 ov22 0.910' 0.43" 11 OV25 0.849' 0.48" gression are characteristic of the chemistry of the stationary 12 BBP d 1.069 0.49 phase. When the coefficient b is small or insignificant, the 13 d TOPO 1.158 0.52 phase is not acidic and cannot donate a hydrogen bond to 14 DEDA d 1.176 0.53 interact with a solute hydrogen-bond base. As expected, the 15 d Carbowax1540 1.676 0.67 d coefficient is small or insignificant because d& is only a small 16 d DEGS 0.76 1.979 polarizability correction term. The largest d coefficients are 17 TCEP 2.184" 0.79' 18 QPACHES 2.064' 0.81' for the fluorinated phases (ZE7, DB-210, and QF-1). The s d 19 TCEP 2.247 0.84 coefficient increases as the phase becomes more polar. This 20 QBACHES 2.239 0.84' means that solute dipolarity should cause a greater increase 21 QBAMOPSO 2.244' 0.88e in retention on the more dipolar phases. The correlation of 22 QBABES 2.326' 0.90e the s coefficient with direct solvatochromic evaluation of the 23 QPRACHES 2.315' 0.92e stationary phase was studied previously for only a few phases "Calculated from data a t 25 "C in ref 39 using its temperature (24). Here, we combine all the available literature data on for coefficient (see text). 'From Table VI11 in this work. C~lolvent the spectroscopically measured P* values of GC stationary hefadecane is from ref 39, its s coefficient is zero by definition. phases and compare them with the s coefficients. All the data A~~~~~~~ and s are all from ref 24. e Calculated from data at 25 OC are given in Table X and are plotted in Figure 5. Because in ref 38 using its temperature coefficient. 'Obtained from regression of data in ref 38 using eq 2. many of the literature values of the solvatochromic parameters of the solvents were obtained at 25 "C and the s coefficients were obtained at the column temperature, we used an average Table XI. Recommended Solutes for the Characterization temperature coefficient for T* of the solvent of -0.0017/K to of Phases" calculate T:,,,,~,~at the column temperature (24). Considering entry no. solute class the fact that the data are so diverse, the overall correlation is very good (see Figure 5). For all 23 phases, the correlation 1 alkylbenzene x x x results are as follows: alcohol 2 x x x x Table X. Coefficient s versus
3 4 5 6 7 8 9
?
nitroaliphatics phenol aliphatic ether pyridine aniline 2-ketone hydrogen-bond donor
T
:
~
x x X x x x x
~
~
~
~
~
x X x x x x X x x X x x x x x X x x x
~ ( ~ r f " ) = (0.01 f 0.07) + (2.49 f 0 . 1 2 ) 7 ~ ~ ~ ~(6) ,~,~ r = 0.978
sd = 0.17
n = 23
We note that the intercept of the plot in Figure 5 is very small,
as one hopes when T* of the stationary phase is zero, the phase s value should be verv small. This constitutes a strong qualitative verification of the basic LSER theory. Certainly, the a coefficients make good chemical sense. For example,
a X means the parameter values are greater than 0.2, blank means less than 0.2 or zero.
Table XII. Comparison of Regression Results of Using Different Numbers of Solutes" d
U
b
sdb
re
nd
1.794 0.023
-0.044 0.015
0.837 0.023
0.073 0.029
0.036
0.999
53
0.538 0.010 0.279 0.021
1.826 0.029 2.184 0.077
-0.071 0.019
0.962 0.032 1.180 0.101
f
0.017
1.000
9
0.078
0.993
18
0.270 0.015 0.332 0.006 0.307 0.007 5.823 0.101 5.711 0.058
2.147 0.052 2.277 0.062 2.146 0.064 -0.968 0.091 -0.698 0.072
0.038
0.999
9
phase
SPLl
l(m)
DB-225
-2.194 0.019'
0.537 0.005
TCEP
-2.169 0.042 -0.009 0.019 0.020 0.074 -0.562 0.029 -0.412 0.035 -0.097 0.068 -0.336 0.091
DEGS
log K O W P
S
0.123 0.031 0.119 0.031 0.214 0.052 0.282 0.048
1.234 0.058 1.211 0.049
0.184 0.062
0.053
0.995
70
1.119 0.041 0.374 0.081 0.270 0.058
0.159 0.057 -3.995 0.116 -3.549 0.143
0.016
1.000
9
0.132
0.996
68
0.034
1* 000
9
Equation 2 is the regression equation employed except for log Kow. Standard deviation. Correlation coefficient. Number of data points. e Standard deviation of the coefficients. /These coefficients were found to be not significantly different from zero and were omitted in the final fit. gThe following equation was employed as the regression equation: log KO,= SPo mV, + sn;' + d& + ua: bo;; also see ref 24.
+
+
218
'7
ANALYTICAL CHEMISTRY, VOL. 64, NO. 2, JANUARY 15, 1992 2.5
19.20
2.0
1.5
n
u
fi"
1.0
correlation studies serve to quantitatively characterize the stationary phase. The LSER s coefficient is in good agreement with direct spectroscopic measurement of the solvatochromic properties of the stationary phases. A novel triangle approach based on the dispersive, dipolar, and hydrogen-bonding-acceptor strengths of the stationary phase allows the classification of stationary phases. Based on only nine probe solutes, the LSER method can become a practical characterization scheme for new GC and HPLC systems. The need for a novel strong hydrogen-bond-donor phase is clearly demonstrated.
W
REFERENCES
II) (1) (2) (3) (4) (5) (6) (7)
0.5
0.0
/,
02
-0.5
* 7~ solvent Figure 5. s coefficient versus ~ same as in Table X.
i ~The, phase ~ ~ numbers ~ ~ are . the
the organic salt phases are very polar and basic therefore they should and do have both high s and a coefficients. Selection of Solutes To Characterize New Phases. Our approach can quantitatively define the coefficients of the various solutesolvent interactions. But for practical purposes we recognize that the number of compounds used is much too large to be generally useful. We know that not every compound contributes essential information. For practical application of the phase classification scheme proposed here, the following important questions arise: what is the minimum number of compounds needed to precisely define all the LSER coefficients, and what are these compounds? Previously (19), we discussed this problem from a statistical and chemical perspective; we stated that a minimum of three to four solutes per parameter should be used. If the compounds chosen can engage in only one interaction, that is, each only has a finite value for one parameter and zero for the other parameters, then 18-24 solutes will be needed for the six unknowns (the intercept and five coefficients) in eq 2. If a solute can engage in more than one type of interaction, the total number of solutes can be decreased. Mathematically, a minimum of seven solutes is needed to do multiple regressions for the six unknowns. We have determined that nine solutes suffice to precisely define the coefficients. The compounds we recommend are given in Table XI. In several cases, we do not indicate a specific compound; instead, an appropriate member of a specific homologue series should be used to ensure adequate retention (k' > 1). We obtain virtually the same coefficients for a variety of typical stationary phases by using nine solutes instead of the whole data set (see Table XII). We also obtained the same coefficients in the analysis of log KO, using its LSER equation (24).
CONCLUSIONS Solute retention in a wide variety of GC stationary phases can be correlated with an LSER equation using chromatographically determined solute parameters (log L16,P;", and a:). The LSER coefficients (1, s, and a ) obtained from the
(8) (9) (10)
(11) (12) (13) (14) (15) (16) (17) (18) (19) (20) (21) 122) ~.
Rohrschneider, L. J. Chromafogr. 1966, 2 2 , 6. Rohrschneider. L. Adv. Chromafogr. 1967, 4 , 333. Rohrschneaer, L. J. Chromafogr. 1969, 39, 383. McReynolds, W. 0.J. Chromatogr. Sci. 1970, 8 , 685. Yancey, J. A. J. Chromafogr. Sci. 1986, 24, 117. Poole, C. F.; Poole, S. K. Chem. Rev. 1989, 8 9 , 377. Poole, C. F.: Pooie, S. K.; Pomaville, R. M.; Kersten, B. R. J. High Resoluf. Chromatogr. Chromatogr. Commun. 1987, 1 0 , 670. Evans, M. 8.; Haken, J. K. J. Chromafogr. 1989, 472, 93. Snyder, L. R. J. Chromatogr. 1974, 9 2 , 223. Snyder, L. R. J. Chromafogr. Sci. 1978, 16, 223. Klee, M. S.;Kaiser, M. A.; Laughiin, K. B. J. Chromatogr. 1983, 279, 681. Kersten, B. R.; Pooie, C. F. J . Chromatogr. 1988, 452, 191. Meyer, E. F.; Awe, M. J.; Wagner, R. E. J. Chem. Eng. Data 1980, 25,371. Chong. E.; deBriceno, B.; Miller, G.; Hawkes, S. Chromafographia 1985, 2 0 , 293. Rutan, S.C.; Carr, P. W.; Cheong, W. J.; Park, J. H.; Snyder, L. R. J . Chromafogr. 1989, 463, 21. Laffort, P.; Patte, F. J. Chromafogr. 1976, 126, 625. Patte. F.; Etcheto, M.; Laffort, P. Anal. Chem. 1982, 54, 2239. Burns, W.; Hawkes, S.J. Chromafogr. Sci. 1977, 15, 185. Li. J.; Dallas, A. J.; Carr, P. W. J. Chromatogr. 1990, 517, 103. Abraham, M. H.; Whiting, G. S.; Doherty, R. M.; Shuely, W. J. J. Chromatogr. 1990, 518, 359. Kamiet, M. J.; Doherty, R. M.; Abraham, M. H.; Marcus, Y.; Taft, R. W. J. Phys. Chem. 1988, 9 2 , 5244. Abraham. M. H.: Grellier. P. L.: McGiil. R. A.: Dohertv. R. M.: Kamlet. 28, M. J.;1363. Hali, T. N.i Taft, R:W.; Carr. P. W.; Koros, W.2: Po/yier 1987; ~~~
(23) Taft, R. W.; Abboud, J.4. M.; Kamlet, M. J.; Abraham, M. H. J. Solution Chem. 1985, 14, 153. (24) Li, J.; Zhang, Y.; Dalhs, A. J.; Carr, P. W. J. Chromatogr. 1991, 550, 101.
(25) Abraham, M. H.; Whiting, G. S.;Doherty. R. M.; Shuely, W. J. J. Chem. Soc., Perkin Trans. 2 1990, 1451. (26) Kersten, B. R.; Poole, S.F.; Pooie, C. F. J. Chromatogr. 1989, 468, 235. (27) Poole, S. F.; Poole. C. F. J. Chromatogr. 1990, 500, 329. (28) McReynolds, W. 0.Gas Chromefographic Retention Data; 5th ed.: Preston Industrial, Inc.: Niles, IL, 1987. (29) McReynokls, W. 0.J. Chromafogr. Sci. 1970, 8 , 685. (30) Guiochon, G.; Guillemin. C. L. Quanfitative Gas Chromafography for Laboratory and On-line Process Control; Elsevier: Amsterdam, 1988; pp 515-526. (31) Leary. J. J.; Justice, J. B.; Tsuge, S.;Lowry, R. S.;Isenhour, T. L. J. Chromafogr. Sci. 1973, 1 1 , 201. (32) Massart, D. L.; Lenders, P.; Lauwereys, M. J. Chromafogr. Sci. 1974, 12, 617. (33) Wold, S.;Anderson, K. J. Chromafogr. 1973, 8 0 , 43. (34) Mann, J. R.; Preston, T. J. Chromatogr. Sci. 1973, 1 1 , 216. (35) Maria, P.4.; Gal, J.-F.; Franceschi, J.; Fargin, E. J. Am. Chem. SOC. 1987, 109. 483. (36) Weiner, P. H.; Dack, C. J.; Howery, D. G. J. Chromafogr. 1972, 6 9 , 249. (37) Weiner, P. H.; Howery, D. G. Anal. Chem. 1972, 44, 1189. (38) Poole, S.K.; Shew, P. H.; Pooie, C. F. Anal. Chim. Acta 1969, 218, 241. (39) Brady, J. E.; Bjorkman, D.; Herter. C. D.; Carr. P. W. Anal. Chem. 1984, 56, 278. (40) Zhang. Y.; Li, J.; Carr. P. W. Manuscript in preparation.
RECEIVED for review May 24,1991. Accepted October 9,1991. This work was supported in part by grants to the University of Minnesota from the National Science Foundation and by the donors of Petroleum Research Fund, administered by the American Chemical Society.
