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Anal. Chem. 1991, 63,1830-1838
should be designed such that one would get an estimate of the important physico-chemical parameters of an acid: Pm, and P K , , , ~If~ these values are known, one can predict PA-, the mobility and retention factor of the compound at different pH and micelle concentrations. Once the response surface for each solute is known, finding an optimum composition that provides the best separation would not be difficult. By using the equations described above, the retention behavior of the chlorophenols at 20 and 40 mM SDS was predicted based on the measured mobility at different pH values and at a micelle concentration (Figures 16). Work is presently underway to examine the use of these models for the prediction and optimization of MECC separation of ionizable compounds. LITERATURE CITED (1) Terabe, S.; Otsuka. K.; Ichkawa, K.; Tsuchiya A.; Ando, T. Anal. Chem. 1984, 56, 111. (2) Terabe, S.; Otsuka, K.; Ando. T. Anal. Chem. 1985, 57, 834-841. (3) Terabe, S.; Yashlma, T.: Tanaka, N.; Arakl, M. Anal. Chem. 1988, 60, 1673-1877. (4) Walbroehl, Y.; Jorgenm, J. W. Anal. Chem. 1988, 58, 479. (5) Nishl. H.; Tsumegarl, N.; Terabe, S. Anal. Chem. 1989, 61, 2434. (6) Scott, R. P. W. J . chrometog.1976, 122, 35. (7) Burton, D. E.: Sepanlak. M. J.; Maskarinec, M. P. J . chrometogr. Scl. 1986, 24, 347-351. (8) Cohen, A. S.; Terabe, S.; Smlth, J. A.; Karger, B. L. Anal. Chem. 1987, 59, 1021-1027. (9) Fujlwara, S.; Honda, S. Anal. Chem. 1987, 59, 2773-2776. ( I O ) otwks,K.; T-k, S.; Ando. T. J . CVMnretog.1965, 332,219-226. (11) Walllngford, R. A.; Ewlng, A. G. J . Chromatog. 1988. 447. 299.
(12) Strasters, J. K.; Khaledl, M. 0. Submitted for publication in Anal. Chem (13) Smith, S. C.; Khaledi, M. G. Submilted for publlcatlonin AM/. Chem. (14) Horvath, Cs.; Melander, W.; Melnar. I . Anal. Chem. 1977, 49, 142. (15) Foley, J. P.; May, W. E. Anal. Chem. 1987, 59, 102. (16) Rodgers, A. H.; Strasters, J. K.; Khaledi, M. G. Unpubilshed resub. (17) Otsuka, K.; Terabe, S.; Ando, T. J . ch*ometog. 1986, 348,39-47. (18) Jorgenson, J. W.; Lukacs, K. D. Anal. Chem. 1981, 53, 1298. (19) Leuer, H. H.; McManigill, D. Anal. Chem. 1988, 58, 166-170. (20) Terabe, S.; Otsuka, K. J . Microcd. Sep. 1969, 1 , 150-154. (21) LIu, J.; CObb, K. A,; NOvOtny. M. J . chrome tog^. 1988, 468, 55-65. (22) VanOrmen. B. B.; Liversidge,G. 0.; McIntire, 0. L.; Olefirowicz, T. M.; Ewing, A. G. J . Microcolumn Sep., In press. (23) Black, B. Fourteenth Internationel Symposium on Column Liquid Chre matography, Boston, MA, May 22, I 9 9 0 Poster 403. (24) Lambert, W. J.; Middleton, D. L. Anal. Chem. 1990. 62, 1585-1587. (25) Smith, S. C.; Strasters, J. K.; Khaledi, M. G. J . C/romatogr., in press. (26) Miller, J. C.; Miller, J. N. SfaLMcs for AnalyHcel Chemkby, 2nd 4.; Ellis Horwood/Wlley and Sons: New York, 1988. (27) Bevington, P. R. Data Reductbn and Error Ana&& for the Fbyslcal sciences; McGraw-HIII: New York, 1969. (28) Otsuka, K.; Terabe, S. J . Mlwocdumn Sep. 1989. 1 , 150-154. (29) Khaledi, M. G.; Rodgers, A. H. Anal. Chbn. Acte 1990, 239, 121-128. (30) Ong, C. P.; Ng, C. L.; ChOng, N. C.; Lee, H. K.; Ll, S. F. Y. J . chromatug. 1990, 576, 263. (31) Schoenmakers, P. J. O p t h h t k n of C/”tcgra@& S.s/ectfvlty; Elsevier: Amsterdam. 1986. (32) Foley, J. P. Anal. Chem. 1990, 62, 1302. (33) Ghowsi, K.; Foley, J. P.; Gale, R. J. Anal. Chem. 1990, 62, 2714.
.
RECW for review January 10,1991, Accepted May 29,1991. We gratefully acknowledge a research grant from the National Institutes of Health (FIRST Award, GM 38738).
Solvent Strength Model for Supercritical Fluid Chromatography on a Porous Glassy Carbon Stationary Phase Tina M. Engel and Susan V. Olesik* Department of Chemistry, The Ohio State University, 120 West 18th Auenue, Columbus, Ohio 43210
The resulk from extended studies of a porous glassy carbon (PGC) materlal for packed-column wpercrltlcal fluid chromatography (SFC) are reported. Low leveb of organic modifiers are used to change the solvent strength of the supercrltical carbon dloxlde moblle phase. A Ilnear model Is developed decrcrlblng solvent strength In terms of modifler molar volume, dlpdarlty, Lewis acidity, and Lewls baslctfy. The solvent strength In SFC PGC depends on the modifier molecular dze as well as modifier polarity. Solute retentbn Is controlled by molecular-level Interactions In the following order of importance: dlsperdon > Lewis acld-base > d i p larlty. The model was effectively used to choose a SFC moMle phaw crpproprlato for analysis of selected polar acfdlc solutes.
INTRODUCTION We recently reported the use of porous glassy carbon BGC) as a stationary phase for packed-column supercritical fluid chromatography (SFC) ( 1). PGC offers many advantages as a SFC stationary phase, including 3- to 10-pm spherical particles, 80% porosity, high surface area (150 m2/g), a spongelike structure resistant to shearing forces, strong hydrophobicity, and a uniform surface evidenced by the absence of active sites (2). The structural and chemical stabilities of 0003-2700/91/0363-1830$02.50/0
PGC allow the use of harsh SFC mobile-phase conditions. PGC also offers alternative retention characteristics to other SFC stationary phases. The retention behavior of PGC has been compared to that of common reversed-phase stationary phases (2). Reversed-phase behavior has not been demonstrated in SFC. Introduction of alternative SFC retention mechanisms through a viable nonpolar stationary phase such as PGC is therefore desirable. Simple solutes included in our earlier studies with SFC PGC showed retention consistent with an expected reversed-phase mechanism ( I ) . The absence of heteroatom sites on PGC suggests that retention may be independent of solute functionality and is instead primarily determined by interactions of the delocalized ?r electrons of the graphitic carbon with solute electron clouds. Retention on other carbon adaorbents has been successfully described in terms of the solvophobic theory (3). We expected this mechamism would allow extension of SFC to more polar solutes. But first, a detailed understanding of what controls solvent strength in SFC PGC was required to choose appropriate mobile-phase systems. This paper describes solvent strength studies of modified supercritical carbon dioxide (Cod mobile-phase systems in SFC PGC. A model is developed and used to separate polar molecules in SFC with PGC. EXPERIMENTAL SECTION Column. Studies were conducted by using a 318-pm4.d. X 20-cm-long fused silica column packed with Hypercarb PGC 0 I991 American Chemical Society
ANALYTICAL CHEMISTRY, VOL. 63,NO. 17, SEPTEMBER 1, 1991
Table I. Solvent Strength Parameters compound
carbon dioxide acetic acid acetone chloroform 1,4-dioxane benzene methyl propionate
n
RC*b
uc
p
0.01 0.05 0.72 0.79 0.66 0.63 0.67 0.66 0.81 0.391 0.00 0.531 0.50 0.666 0.11 0.777 0.13 1.00 0.16
0.194 0.252 0.274 0.291 0.304 0.327 1,1,1,3,3,3-hexafluoro-2-propanol0.363
1.12 0.08 0.44 0.00 0.00 0.00 1.51 0.00 0.00 0.00 0.00 0.00
0.48 0.00 0.37 0.10 0.42 0.00 0.00 0.12 0.00 0.00 0.00
n-pentane n-butylbenzene n-decane n-dodecane n-hexadecane a Adjusted molar volume of liquid modifier calculated by dividing the published molar volume (cma/mol)of the given modifier by the molar volume of the largest modifier studied, n-hexadecane (5). bAdjusted R* of liquid calculated by subtracting the lowest r* value (-0.08 for n-pentane) from the published R* value of the given modifier (6); value for carbon dioxide determined in-house (7). eLewis acidity parameter of liquid modifier (6);value for carbon dioxide determined in-house (7). dLewia basicity parameter of liquid modifier (6). 99 (manufactured by Shandon Scientific, Ltd., England, and supplied by Keystone Scientific, Inc., Bellefonte, PA) and equipped with a tapered restridor prepared in-house (4). The details of column preparation have been previously described (1).
Chromatographic System. An ISCO LC-2600 precision syringe pump (ISCO, Lincoln, NE)was used to pressurize and deliver the supercritical fluid mobile phase. Samples were injected with a W-series high-pressure injection valve that was fitted with a 60-nL rotor (Valco Instruments, Houston, TX). The column was heated in a Hewlett-Packard 5790A series gas chromatograph. The detector was a Sievers 350 sulfur chemiluminescence detector (SCD) (Sievers Research, Boulder, CO). Materials. Mobile phases were prepared by adding 1% (v/v) of 12 different organic modifiers to supercritical grade COz (Scott Speciality Gases). The organic modifiers used in this study are listed in Table I; formic acid was also used as a modifier. The modifiers listed in Table I are known to be miscible with liquid COz (8) and supercritical COz (9-11) at concentration levels higher than used in this study. Large nonpolar hydrocarbons similar to n-decane, n-dodecane, and n-hexadecane have solubilities of ca. 5% in supercritical COS (12). Formic acid has been used as a modifier in supercritical COz at levels exceeding 3% (13). The modifiers were purchased from Aldrich Chemical Co. and were specified at 96% or greater purity. The data were generated with standard solutions of organic solutes in acetone. The solutes studied included 2-(2-thienyl)ethanol, 1-(2-thienyl)propanone,methyl p-tolyl sulfide, benzo[b]thiophene, phenyl sulfide, phenyl disulfide, 2thiopheneacetic acid, 24hiopheneglyoxylic acid, and 3thiophenemalonic acid. These solutes were purchased from Aldrich Chemical Co. and were specified at 96% or greater purity. Data Treatment. Data were collected and compiled by using ASYST software (ASYST Software Technologies, Inc.). Multivariable linear regressions were performed by using SYSTAT software (SYSTAT, Inc.). Capacity factors were collected in triplicate, and the average value was used for model calculations; capacity factor data were typically reproducible within 1%. The Committee on Minimal Standards for Reporting Results of Regression Analyses of the International Group for Correlation Analysis in Organic Chemistry published an an-
1891
nouncement entitled “Recommendations for Reporting the Results of Correlation Analysis in Chemistry using Regreasion Analysis’ (14). This publication lists the following statistica as being necessary for a thorough evaluation of a multivariable regression analysis: (1)R, the coefficient of multiple correlation. R is equivalent in meaning to the commonly used coefficient of correlation (r) for a single-variable regression model. Its square (R2) is the coefficient of determination or the percentage of data variance accounted for by the regression equation. The coefficient of multiple correlation varies from 0 to 1, with values approaching 1indicating excellent correlation of the model with observed values (15). (2) s, the standard deviation from regression. (3) F test, a statistic used to assess the overall significance of the derived equation. Calculated F-test values are compared with published statistics tables (16);if the calculated F-test value is greater than the published value for the appropriate number of independent variables and degrees of freedom at the defined confidence level, then the derived equation is significant at the level of confidence. (4) t tests,the signifcance of each equation coefficient being evaluated by generating t-test values and comparing these values to published Statistics tables (16).If the absolute value of the calculated t test is greater than the published value for the appropriate number of degrees of freedom at the defined confidence level, then the calculated equation coefficient is significant at that level of confidence. (5) Cross-correlationcoefficients, rij, between independent variables. Correlation coefficients less than approximately 0.8 indicate that the independent variable data provide statistically different information (I 7, 18). Cross-correlation coefficients were calculated for the solvent strength parameter data given in Table I; rij values were always less than 0.7and typically lower than 0.5. These recommendations were followed in this paper. In addition, we also report the adjusted coefficient of multiple determination (RZ). Adding independent variables to a model can only increase R; therefore, in this case, R is not a good indicator of the goodness of fit of the model. However, the adjusted coefficient of determination is a better measure of model fit (15). The adjusted coefficient of multiple determination for a data set decreases when too many independent variables are introduced to the model because the increase in model fit is offset by a loss in the degrees of freedom of the model. RESULTS AND DISCUSSION Solvent Strength in Chromatography. Snyder (19) described liquidaolid adsorption chromatography by the general equation log KO = log V, + AE (1) where KO is the equilibrium distribution coefficient for the adsorption-desorption interaction of the solute with the stationary phase, V, is the adsorbent surface volume, and AE is the dimensionless net free energy of adsorption. For a solute molecule to be adsorbed, it must first displace solvent (mobile-phase) molecules. Accordingly, eq l can be expanded to = log v, + (Yd(Sd - A&) + @(so- A#) (2) log where (Yd and ( Y O are terms that describe the surface activity toward dispersive and specific (H-bond,dipole-dipole, induced dipole-dipole) interactions, respectively, S d and soare the dispersive and selective adsorption energies of the solute in a standard chromatographicsystem, respectively, 4is the area required by the solute when adsorbed on the solid adsorbent surface, and ‘d and eo are the dispersive and selective solvent strength parameters, respectively. The second term in the
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ANALYTICAL CHEMISTRY, VOL. 63, NO. 17, SEPTEMBER 1, 1991
right portion of eq 2 describes the net adsorption energy caused by dispersive interactions in the interchange of solvent molecules with solute molecules, and the third term describes the net interaction energy resulting from selective interactions involved in the interchange. If the stationary phase and solutes are kept constant while only the mobile phase is varied, then several terms in eq 2 (V,, a d , ao,A,, Sd,and So)are also constant. Equation 2 then simplifies to
(3) where k' is the capacity factor of the solute. Therefore, by varying the SFC mobilephase Characteristics with the addition of various modifiers and monitoring resultant solute capacity factors, information on dispersive and/or selective solvent strength parameters (ed and eo) can be obtained. Historically, modifier effects in SFC using silica-based stationary phases were determined in an empirical and qualitative manner. Valuable information was gained but not in a time-efficient manner. PGC is a new material for use as a SFC stationary phase that we believe will be valuable for analysis of polar solutes. We therefore chose to systematically determine the modifier characteristics controlling solvent strength in SFC PGC with the belief that this information would allow efficient optimization of SFC PGC for polar solutes. Numerous scales of solvent polarity have been developed, including the Hildegrand solubility parameter (20),the E ~ ( 3 0 ) solvatochromic scale (21), and the expanded solubility parameters developed by Karger and Snyder (22). A problem with many solvent parameters such as ET(30)is that they are all-inclusive, and the relative importance of individual molecular interactions cannot be discerned. Kamlet and Taft have reported solvatochromically determined indicators of dipolarity (T*), hydrogen-bond acidity (a), and hydrogen-bond basicity (8)(23,241. We chose to develop our model by using the Kamlet-Taft parameters because they clearly separate and scale the molecular-level interactions (dipolarity and hydrogen-bond acidity-basicity characteristics) necessary to characterize solvent strength in SFC PGC. A significant number of these parameters are available in the literature (6). When the Kamlet-Taft multicomponent solvent strength parameters are included in the SFC PGC solvent strength model, eq 3 becomes where C, D, and E are parameter coefficients. The model in eq 4 describes the solvent strength as indicated by observed solute capacity factors in terms of mobile-phase (modifier) dispersive energy, dipolarity, and hydrogen-bond aciditybasicity characteristics. Solvatochromic solvent strength parameters for the modifiers in the liquid state were used in this model. Use of these solvatochromic parameters at high-pressure, low-compressibility operating conditions is appropriate. Previous work has shown that solvatochromic parameters of fluids in this supercritical density regime (25) are approximately equal to those of fluids in the liquid state (26).
Dependence of Solvent Strength on Modifier Dispersive Energy. The principal controlling mechanism of solute adsorption on graphitic carbon is expected to be dispersive interactions between the solute and the stationary phase (19, 27,243). The dispersive energy of a molecule is proportional to the size of the molecule (29). However, in adsorption interactions, only the portion of the molecule that interacts with the solid surface is important. Therefore, the best measure of modifier dispersive energies is likely the crosssectional areas of the molecule adsorbed on the PGC surface. Tabulated values for cross-sectional areas of solvents on carbon
are available (30);however, few values exist and the precision of the reported values is low. Karger estimated a dispersive energy parameter (ad) via the Lorentz-Lorenz function and the refractive index of the pure compound (22). However, dipole-dipole and induced dipole-dipole interactions seem to be included in 8d because the reported orientation (8,) and induction (6J parameter values were zero for compounds such as benzene and toluene (22). We chose instead to use molar volume as a measure of average modifier dispersive energies. Molar volume has been shown to indicate the average dispersive energy of a molecule (29). Extensive tables of molar volumes are available (5). Molar volume will, however, represent the maximum possible dispersive interaction energy and may overestimate the extent of dispersive interaction if only a portion of the molecule adsorbs. If dispersion interactions control solvent strength in PGC SFC, then variation of solute retention with mobile-phase composition should be predicted by the following relationship: logk'=A+@Q (5) where A is a constant, B is the dispersive energy parameter coefficient, and fl is the dispersive energy parameter. The modifier dispersive energy parameters, fl, were generated by dividing the molar volumes of the modifiers used in this study by the molar volume of the largest modifier studied, n-hexadecane. This gives 0 parameter values from 0 to 1,which is in agreement in magnitude with the scales developed for the solvatochromic indicators used later in this study. All independent variables used in this study are scaled to this same range of values to permit valid comparison of model coefficients. Values of fl used in this study are listed in Table I. Since the proportion of the primary component of the mobile phase, supercritical COP,is held constant and only the modifier is changed, fl values were estimated by using only the molar volumea of the modifiers. Hence, Cl reflects changes in the mobile-phase dispersive energy due to the modifier and assumes that any contribution from C02 remains constant. In order to evaluate the effect of modifier dispersive energy on mobile-phase strength, the capacity factors of methyl p-tolyl sulfide, benzo[b]thiophene, phenyl suEde, and phenyl disulfide were monitored as a function of mobile-phase composition. Modifiers were chosen that varied significantly in size and, thus, in dispersive energy. These modifiers also have small or zero ir* values and no a and @ components. The mobile-phase systems studied were supercritical C02 containing 1% (v/v) benzene, n-pentane, n-decane, n-dodecane, or n-hexadecane at 272 atm and 50 OC. The sample chromatograms generated using the benzene-modified and nhexadecane-modified supercritical C02 mobile phases are shown in parts A and B of Figure 1, respectively. The dramatic decrease in solute capacity factors with the larger modifier supports the hypothesis that the dispersive interactions of the modifiers significantly control mobile-phase eluotropic strength. The solute capacity factor data were fit to eq 5 by using multivariable linear regression. To maintain clarity of data presentation, capacity factor data for only one solute, phenyl sulfide, are plotted in Figure 2A to illustrate the proposed solvent strength models. Model statistics for the other solutes were also generated and are given in Table 11. For the solutes and modifiers studied, dispersive interactions were acceptable as an indicator of solvent strength. The coefficient of multiple correlation ( R )values listed in Table I1 ranged from 0.94 to 0.96, indicating a direct dependence of solvent strength on modifier dispersive energy. F-test values greater than FS also support the statistical significance of the solvent strength equations above the 95% confidence level. Model coefficients for the four solutes are shown in Table 11. Values of the dispersive energy coefficient,B, range from
ANALYTICAL CHEMISTRY, VOL. 63, NO. 17, SEPTEMBER 1, 1991
+ BQ)"
Table 11. Dependence of Solvent Strength on Modifier Dispersive Energy (Model log k' = A coeff (t testy B
solute
nc
Nd
A
methyl p-tolyl sulfide benzo[b]thiophene phenyl sulfide phenyl disulfide
6 6 6 5
4 4 4 3
1.26 1.43 1.53 2.03
-1.49 (6.28) -1.43 (5.43) -1.37 (7.30) -1.62 (5.00)
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statistics
R'
R:#
sf
0.953 0.938 0.964 0.945
0.137 0.152 0.108 0.169
0.885 0.850 0.913 0.857
tssh
F'
F@J
2.776 2.776 2.776 3.182
39.46 29.43 53.29 25.02
7.71 7.71 7.71 10.13
a These data were generated by using 1%each benzene, n-pentane, n-butylbenzene, n-decane, n-dodecane, and n-hexadecane modifiers in COPat 272 atm and 50 OC. *Parameter coefficients; absolute value of the t test for specified coefficient is given in parentheses. Number of observations (modifiers); pentane modifier data not available for phenyl disulfide solute. dNumber of degrees of freedom: N = n (number of independent variables) - 1. aCoefficient of multiple correlation. 'Standard error of the estimate. #Adjusted coefficient of multiple determination. t-test value from statistical tables appropriate for the 95% confidence level. F-test value for derived equation. jF-test value from statistical tables appropriate for the 95% confidence level.
A
A Tetrahydrothiophene
I/
I"
I
Benzene Methyl p-tolyl r u l t i d e Benzo[blthiophene Phenyl dirulfide
I-
0
, -
- 1
5
4
;5
;2
0.0
k
r 0.0
0.5
Rotont/on Time (m/n)
B
f.0
f.5
Obsenvd/ogk'
B
Tetrshydrothiophene
Methyl p-tolyl sulfide Benzo[b]thiophenc Phenyl sulfide
Phenyl disulfide
-
0
f
a
2
;
0.0 0.0
i
0.5
Rotontion rim. (Wn)
Figure 1. Chromatograms demonstratlng the effect of modifler slze on solute retention: mobile phases are (A) 1 % benzene In CO, and (B) 1 % n-hexadecane In CO,.
-1.37 to -1.62. The dispersive energy coefficient was statist i d y significant above the 95% confidence level as indicated by t-test values greater than tss. In all cases, B values were negative, which indicates that the addition of larger modifiers to C02 increases the effective mobile-phase solvent strength as evidenced by observed lower solute capacity factors. However, closer evaluation of Figure 2A shows that the aromatic (benzene and n-butylbenzene) and larger aliphatic modifiers deviate slightly from the purely dispersive energy model. The incomplete description of solvent strength by a single parameter is not unexpected (31). These modifiers also have measurable R* values. A **-based independent variable was therefore added to the solvent strength model to test the effect of modifier dipolarity on mobile-phase solvent strength. Dependence of Solvent Strength on Modifier Dipolarity. The ?r* scale is an assessment of solvent dipolarity and measures the ability of the solvent to stabilize a charge or a dipole (32). If dipolarity, in addition to dispersion interactions, controls solvent strength in SFC PGC, then eq 5 can be modified to give the following relationship: log k'= A BQ CT,* (6)
+
+
where C is the dipolarity parameter. Values of
rc* used
in
7-0
7.8
Ob8@mdlo# k '
Flgurr 2. observed capacity factors vwsus estlmated capacity factom for phenyl sulfkle solute with modifiers listed in Tables I 1 and I11 (modifier group A) using two models: (A) log k' = A BQ and (B) log k ' = A BQ CT,'.
+
-+
+
this study are listed in Table I. The dipolarity parameter scale used in this study was generated by subtracting the published ?r* value of n-pentane (-0.08) from the published T* values of the other modifiers used in this study (6). This gave rc* values from 0 to 0.81, a nonnegative range that is more in agreement with other solvatochromically determined indicators used later in this study. The solute capacity factor data used for eq 5 were fit to eq 6 by using multivariable linear regression. The resultant estimated capacity factors for phenyl sulfide plotted versus the observed capacity factors are shown in Figure 2B. When compared to capacity factors estimated considering only modifier dispersive energies (Figure 2A), the estimated log k ' values shown in Figure 2B are noticeably improved, especially for the modifiers with significant dipolarity parameter values (benzene and n-butylbenzene). Model statistics for the four solutes are shown in Table 111 (modifier group A). For the solute-solvent systems studied, the linear combination of modifier dispersive energy and dipolarity was an excellent indicator of solvent strength. The observed solute capacity factor data were well fit by the model as evidenced by coefficients of multiple correlation (R) approaching 1 and F-test
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ANALYTICAL CHEMISTRY, VOL. 63, NO. 17, SEPTEMBER 1, 1991
Table 111. Dependence of Solvent Strength on Modifier Dipolarity (Model log k' = A solute
n
N
A
methyl p-tolyl sulfide benzo[b]thiophene phenyl sulfide phenyl disulfide
6 6 6 5
3 3 3 2
1.51 1.72 1.74 2.92
coeff (t test) B c Modifier Group Aa -1.71 (10.55) -1.69 (11.45) -1.55 (19.85) -2.48 (12.61)
-0.45 (2.83) -0.53 (3.67) -0.39 (5.12) -1.04 (5.17)
+ BQ + Cr*) statistics
R
S
R,1
t96
F
4%
0.987 0.989 0.996 0.996
0.082 0.075 0.040 0.055
0.958 0.964 0.988 0.985
3.182 3.182 3.182 4.303
58.39 67.32 207.9 133.3
9.55 9.55 9.55 19
Modifier Group Bb methyl p-tolyl sulfide 12 9 1.37 -1.53 (3.57) -0.36 (1.00) 0.820 0.237 0.600 2.262 9.27 4.26 phenyl sulfide 12 9 1.74 -1.53 (3.04) -0.39 (0.93) 0.770 0.279 0.500 2.262 6.50 4.26 OThese data were generated by using 1% each benzene, n-pentane n-butylbenzene, n-decane, n-dodecane, and n-hexadecane modifiers in COz at 272 atm and 50 "C;pentane modifier data not available for phenyl disulfide solute. bThesedata were generated by using 1% each of all 12 modifiers (Table I) in CO, at 272 atm and 50 "C. values exceeding the 95% confidence level. The addition of the dipolarity variable to the model improved the model fit as evidenced by increased R values over those generated by using the dispersive energy only model (Table 11). The value of the adjusted coefficient of multiple determination, R,2, also increased when the dipolarity term was added to the model. This indicates that the observed improvement in the model was real and not a result of "overfitting" from the addition of too many independent variables to the model. Estimated model coefficients for the four solutes are shown in Table I11 (modifier group A). With the exception of the dipolarity parameter coefficientfor methyl p-tolyl sulfide, all model coefficients are statistically significant at the 95% confidence level as indicated by t-test results. The values of the dispersive energy coefficient, B, are large and negative, ranging from -1.55 to -2.48; these B values again show that modifier dispersive energy directly Contributes to mobile-phase solvent strength. Values of the dipolarity parameter coefficient, C, are also negative, indicating that increased modifier dipolarity also contributes to increased mobile-phase solvent strength. The magnitudes of the respective coefficients, B and C, indicate that modifier molecular size (dispersive interactions) is the determining factor in mobile-phase solvent strength for this set of modifiers. Extension of the Dispersion/Dipolarity Model to More Polar Modifiers. The results in Table I11 (modifier group A) indicate that dispersive and dipolar interactions describe well the mobile-phase strength in SFC PGC. By using two of the test solutes, methyl p-tolyl sulfide and phenyl sulfide, the model was extended to the wider range of modifiers listed in Table I. The observed capacity factors were fit to eq 6, which considers modifier dispersion interactions and dipolmity to predict solute capacity factors. The resultant estimated capacity factors for phenyl sulfide plotted versus the observed capacity factors are shown in Figure 3A. Estimated model coefficientsand goodness of fit indicators for these two solutes are listed in Table III (modifier group B). The obvious increased scatter about the model line in Figure 3A and lower values of R show clearly that the addition of more polar modifiers such as acetic acid, acetone, and chloroform diminishes the predictive abilities of the dispersion/dipolarity model. Since most of these modifiers have significant Lewis acidity or basicity, we decided to next include the a and @ parameters in the model. Dependence of Solvent Strength on Modifier Lewis Acidity-Basicity. The a and @ solvent strength scales were developed using dyes capable of accepting or donating hydrogen bonds, respectively (32).Hydrogen bonding is a subset of a more general clasification of Lewis acid-base interactions. Therefore, a and @ were used to describe the electron donor-acceptor interactions (Lewis acidity and basicity) of a solute, respectively. If Lewis acidity and/or basicity, in ad-
A 50
r
I
Acetic a c i d
\
Chloroform
I
0,0
a0
0.5
1.0
1.5
2.0
0br.lv.d lop k '
B
Acelic acid
,.O
1,CDIoxane
0.0 0.0
0.s
1.0
f.S
2.0
Ob88m.d log k ' Figure 3. observed capacity factors versus estimated capacity factors for phenyl sulfide solute with modifiers listed In Tables 111 (modifier group B) and I V using two models: (A) log k'= A BQ 4- C r C *and (B) log k'= A BQ Cr,' E@.
+
+
+
+
dition to dispersion and dipolarity interactions, controls solvent strength in PGC SFC, then eq 6 can be modified to give the following relationship: log k'= A
+ BQ + C?r,* + D a + E&
(7)
where D and E are the Lewis acidity and Lewis basicity parameter coefficients, respectively, and a and @ are the Kamlet-Taft parameters describing Lewis acidity and basicity, respectively. Values of a and @ used in this study are listed in Table I. These parametears reflect changes in the mobile-phase Lewis acidity-basicity due t~ the modifier, and the assumption was made that any contribution from C02remains constant. The methyl ptolyl sulfide and phenyl sulfide capacity fador data generated by using all 12 modified supercritical mobile-phase systems were fit to eq 7. Again, these modifiers vary significantly in dispersive energy, dipolarity, and Lewis acidity-basicity. The addition of the a-independent variable into the model resulted in statistically insignificantLewis acid
ANALYTICAL CHEMISTRY, VOL. 63, NO. 17, SEPTEMBER 1, 1991
+ B Q + Cr* + E@)"
Table IV. Dependence of Solvent Strength on Modifier Lewis Acidity-Basicity (Model log k' = A coeff (t test) solute
n
N
A
c
B
E
R
statistics R,2 t,
s
methyl p-tolyl sulfide 12 8 1.32 -1.43 (5.60) -0.62 (2.82) 1.09 (4.20) 0.948 0.141 0.860 phenyl sulfide 12 8 1.67 -1.40 (8.61) -0.74 (5.33) 1.48 (8.95) 0.981 0.089 0.949 "Thesedata were generated by using 1% each of all 12 modifiers (Table I) in COz at 272 atm and 50 O C . Table V. Dependence of Solvent Strength on Modifier Lewis Acidity-Basicity (Model log k' = A coeff (t test)
1831
2.306 2.306
F
F,
23.49 69.07
4.07 4.07
+ Cr* + EB)'
statistics
solute
n
N
A
c
E
R
5
R,2
t,
F
F,
1-(2-thienyl)propanone
8 8 8 8
5 5 5 5
0.76 0.74 0.99 1.12
-0.16 (0.95) -0.39 (2.17) -0.58 (2.41) -0.54 (3.11)
0.80 (3.95) 1.08 (5.06) 1.55 (4.10) 1.47 (7.03)
0.870 0.916 0.926 0.954
0.110 0.116 0.154 0.113
0.661 0.775 0.763 0.874
2.571 2.571 2.571 2.571
7.82 13.06 9.07 25.36
5.79 5.79 5.79 5.79
methyl p-tolyl sulfide
benzo[b]thiophene phenyl sulfide " These data were generated by using 1 % each acetic acid, acetone, chloroform, 1,4-dioxane, benzene, methyl propionate, 1,1,1,3,3,3hexafluoro-~-~ro~anol. and n-Dentane modifiers in Co, at 272 atm and 50 O C . parameter coefficients and decreased values of the adjusted coefficient of multiple determination. This indicated that addition of the modifier Lewis acidity to the model contributed little to the model fit while decreasing the degrees of freedom of the system. The a parameter was removed from the model, and eq 7 was modified to give the following relationship: log k' = A
+ BO + CT,* + E/3
(8)
The methyl p-tolyl sulfide and phenyl sulfide capacity factor data generated by using all 12 modified supercritical mobile-phase systems were fit to eq 8. The resultant estimated capacity factors for phenyl sulfide plotted versus the observed capacity factors are shown in Figure 3B. When compared to capacity factors estimated by using the dispersion/dipolarity model (Figure 3A), the estimated log k'values shown in Figure 3B are noticeably improved. The calculated model statistics are listed in Table IV. Values of R generated by using this model were significantly improved over those generated by using the dispersive energy/dipolarity model (Table 111modifier group B). In addition, the adjusted coefficient of multiple determination also increased when the Lewis base term was added to the model. This indicates that the observed improvement in the model was real and not an artifact from overfitting the data. Estimated model coefficientsfor the two solutes are shown in Table IV. All model coefficients were statistically significant. The dispersive and dipolar interaction parameter coefficients were negative, indicating that as these two modifier characteristics increase, the mobilephase solvent strength also increases. The large positive /3 coefficients indicated that addition of a Lewis base modifier to the supercritical COz mobile phase significantlydecreased the mobilephase solvent strength. The magnitudes of the respective coefficients, B, C, and E, indicate that modifier molecular size (dispersive interactions) and Lewis basicity are the major factors in mobile-phase solvent strength for this set of modifiers and that modifier dipolarity makes a secondary but significant contribution. The model described in eq 8 successfully predicted solvent strength for a wide range of organic modifiers in supercritical COz. The study was then further expanded to more solute/modifier systems. The solutes studied included 2-(2thienyl)ethanol, 1-(2-thienyl)propanone,methyl p-tolyl sulfide, benzo[b]thiophene, and phenyl sulfide. The modifiers evaluated included acetic acid, acetone, chloroform, l,4-dioxane, benzene, methyl propionate 1,1,1,3,3,3-hexafluoro-2-propanol, and n-pentane. These modifiers vary significantly in dipolarity and Lewis acid-base characteristics but have approximately
the same molecular size. Evaluation of the molar volumes listed in Table I reveals that the molar volumes of these modifiers vary by less than 20%, and thus the contribution of changes in modifier dispersive energy to changes in mobile-phase solvent strength is small. Furthermore, use of a Lewis acid variable, a,again did not improve the model fit as evidenced by statisticallyinsignificant Lewis acid parameter coefficients and smaller adjusted Coefficients of multiple determination. Therefore, the dispersive energy and Lewis acidity terms were removed from the solvent strength model. The resultant capacity factor data were fit to the model described in the following equation: log k'= A CT,* E/3
+
+
The model coefficients and related goodness of fit statistics are given in Table V. In general, the goodness of fit of this model to these data is not as good as those previously reported. This probably reflects the small changes in solute capacity factors observed when using these solvents at these pressure and temperature conditions. However, coefficients of multiple correlation and F-test values indicate that the retention of all four illustrated solutes is satisfactorily predicted by the model. Only the dipolarity parameter coefficient for phenyl sulfide solute is significant a t the 95% confidence level as indicated by t-test values; C values for the other three solutes are significant only to the 90% confidence level. The dipolarity parameter coefficientsare negative, which is consistent with earlier observations that addition of a modifier with significant.rr* value increases the overall mobile-phase solvent strength. The Lewis base parameter coefficients, E, are statistically significant at the 95% confidence level. The Lewis base coefficient is negative, again indicating that introduction of a Lewis base modifier into the COz mobile phase increases the mobile-phase solvent strength. The magnitudes of the respective coefficients, C and E, indicate that Lewis basicity is the determining factor in mobile-phase solvent strength for this set of modifiers. In summary, the solvent strength model described in eq 7 was applied to solute capacity factor data generated in SFC PGC using supercritical COz modified with organic solvents possessing varying molar volumes, dipolarity, and Lewis acidity-basicity characteristics. Estimated model coefficients indicated that (1)use of modifiers with large molar volumes and a high degree of dipolarity increases the mobile-phase solvent strength, (2) use of modifiers with large /3 parameter values decreases the mobile-phase solvent strength, and (3) the modifier a value has little or no effect on mobile-phase solvent strength.
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ANALYTICAL CHEMISTRY, VOL. 83, NO. 17, SEPTEMBER 1, 1991
Structure of PGC. PGC is macroscopically amorphous and microscopically ordered. On the 100-lO00-8, scale, PGC appears as a randomly distributed interlacing of thin carbonaceous ribbons (33). However, at higher magnification, the ribbons have a crystalline structure similar to that of graphite (33). The molecular level surfce of these ribbons is termed the basal plane due to its structural similarity to the basal plane of graphite. These planes of hexagonally packed sp2 carbons have finite lengths, indicating that edge planes also exist in PGC (34). Therefore, PGC has at least two different types of surface sites: basal-plane sites and edge-plane sites. Mechanism of Retention. Dispersive interactions are a predominant force involved in the retention of solutes on graphitic carbon (19,27,28). Since PGC has some chemical properties similar to graphite, dispersive interactions were originally throught to be the predominant cause of retention of PGC (2). As expected, modifier molecular size played an important role in the mobile-phase solvent strength. This is demonstrated in the capacity factor data generated by using modifiers with significantly varying molar volumes. Larger modifiers competed more effectively with solutes for adsorption onto the PGC surface by virtue of their increased dispersive energies. Therefore, increasing the size of the modifier increased the solvent strength of the supercritical C02-based mobile phase. Model coefficients estimated by using these data are shown in Tables 11-IV; the statistically significant negative dispersive energy coefficients clearly show that larger modifiers increase the mobile-phase solvent strength. However, dispersive interactions alone do not fully describe the eluotropic solvent strength. The ability of the a-electron structure of graphitic carbon to interact with solutes and thus affect solute retention was postulated previously (35,36).Thus, dipolarity as described by the ** parameter was also expected to be directly related to solute retention on PGC. For example, modifiers with significant a* parameters provided higher mobile-phase solvent strengths than predicted from their molecular sizes. Modifiers capable of dipole-dipole or induced dipole-dipole interactions competed more effectively with solutes for adsorption on the PGC surface as evidenced by the statistically significant negative dipolarity coefficients listed in Tables 111-v. The effect of mobile-phase Lewis acid-base characteristics on solvent strength on PGC was not expected. However, this study and a complimentary study of liquid eluotropic solvent strength (7)both showed that Lewis acid-base interactions are important in retention on PGC. Estimated 0 coefficients listed in Tables IV and V clearly show a significant dependence of mobile phase solvent strength on modifier Lewis acid-base characteristics. In the complimentary liquid study, acid-base complexation at the carbon surface was also shown to be important to overall eluotropic strength (7). In addition, two different types of solutePGC interactions were discerned. Retention of solutes possessing a heteroatom such as phenols and quinoline was linearly dependent on mobile-phase Lewis acidity. Retention of these solutes likely involved localized Lewis acid-base interactions between solute polar moieties and the PGC surface. However, retention of solutes without heteroatoms that contain delocalized a electrons such as naphthalene was linearly dependent on mobile-phase dipolarity as indicated by a*. Retention of aromatics such as naphthalene likely involved interactions between the a-electron cloud of the aromatic molecule and that of the PGC surface. We concluded that these two different interactions also corresponded to two different types of adsorption sites associated with the PGC basal-plane and edge-planesites. The edge-plane sites are likely locations for localized Lewis acidbase interactions. The basal-plane sites would be the site of
interactions between the *-electron orbitals of the solute and the PGC surface. In terms of the model described in this paper, interactions of solutes with the PGC edge plane would be indicated by a dependence of mobile-phase solvent strength on the modifier p parameter. Alternatively, the carbon basal-plane interactions are expected to be related to the a,* parameter. For solutes with significant dipolarity and Lewis acid-base characteristics, as is the case for all the solutes in this study, adsorption would occur at both edge-plane and basal-plane sites. The relative values of the coefficients for and a,* indicate that the localized Lewis acid-base interaction was more important to retention than the delocalized a* interaction. A number of recent studies have found that the edge-plane sites are more reactive than the basal-plane sites (37). The positive B coefficients estimated in this study clearly indicate that PGC is behaving as a Lewis base. Complimentary studies also showed that PGC behaves as a Lewis base under liquid mobile-phase conditions as evidenced by the retention order of substituted phenols (7). By definition, classifying PGC as a Lewis base indicates that adsorption of solutes results from a net donation of electron density from the PGC to the solute (38).Therefore, the ability of a solute to accept charge from the PGC surface in part controls retention of that solute. Alternatively, conditions that modify the surface’s ability to donate electrons also change the overall retention characteristics of the material. The ability of local conditions to modify the Lewis acid-base characteristics of surfaces has been well-characterized with clean metal surfaces (38). For instance, it is known that introduction of electronegative elements onto clean metal surfaces causes an inductive effect, thereby making nearby metal atoms less basic or more acidic (38);alternatively, addition of basic constituents to the metal surface would raise the basicity or lower the acidity of the metal surface. This analogy can be extended to the PGC surface. Since PGC is behaving as a Lewis base,introduction of basic modifiers (high B parameter) increases the Lewis basicity of the PGC and increases the overall retentive properties of the PGC. Addition of a Lewis base modifier therefore decreases the observed eluotropic solvent strength of the mobile phase. The solutes used to measure capacity factors all contain sulfur to allow detection by the sulfur chemiluminescence detector; these solutes are generally considered to be soft Lewis bases (39). If these solutes are Lewis bases, why are they retained on the basic PGC? These solutes possess dispersive energies and dipolarity characteristics that allow adsorption to the basal-plane sites of the PGC regardless of solute acid-base characteristics. In addition, any molecule or atom can act as a Lewis acid (40-42). These Lewis basic solutes may behave as Lewis acids when expcwed to the PGC surface, allowing them to participate in localized interactionswith PGC edge-plane sites. Alternatively, the solutes are likely highly solvated by C 0 2 (a weak, hard Lewis base) and modifiers in the mobile phase, and the solvated species may behave as a Lewis acids. Regardless of the primary adsorption mechanism of the solute, the ability of the modifier to adsorb on the PGC and thus compete with the solute for adsorption sites controls the solvent strength of the mobile phase. A modifier with high dispersive energy, significant dipolarity, and Lewis acid characteristics therefore provides desirable mobile-phase characteristics when the PGC acts as a Lewis base. Polar Solutes. To extend the use of PGC to more polar solutes, the mobile phase must both dissolve the solute and act as a strong solvent in SFC PGC. The effect of solvation was demonstrated when 5-500-ng aliquots of various solutes
ANALYTICAL CHEMISTRY, VOL. 63, NO. 17, SEPTEMBER 1, 1991 A P-(P-Thlenyl)ethanol
A ,"'
I!&
.,'
1-(2-Thlenyl)propanone Methyl p-tolyl sulflde
Qc"*coo"
.
Phenyl sulfide
----. 0
2
4
8
/ L
8
ro
B
b
2
4
6
8
io
Rerenr/on T h e fmh]
Figure 4. Chromatograms demonstrating analysis of polar solutes; mobile phase is 1.5% formic acid In CO,: (A) two superimposed chromatograms collected at 50 O C and 122 atm and (B) two superimposed chromatograms collected at 50 O C and 272 atm.
were analyzed by using several of the modified C02 mobilephase systems. The peak shapes of these solutes were evaluated as a function of solute concentration and mobile-phase modifier. Relatively nonpolar solutes such as methyl p-tolyl sulfide displayed Gaussian peaks at lower concentrations and increased peak tailing at higher concentrations. Peak tailing is common for adsorption chromatography when a strong interaction exists between the stationary phase and the solute; the peak tailing behavior is observed when the number of solute molecules exceeds the available adsorption sites on the adsorbent surface. Alternatively, a polar solute such as 2thiopheneacetic acid displayed increasingly fronting peak shapes with increased concentrationwhen a nonpolar modifier such as n-pentane was used in the supercritical C02mobile phase. Peak fronting indicates that 2-thiopheneacetic acid was soluble only at low concentrations in the pentmemodified mobile phase. When a more polar modifier such as propionic acid was substituted, the 2-thiopheneacetic acid peaks no longer displayed fronting behavior, indicating increased solubility in the mobile phase. In SFC, the ideal solvent is therefore one that generally increases the polarity of the modified supercritical C02mobile phase and also has high T* and low 8 values, which lead to increased mobile-phase solvent strength. An obvious modifier choice is formic acid, which is often used as a polar modifier because it is soluble in supercritical C02 and is transparent to a flame ionization detector (13). The formic acid molecule is small and expected to have a lower dispersive energy than other modifiers used in this study. Solvatochromicparameters for formic acid have not been measured. However, formic acid is expected to have a dipolarity parameter similar to those of acetic acid and acetone (Table I), a very small B value, and a large a value exceeding that of acetic acid (>l.l). Sample chromatograms generated by using 1.5% formic acid in C02 at 272 atm and 50 OC are shown in Figure 4. Analyses of 60 ng each of several relatively nonpolar solutes and 2-thiopheneacetic acid are shown in Figure 4A. Formic
1837
acid proved to be a much stronger modifier than would predicted based on its molar size or dipolarity (T*).Capacity factors of the less polar solutes such as methyl ptolyl observed using formic acid m d i e r were comparable to those observed when larger modifiers such as benzene were added to the supercritical C02 mobile phase. In addition to increasing the overall eluotropic solvent strength of the mobile phase, formic acid modifier also allowed elution of more polar solutes than previously observed. 2-Thiopheneaceticacid was not observed or exhibited extreme peak tailing when less polar modifiers were used. When the formic acid modifier was introduced, the 24hiopheneacetic acid peak shape became equivalent to that observed for less polar solutes. In fact, Figure 4B shows that more polar previously undetected solutes, 3-thiophenemalonic acid and 2-thiopheneglyoxylic acid, were also detected with relative ease when formic acid modifier was introduced. CONCLUSIONS Solvent strength in SFC PGC is described by a linear model using modifier molar volume as a measure of dispersive interaction energy and solvatochromically determined indicators of dipolarity, Lewis acidity, and Lewis basicity. The solvatochromically determined polarity parameters independently measure different polar characteristics of the modifiers, thus allowing determination of which modifier characteristics directly effect the mobile-phase solvent strength. In SFC PGC with modified C02 mobile phases, solute retention is controlled by molecular level interactions in the following order of importance: dispersion > Lewis acid-base > dipolarity. This study using supercritical mobile phases and a complimentary study using liquid mobile phases both indicate that the PGC surface behaves as a Lewis base. Use of the model to choose a modifier with characteristics that maximize supercritical C02 mobile-phase eluotropic solvent strength allowed the analysis of more polar solutes such as dicarboxylic acids. ACKNOWLEDGMENT We thank Keystone Scientific,Inc.,for providing the PGC used in these studies and Ellen Pineda for assistance in conducting many of the chromatography experiments. Registry No. C02, 124-38-9;carbon, 1440-44-0. LITERATURE CITED (1) Engel, T. M.; Oleslk, S. V. Anal. Chem. 1990, 62, 1554-1560. (2) Knox. J. H.; Kaur, B.; Millward, G. R. J . Chrometogr. 1986, 352, 3-25. (3) Clccloll, R.; Tappa, R.; Libertl, A. Chromatogmphle 1983, 18, 330-335. (4) Oleslk, S. V.; Pekay, L. A. Chromatogaphle 1990, 29. 69-75. (5) Barton, A. F. M. CRC Hendbook of SoJubWHy Pammefers and 0thsr cohesion Factcxs; CRC Press, Inc.: Boca Raton, FL, 1983. (6) Kamlet, M. J.; Abboud, J. L. M.; Abraham, M. H.; Tan, R. W. J . Org. Chem. 1983, 48, 2877-2887. (7) Cui, Y.; Oleslk, S. V. A M I . Chem. 1991, 63. 1812-1819. (8) Francis, A. W. J . Am. C b m . Soc.1954, 58, 1099-1114. (9) Schmitt. W. J.; Reed, R. C. F/UM phase EquNlb. 1988, 32, 77-99. (10) Lemert, R. M.; Johnston, K. P. F/uid Phase €qu///b. 1989, 45. 265-286. (11) Leyendecker, D.;Leyendecker, D.; Schmk, F. P.; Lorenschat, 6.; Klesper. E. J . Chrometogr. 1987, 398, 105-123. (12) SwaM. I.; Nickel, D.; Schneider, G. M. Fluid phase €qu/l. 1985. 21, 95-112. (13) Pacholec, F.; Boyer, D. S.; Houck, R. K.; Rosselll. A. C. I n Modem Scrpercriricel F/uU Chromatography; White, C. M., Ed.; Dr. Alfred HiitMg Verlag: Heideiberg, 1988. (14) Charton, M.; Clementl. S.; Ehrenson, S.; Exner. 0.;Shorter. J.; Wold, S. Ouant. Sbvct. Act. Relet. 1985. 4 , 29. (15) Neter, J.; Wasserman, W.; Kutner, M. Appmed SteffstlcelMOdels, 2nd ed.; Richard E. Irwin, Inc.: Homewood, IL, 1985. (16) Massart, D. L.; Vandeglnste, B. 0.M.; Demlng. S. N.; Mlchotte, Y.; Kaufman. L. I n C h e " e M c s : a Textbook; Vandeglnste, B. 0. M.. Kaufman, L., Eds.; Eiaevler: Amsterdam, 1988, (17) Kaliaran, R. In QuanUtaffveSbvctwe-Chromat~aph/cR e f " Relatbn&lps; Wlnefordner, J. D., Ed.; John Wiley and Sons: New York, 1967. (18) Kaliszan, R.; Osmlalowski, K.; Tomellini, S. A.; Hsu, S.; Fario, S. D.; brtwlck. R. A. J . ChrOmatw. 1986, 352, 141-155. (19) Snyder, L. R. J . Chromatogr. 1968. 36,455-475.
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Anal. Chem. 1991, 63, 7830-7843
(20) HHdObrand, J. H.; Scott, R. L. The SokMty of ;Dover Pubiicatkns, Inc.: New York, 1964. (21) Rekhardt, C. Angsw. Q”.,Int. Ed. Et@. 1965, 4 , 29-40. (22) Karger, E. L.; Snyder, L. R.; Eon. C. J . Crwomrrtcgr. 1978, 725. 71-88. . . (23) Park, J. H.; Can, P. W. J . chrometop. 1989, 465, 123-136. (24) Rutan, S. C.; Can,P. W.; Cheong, W. J.; Park, J. H.; Snyder, L. R. J . ChrcwnetogV. 1989. 483. 21-37. (25) Yonker, C. R.; Smith, R. D. J . phvs. Chem. 1988, 92, 2374-2378. (26) Hyatt, J. A. J . Ufg. Chem. 1984. 49, 5097-5101. (27) Dl Corcle, A.: L W , A. In Advances /n Crwomrrtogephy;Qiddings, J. C., (Lushka, E., Cazes, J., Brown, P. R., Eds.; Marcel Dekker, Inc.: M W York, 1976; VOi. 14, pp 305-366. (28) Snyder, L. R. In R#WeS of Acbptbn C)wometogephy:oiddkrgs,J. C., Keiler, R. A., Eds.; Marcel Dekker, Inc.: New York, 1968. (29) Moore, W. J. physhl Chemlsfry, 4th ed.;Rentice-Hall, Inc.: Englewood Cliffs, NJ, 1972. (30) McClellan, A. L.; Harnsberger, H. F. J . C o / M Interface Sci. 1987, 2 3 , 577-599. (31) Cheong, W. J.; Can, P. W. A&. them. 1989, 6 1 , 1524-1529. (32) Kamlet, M. J.; Abboud, J. L. M.; Taft, R. W. prog. phys. org. Chem. 1981, 13, 485-630.
(33) Jenkins, G. M.; Kawamura, K. Nature 1971, 237, 175-176. (34) Robertson, J. A&. phys. 1988, 35. 317-374. (35) Bassler, E. J.; Hartwick. R. A. J . Chrmtogr. Sc/. 1989, 27. 182- 165. (36) Bassler, B. J.; Kalisan, R.; Hartwick, R. A. J . Chrmtogr. 1989. 461m 139-147. (37) Bowling, R.; Packard, R.; McCreely, R. L. J . E/&”. Soc. 1988, 735, 1605-1606. (38) Stair, P. C. J . Am. Chem. Soc.1982, 104, 4044-4052. (39) Pearson, R. G. J . chem. Educ. 1988, 45, 581-587. (40) Lewis, G. N. Frank//n Inst. 1938, 226, 293. (41) Finston, H. L.; Rychtman, A. C. A New Vlew of Current AcM-Base 77”;John Wiley 8 Sons: New York, 1982. (42) Kolthoff, I. M. In TreatEse on Ana&tka/ chemlsby; Kdthoff, I. M., Eking, P. J., Sandell, E. B., Eds.; Wley-Intersclence: New York, 1959; Vol. I, Part 1, Chapter 11.
RECEIVED for review January 14,1991.Accepted May 29,1991. Financial support for this reasearch was provided by The Ohio State University Office of Research and the Eli Lilly Co.
High-Performance Liquid Chromatographic Determination of 15NH4:[I4NH4 15NH4]Ion Ratios in Seawater for Isotope Dilution Experiments
+
Wayne S. Gardner* and Lynn R. Herche NOAA Great Lakes Environmental Research Laboratory, 2205 Commonwealth Boulevard, Ann Arbor, Michigan 48105 Peter A. St. John St. John Associates, Inc., 4805 Prince George’s Avenue, Beltsville, Maryland 20705 Sybil P. Seitzinger Division of Environmental Research, The Academy of Natural Sciences of Philadelphia, 19th and the Parkway, Philadelphia, Pennsylvania 19103
A llquld chromcrtographlc mahod with fiuoronntric detectton, after postcolumn labeling with o -phthdaldehyde/2mercaptoethad rea@ent, was detvdoped to directly quantlfy 15NH,:[14NH4 15NH,] lon ratios in aqueous samples that had been enrlched wHh “NH, for Isotope dllutlon experbnents. Catlon-exchange chromatography, with a sodlum borate buffer mobHe phase, was selected as the separation mode because the two kotopcn have sUghUy Merent constants in the equl#brbm reactbn between ammonium lon and ammonla. When the two forms of ammonlum were passed separately through a hlgh-performance cattonaxchange column under preclsely controlled chromatographic condnlons, the r e t e t h e (RT) of “NH, was 1.012 tcner the RT of “NH,. The two isotopic forms of ammonium ion were not resolved Mo separate peaks when they were Injected together, but the retentlon tlme of the comblned peak, as defined by an Integrator, Increased wlth Increadng percentages of “NH, In the mixture. The rdatlonshlp of RT shtft vs percentage of lSNH, relative to total ammonlum followed a dgmold-shaped curve with the maximum RT shms per change in M o p l c composHlon occurring between 25 and 75% “NH,. Udng a callbratlon curve based on thls relationship and a solution of separately InJected 14NH4In mobile-phase buffer as an “internal standard”, we were able to directly determlne the concentratlono and ratios of the two isotopes In enrlched seawater.
+
* Corresponding author. 0003-2700/91/0363-1838$02.50/0
INTRODUCTION Nitrogen recycling by organisms is a major proem providing ammonium ion to primary producers in marine and freshwater food webs (1-3). Measurement of nitrogen recycling rates in aquatic systems is complicated by the fact that production and uptake processes occur simultaneously, often at similar rates, with the net result that ammonium ion concentrations do not necessarily change substantially even when recycling rates are relatively high (4). Isotope dilution experimenta, involving the addition of [16N]ammoniumion to water samples and the measurement of changes in the concentrations and isotopic composition of dissolved or particulate nitrogen in the sample over measured time intervals, provide a means to study nitrogen cycling rates in aquatic systems (e.g., refs 5 and 6). In these experiments, it is assumed that both ammonium isotopes will be taken up at about the same relative rates by organisms but that previously fixed nitrogen with a + 14NH4]= 0.9963) will natural isotopic ratio (l4NH4:[l6NH4 account for most of the ammonium ion released by mineralization proceases during short incubation intervals (hours). To calculate the ammonium ion regeneration and uptake rates by isotope dilution models (5-7),both ammonium ion concentrations and isotope ratios must be determined during short incubations. The usual procedure to determine isotope ratios is to convert the fixed nitrogen to Nzand then measure the nitrogen isotope ratios by mass or emission spectrometry. Conversion of particulate nitrogen to Nzby combustion of dried samples in the presence of an oxidizing agent is relatively uncompli0 I991 Amerlcan Chemical Society
