Anal. Chem. 1995,67,499-510
Chemical Selectivity in Micellar Electrokinetic Chromatography: Characterization of Solute-Micelle interactions for Classification of Surfactants Shenyuan Yang and Morteza 0. Khaledi*
Department of Chemistv, North Carolina State University,Raleigh, North Carolina 27605-8204
The influence of surfactant type on migration behavior and chemical selectivity in micellar electrokinetic chromatography (MEKC) is investigated through linear solvation energy relationships (LSER) and functional group selectivities. In LSER modeling, solutes' capacity factors are correlated with their structural descriptors such as size, &polarity, and hydrogen-bonding abilities. Using the LSER methodology, useful information about the nature of solute interactions with different types of surfactant wegates can be obtained since capacity factor in MEKC is directly related to solute distribution between the bulk aqueous solvent and micelles. High correlations were observed for differentLSER models of migration behavior in MEKC for a group of 60 uncharged aromatic compounds of non-hydrogenbonding (NHB), hydrogen-bonding acceptor (HBA)bases, and hydrogen-bonding donor (HBD) acids. In two anionic, hydrocarbon micellar systems of sodium dodecyl sulfate (SDS) and sodium cholate (SC), retention is primarily influenced by the size of molecules and their hy&ogen bond accepting basicity. Their dipolarity/polarizability and hydrogen bond donating acidity play minor roles. Capacity factors of solutes in SDS and SC systems increase with their size and decrease for stronger hydrogen bond acceptor bases. These results are similar to those observed for other systemswhere hydrophobic interactions play a major role, e.$., solute distribution in the 1-octanol-water solvent system or retention in reversed phase LC. In MEKC with an anionic fluorocarbon surfactant, lithium perfluorooctanesulfonate (IiPFOS), however, size and solute HBD acidity are the two predominantfactors. The LSER results indicate that compounds find the SDS micellar environments slightly less cohesive (Le., more apolar) than the SC micelles, while the IiPFOS micelles are the most cohesive among the three swhctant aggregates and l-octan01 provides the least cohesive environment. The fluorocarbon micelles of WFOS, on the other hand, are the strongest hydrogen bond donor acids, followed by SDS, SC, and 1-octanol, respectively. The SC micelles have the most hydrogen bond acceptor basic characteristics, followed by 1-octanol,SDS, and IiPFOS micelles. It can be concluded that selectivity differences between these surfactant types in MEKC is primarily due to hydrogen-bonding interactions rather than the dipolar interactions. Comparing the perfluorinated and the hy0003-2700/95/0367-0499$9.00/0 0 1995 American Chemical Society
drocarbon surfactants, even solute size can play a role in selective migration patterns. In addition, information from polar and hydrophobic group selectivities con6rm the LSER conclusions about the underlying interactions that control migration behavior and chemical selectivity in MEKC. This paper is the &st attempt from this laboratory to characterize the important interactions that control migration pattems in MEKC. A better understanding of these interactions may lead to classification of surfactant aggregates in terms of their chemical selectivity.
In micellar electrokinetic chromatography (MEKC) ,l uncharged molecules are separated on the basis of their differential partitioning into the micellar pseudostationary phase.'-3 The fact that MEKC has been regarded as a chromatographic technique is primarily the result of the partitioning mechanism. As with conventional chromatography, the chemical nature of the interactive phase in MEKC plays an important role in the separation process. A main advantage of MEKC is the feasibility of changing the chemical composition of the system by simply rinsing the capillary with a solution of the new pseudostationary phase. Migration behavior in MEKC can then be easily manipulated and controlled through proper selection of the surfactant type, mixed micelles, or inclusion of various m o a e r s such as cyclodextrins,4J organic solvents,6-* and urea? Unfortunately, despite the enormous flexibility and the ease of varying chemical conditions in MEKC, selection of the optimum composition of the micellar interactive phase, among numerous possibilities, is not a simple task.lo-l3 Presently, due to the lack of knowledge about the exact Terabe, S.; Otsuka, K; Ando, T. Anal. Chem. 1985,57,834. Khaledi, M. G.; Quang, C.; Sahota, R S.; Strasters, J. K; Smith,S. C. In Capillary Electrophoresis Technology; Guzman, N. A, Ed.; Marcel Dekker: New York, 1993;Part I, pp 187-260. Khaledi, M. G. In Handbook of Capillary Electrophoresis; Landers, J. P., Ed.; CRC Press: Ann Arbor, MI, 1993; Chapter 3, p 43. Terabe, S.; Miyashita,Y.; Shibata 0.;Barnhart, E.; Alexander, L; Patterson, D.; Karger, B.; Hosoya,K; Tanaka, N. J, Chromatog. 1990,516,23. Nishi, H.;Matsuo, M. J. Liq. Chromatogr. 1991,14,973. Balchunas, A;Sepaniak, M. Anal. Chem. 1987,59, 1466. Sepaniak, M.; Swaile, D.; Powell, A; Cole, R J, High Resolut. Chromatogr. 1990,13,679. Weinberger, R;Lurie, I. Anal. Chem. 1991,63,823. Terabe, S.;Ishihama, Y.; Nishi, H.;Fukuyama,T.; Otsuh, K J Chromafop. 1991,545,359. Khaledi, M. G.; Smith,S. C.; Strasters, J. K Anal. Chem. 1991,63,1820. Smith,S.C.; Khaledi, M. G. J. Chromatogr. 1993,632,177. Strasters, J. IC; Khaledi, M. G. Anal. Chem. 1991,63,2503.
Analytical Chemistry, Vol. 67,No. 3,February 1, 7995 499
chemical nature of solute-micelle interactions, this is accomplished by trial and error or according to analysts' intuition and experience. Stationary phases in GC or solvents in LC can be chosen on the basis of selective chemical interactions using the Rohrschneider-McReynolds scale14 or Snyder's selectivity triangle.15J6 Similar efforts in MEKC can obviously be quite beneficial. Since the first introduction of MEKC,' sodium dodecyl sulfate (SDS) has been the predominantly used surfactant. Several reports, however, have demonstrated the important role of surfactant type in MEKC as different migration patterns have been observed for the same group of compounds using various s ~ r f a c t a n t s . ~The ~ - ~variation of migration patterns with surfactant type is indicative of the selective nature of solute interactions with micelles. It is widely known that hydrophobic interaction is the main driving force behind solute retention by the micellar pseudostationary phase in MEKC. However, the influence of selective mechanisms such as hydrogen-bonding and dipolar interactions or even steric effects on solute binding to micelles and consequently on migration behavior in MEKC is not clear. The main focus of this paper is the characterization of various solute interactions with different micelles in MEKC through linear solvation energy relationships (LSER)?lzZ2 In LSER modeling,21s22the relationships between migration behavior in MEKC (quantitated by logarithm of capacity factor, log k') and structural descriptors of solutes (represented by solvatochromic parameters and intrinsic molar volume) are investigated. The LSER methodology and the solvatochromic parameters were first developed by W e t , Taft,and ceworkers?l In general, LSER models are built to describe the innuence of solute-solvent interactions in terms of nonspecik and specifk interactive forces. Thus, a solvent- or solubility-relatedproperty (SP) can be generally described by three main processes as
SP = SPo+ cavity term
+ dipolar term + hydrogen-bondmg term(s) (1)
In the case of MEKC migration, SP would be logarithm of the capacity factor, log k', and the three terms show the net effects of solute interactionswith the two interactive phases: bulk aqueous solvent and micelles. A multiparameter equation can then be written with four system coefficients (m, s, b, a) and four descriptors of solutes properties (6,n",/?,a) as
+
SP = SPo mV,/100 + sn* + bp + aa
(2)
The cavity term, m6/100, is an endoergic (disfavorable) process that represents the free energy that is required to separate (13) Quang, C.; Sbsters, J. IC; Khaledi, M. G. Anal. Chem. 1994, 66, 1646. (14) McReynolds, W.0.J. Chromatogr. Sci. 1970,8, 685. (15) Snyder, L. R J Chromatogr. Sci. 1978, 16,223. (16) Snyder, L R;Kirkland, J. J. Introduction to Modem Liquid Chromatography, 2nd ed.; Wiley: New York, 1979; p 260. (17) Bumgarner, J.; Khaledi, M. G. Electmphorais 1994, 15, 1260. (18) Nishi, H.; Fukuyama,T.; Matsuo, M.; Terabe, S.J Chromatogr. 1990,498, 313. (19) Cole, R;Sepaniak, M.; Hinze, W. L J. High Resolut. Chromatogr. 1990, 13, 579. (20) Cole, R;Sepaniak, M.; Hinze, W.; Gorse, J.; Oldiges, K. J. Chromatop. 1991, 557, 113. (21) Taft, R W.; Abboud, J. M.; Kamlef M. J.; Abraham, M. H.J Solut. Chem. 1985, 14, 153. (22) Carr, P. W.Microchem. J. 1993, 48, 4.
500 Analytical Chemistry, Vol. 67,No. 3,February 1, 1995
solvent molecules (i.e., to overcome solvent-solvent interactions) in order to provide a suitably sized cavity for the solute. Intrinsic molar volume (van der waals volume), 6, describes the solutes effect, and coefficient m shows the solvent contributions. This term is in fact a measure of nonspecific interactions. Note that the formation of a cavity is an important part of hydrophobic interaction. The other two specific interaction terms are exoergic or favorable. The dipolar term, sn",is a measure of dipole-dipole and dipole-induced dipole interactions, where n* is a quantitation of dipolarity/polarizabilityof solutes, while s is the equivalent term to describe the solvent involvement. The hydrogen-bondmg terms represent the interactions involving sharing of a proton, both the typeA (shown by b/?for solutes accepting and solvent (s) donating) and the type B (represented by aa for solutes donating and solvent(s) accepting). Therefore, b is to account for the strength of solvent hydrogen bond donating acidity, /? is solute hydrogen bond accepting basicity, a is solvent hydrogen bond accepting basicity, and a is solute hydrogen bond donating acidity. The SPOterm in eq 2 includes information about the chromatographic systems such as phase ratio.22 LSER modeling has been used to describe the interactions in over 600 different chemical and biological systems. A few examples that are relevant to this work are solute distributions in l-octanol-water system, aqueous solubility, and retention in reversed phase liquid chromatography WE)F3-30 We have recently applied this method to describe retention behavior in solute , binding to micelles, micellar liquid chromatography (ME) and migration behavior in MEKC.31 In a sense, LSER is an example of quantitative structure retention relationships (QSRR), where migration in MEKC is described by solute structural properties. Recently, we observed another example of QSRR through correlations between log k' in MEKC and l-octanol-water partition coefficients (log The log k' vs log Powrelationships were investigated for two reasons. First was the estimation of either log Powfrom MEKC capacity factors or vice versa, prediction of migration behavior in MEKC on the basis of the available log Powdata bank. The second reason was to better understand the migration behavior of solutes according to their structural properties. The relationships between log k' and log Powprovided some useful insights about the different behavior of solutes in various surfactant systems in MEKC. However, no dehite conclusion could be made about the exact nature of the underlying interaction forces that control the migration process. The log Powscale is the most widely known (23) T& R W.; Abraham, M. H.; Famini, G. R; Doherty, R M.; Abbroud, J. M.; M e t , M. J. I. P h a m . Sci. 1985, 74, 807. (24) W e t , M. J.; Doherty, R M.; Abraham, M. H.; Marcus, Y.; Taft, R W. J. Phys. Chem. 1988, 92,5244. (25) Kamlef M. J.;Abraham, M. H.; C a r , P. W.; Doherty, R W.; Taft, R W.J Chem. SOC.,Perkin Trans. 2 1988,2087. (26) Park,J.H.;Carr,P.W.;Abraham,M.H.;Taft,RW.;Doherty,RM.;Kamlet, M. J. Chromatographia 1988,25,373. (27) Park, J. H.; Nah, T. H . J Chem. Sot., Perkin Trans. 2 1994, 1359. (28) Helburn, R S.;Rutan, S. C.; Pompano, J.; Mitchem, D.; Patterson, W. T. Anal. Chem. 1994, 66, 610. (29) Park,J. H.; Chae, J. J.; Nah, T. H.; Jang, M. D.J. Chromatogr. 1994, 664, 149.
(30) Sadek. P. C.; Carr, P. W.; Doherty, R M.; W e t , M. J.; Taft, R W.; Abraham,M. H. Anal. Chem. 1985,57, 2971. (31) Yang, S.; Khaledi, M. G. J. Chromatogr., in press. (32) Yang, S.;Bumgarner, J. G.; Kruk, L. R; Khaledi, M. G. submitted for publication in Anal. Chem.
quantitative measure of the lipophilic character of mole~ules.3~-35 In addition to hydrophobic interactions, hydrogen bonding can also play an important role in the l-octanol-water partitioning process. Using the LSER models, on the other hand, one can differentiate between the effects of different specific and nonspe cijic interactions on migration patterns. The system coefficients (m,s, b, a) provide useful information about the interactive nature of different types of micelles or other organized media. EXPERIMENTAL SECTION
All experiments were carried out on a laboratory-built CE system that comprised a 0-30 kV high-voltage power supply (Series EH, Glassman High Voltage, Inc., Whitehouse Station,NJ) and a 50 pm i.d., 375 pm 0.d. fused-silica capillary tubing (Polymicro Technologies, Phoenix, AZ). The total length of the capillary was 62 cm, and detection was performed at 50 cm downstream. A variablewavelength W detector (Model 200, Linear Instruments, Reno, NV) was used in this work. The wavelength was set at 210 nm for sodium dodecyl sulfate (SDS) buffers, at 254 nm for sodium cholate (SC) buffers, and at 214 nm for lithium perfluorooctanesulfonate GPFOS) buffer. An integrator (Model SP 4200, Spectra-Physics, San Jose, CA) was utilized to record the electropherograms. The samples were introduced into the anodic end of the capillary by gravity, 10 cm height for 8 s. A positive voltage of 20 kV was applied throughout the experiment. Reagents. All the test solutes were purchased from Aldrich (Milwaukee,WI). Test solutes and their solvatochromic parameters are listed in Table 1. The solvatochromic parameters were obtained from ref 24 or estimated in terms of the rules described in the same paper. The stock solutions of SDS (Sigma, St. Louis, MO), SC (Aldrich, Milwaukee, WI), and WFOS (3M Co., St. Paul, MN) were prepared by dissolving the required amount of surfactant in doubly distilled deionized water and were filtered through a 0.45 pm nylon-66 membrane filter (Rainin, Wobum, MA). Buffer solutions were kept at pH 7.0 and 0.050 M phosphate (ionic strength) for SDS, SC, and LiPFOS. The capillary temperature was maintained at 25 "C. The migration t h e of an unretained solute (i.e., t,) was measured from the time of injection to the first deviation from the base line for the solvent peak, methanol. The tmcmarker was n-dodecanophenone. RESULTS AND DISCUSSION
Retention-Surfactant Qpe Relationship. Several reports demonstrated the signjjicance of the surfactant type in MEKC separation~.'~-2~ The chemical composition of the hydrophobic moieties and ionic head groups in surfactants signiscantly influences their interactions with solutes as well as the migration velocity of micelles. In other words, type of surfactant has a major impact on at least three of the four factors that influence resolution in MEKC, i.e., capacity factor (h'), selectivity (a),and size of the elution window (tmc/tm). In many cases, efficiency is also affected. Consequently, the characterization of different surfactants is of great interest for a better understanding of the separation process in MEKC. In this work, the retention behavior of 60 aromatic compounds in three anionic surfactants was examined. Two of the surfactants, (33) Hansch, C.; Leo, k Substifufenf Constants for Correlation Analysis in Ckemisfty and Bioiom, Wiley-Interscience: New York, 1979. (34) Hansch, C. In Dmg Design; Mens, E. J., Ed.; Academic Press: New York, 1971; Vol. 1, p 271. (35) Khaledi, M. G.; Breyer, E. D. Anal. Ckem. 1989,61, 1040.
Table 1. Test Solutes and Their Solvatochromic Parameters'
compds
1 2 3 4 5 6 7 8 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 (I
benzene toluene ethylbenzene propylbenzene pxylene acetophenone propiophenone butyrophenone valerophenone benzaldehyde benzonitrile nitrobenzene anisole ethoxybenzene methyl benzoate ethyl benzoate fluorobenzene chlorobenzene bromobenzene iodobenzene +dichlorobenzene odichlorobenzene 2chloronitrobenzene khloronitrobenzene khlorotoluene khloroanisole Cbromonitrobenzene Cnitrotoluene khloroacetophenone methyl 2-methylbenzoate phenyl acetate phenol Cmethylphenol kthylphenol Cfluorophenol khlorophenol 4bromophenol Ciodophenol benzyl alcohol Cmethylbenzyl alcohol khlorobenzyl alcohol aniline Nethylaniline khloroaniline Cbromoaniline pyridine naphthalene 1-methylnaphthalene 2-methylnaphthalene anthracene biphenyl 3chlorophenol 3-methylphenol 2-methylphenol %bromophenol Smethylbenzylalcohol khlorobenzyl alcohol phenethyl alcohol 3-phenyl-1-propanol 3,5dimethylphenol
W O O
JC*
0.491 0.592 0.668 0.769 0.668 0.690 0.788 0.886 0.984 0.606 0.590 0.631 0.639 0.727 0.736 0.834 0.520 0.581 0.624 0.671 0.671 0.671 0.721 0.721 0.679 0.720 0.764 0.729 0.780 0.834 0.736 0.536 0.634 0.732 0.562 0.626 0.669 0.716 0.634 0.732 0.724 0.562 0.758 0.653 0.659 0.470 0.753 0.851 0.851 1.015 0.920 0.626 0.634 0.634 0.669 0.732 0.724 0.732 0.830 0.732
0.59 0.55 0.53 0.51 0.51 0.90 0.88 0.86 0.84 0.92 0.90 1.01 0.73 0.69 0.75 0.74 0.62 0.71 0.79 0.81 0.70 0.80 1.11 1.01 0.67 0.73 1.01 0.97 0.90 0.71 1.14 0.72 0.68 0.66 0.73 0.72 0.79 0.81 0.99 0.93 1.11 0.73 0.82 0.73 0.79 0.87 0.70 0.66 0.66 0.80 1.18 0.77 0.68 0.68 0.84 0.95 1.11 0.97 0.95 0.64
j?
0.10 0.11 0.12 0.12 0.12 0.49 0.49 0.49 0.49 0.44 0.37 0.30 0.32 0.30 0.39 0.41 0.07 0.07 0.06 0.05 0.03 0.03 0.26 0.26 0.08 0.22 0.26 0.31 0.45 0.40 ' 0.52 0.33 0.34 0.35 0.28 0.23 0.23 0.35 0.52 0.53 0.42 0.50 0.47 0.40 0.40 0.44 0.15 0.16 0.16 0.20 0.20 0.23 0.34 0.34 0.23 0.53 0.42 0.55 0.55 0.35
a 0 0 0 0 0 0.04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.06 0 0 0.61 0.58 0.58 0.65 0.67 0.67 0.71 0.39 0.39 0.40 0.26 0.17 0.31 0.31 0 0 0 0 0 0 0.69 0.58 0.54 0.69 0.39 0.40 0.33 0.33 0.56
Solvatochromic parameter values are from ref 24.
SDS and SC, have hydrocarbon hydrophobic moieties while the third one, LiPFOS, is a fluorocarbon surfactant. The test solutes were selected from the paper published by Kamlet, Taft, and coworkers on the LSER analysis of 1-octanol-water partition coefficients.% These aromatic compounds were classified in a similar manner to that of Kamlet and Taft into three groups of non-hydrogen bonding (NHB), hydrogen-bonding donor (HBD) Analytical Chemistty, Vol. 67, No. 3,February 1, 1995
501
0.81.5-
0.61-
% I
-: k
0.4-
dg
0.5-
I E
0.20-
sk 4.2-
0-
8
8 -0.4-
-0.5-
-0.6-
-0.8U
-1.5 -0.5
0
0.5
1 log k’ (40m M SDS)
1.5
2
2.5
Flgure I.Plot of log K(60 mM SC) vs log K(40 mM SDS).log K(60 mM SC) = (1.02 f 0.01) log K(40 mM SDS) - 0.04; n = 60, r = 0.9328, SE = 0.203. Line 1 (H) includes alkylbenzenes, halobenzenes, polyaromatic hydrocarbons, phenol, and halophenols (1-5, 17-22,25,32,35-38,47-52,55). The following regression equation was obtained: log K(60 mM SC) = (0.88 f 0.01) log K(40 mM SDS) - 0.17; n = 24, r = 0.9898, SE = 0.080. Line 2 (*) consists of aromatic ethers, nitrobenzenes, alkylphenols, and halobenzyl alcohols (1214, 23, 26,33,34, 41,44,45,53, 54,57,60). It can be described by the following regression equation: log K(60 mM SC) = (1.03 f 0.04) log K(40 mM SDS) - 0.39; n = 14, r = 0.9758, SE = 0.050. Line 3 (0) includes alkyl aromatic ketones, aromatic esters, benzonitrile, anilines, and alkylbenzyl alcohols (6-1 1, 15, 16,24, 27-31, 39,40, 42, 43, 56, 58, 59). It can be described by the following equation: log K(BO mM SC) = (0.88 f 0.02) log K(40 mM SDS)- 0.58; n = 21, r = 0.9854, SE = 0.064.
acids, and hydrogen-bonding acceptor (HBA) bases.24 The NHB compounds were in fact weak HBA solutes @ I0.2) and were termed as non-hydrogen bond donors by Kamlet and TafLB The overall migration patterns in all three types of micelles are different. This is shown in Figures 1 and 2, where the logarithm of capacity factors of the 60 test solutes in SC- and LiPFOS-MEKC systems are plotted against log k’ in the SDS system. Since hydrophobic interaction is the predominant driving force behind solute-micelle interactions, there exist some correlations between the migration behavior in different systems. On the other hand, the existence of more than one line (Figures 1 and 2) is an indication of the differences in migration patterns for different groups of solutes. There is a much higher degree of correlation between retention behavior in SDS and SC systems (r = 0.9328, n = 60) than that between LiPFOS and SDS (r = 0.7131, n = 60). The correlation between retention in the SC and LiPFOS is very low (r = 0.49), which indicates the largest difference in selectivity between the latter two micellar systems. Obviously, one can detect higher correlations in retention behavior among several subgroups of compounds. It is apparent that the NHB group has a behavior different from the HBA solutes in both cases (Figures 1and 2) and HBDs are divided into various groups (vide infra). The interesting point is that these various subgroups have different (in fact opposite) affinities toward the three surfactant aggregates. In Figure 1, one can identify relatively high correlations between retention in SDS and SC systems for three subgroups of compounds [apparently pyridine (46) is an outlier]. The first group (top line with the filled squares) mainly consists of nonhydrogen-bonding solutes such as alkylbenzenes, halobenzenes, 502 Analytical Chemistry, Vol. 67, No. 3, February 1, 1995
1
-0.5
0
0.5
1
1.5
2
Icg k’ (40 mM SDS)
Figure 2. Plot of log K(40 mM LiPFOS) vs log K(40 mM SDS). log K(40 mM LiPFOS) = (0.59 f 0.02) log K(40 mM SDS) - 0.43; n = 60, r = 0.7131, SE = 0.298. Line 1 (m) consists of alkylbenzenes, halobenzenes, PAHs, alkylphenols, two chlorinated benzyl alcohols, and chlorinated aromatic ether (1-5, 17-22,25,26,33,34,41, 4751, 53, 54, 57, 60). The following equation was obtained: log K(40 mM LiPFOS) = (0.57 f 0.01) log K(40 mM SDS) - 0.54; n = 25, r = 0.9645, SE = 0.093. Line 2 (*) includes alkyl aromatic ethers, chlorinated aromatic compounds with a carbonyl or nitro group, alkylbenzyl alcohols, and pyridine (13, 14, 23,24, 27, 39, 40, 43, 48, 56, 58, 59). It can be described by the following equation: log K(40 mM LiPFOS) = (0.88 f 0.04) log K(40 mM SDS) - 0.37; n = 12, r = 0.9814, SE = 0.048. Line 3 (A)consists of alkyl aromatic ketones, esters, and nitrobenzenes (6-12, 15, 16, 28-31). The following regression equation was obtained: log K(40 mM LiPFOS) = (0.79 & 0.03) log K(40 mM SDS)- 0.37; n = 13, r = 0.9842, SE = 0.059. Line 4 (0)includes phenol, aniline, halophenols, and haloanilines (32, 35-38, 42,44,45,52, 55). The regression equation was as follows: log K(40 mM LiPFOS) = (0.29 f 0.03) log K(40 mM SDS) - 0.77; n = 10, r = 0.9046, SE = 0.052.
and polyaromatic hydrocarbons (PAHs) along with some hydrogenbonding donor acids like phenols. The hydrogen bond acceptor bases are divided into two groups according to their retention behavior in the two MEKC systems. The middle line (with the asterisks) includes some of the HBA bases such as aromatic ethers and nitrobenzene and several halogenated aromatic compounds such as anilines, alcohols, and ethers. The bottom line (with open squares) mainly consists of other hydrogen-bondingacceptor bases such as alkyl aromatic ketones, aromatic esters, benzonitrile, and anilines as well as some HBD compounds like benzyl alcohols. The classification of solutes according to their retention in LiPFOS (as compared to that in SDS, Figure 2) is somewhat similar; however, the order of the lines is opposite of the SC vs SDS case (Figurel). That is, the HBA bases fall into two groups but are the top lines, which indicates their higher affinity for the LiPFOS micelles. The top line (filled triangles) consists of alkyl aromatic ketones, nitrobenzenes, and aromatic esters. The second line is comprised of other HBA bases like aromatic ethers, chlorinated aromatic compounds with a carbonyl or nitro groups, and pyridine. The third line belongs to NHB compounds such as alkylbenzenes, halogenated benzenes, and polyaromatic hydrocarbons, as well as some HBD acids like alkylphenols and two Chlorinated benzyl alcohols. The fourth group consists of halophe nols and anilines. These results indicate that the hydrophobic NHB compounds have a stronger a€fhity toward the SC micelles than HBA bases
Table 2. Effect of Micelles on Migration Behavlor In MEKC
SP log k’ (0.02 M SDS) log k’ (0.04 M SDS) log k‘ (0.06 M SC) log k‘ (0.08 M SC) log k‘ (0.04 M LiPFOS)
SPO
m
S
b
a
-1.87
4.00 (0.05) 3.95 (0.05) 3.89 (0.05) 3.82 (0.05) 2.44 (0.05) 5.62 (0.05)
-0.25 (0.04) -0.26 (0.04) -0.27 (0.04) -0.32 (0.04) -0.25 (0.03) -0.66 (0.03)
-1.79 (0.04) -1.80 (0.04) -2.88 (0.04) -2.85 (0.04) 0.16 (0.04) -3.90 (0.04)
-0.16 (0.02) -0.18 (0.02) 0.23 (0.02) 0.18 (0.02) -0.98 (0.02) 0.14 (0.02)
-1.49 -1.62 -1.38 -1.51 0.17
log Pow
-b/m
na
Ib
SEc
0.45
60
0.9538
0.159
0.46
60
0.9553
0.156
0.74
60
0.9684
0.144
0.75
60
0.9691
0.142
60
0.9511
0.135
60
0.9863
0.135
-0.07 0.69
n is the number of test solutes. r is the correlation coefficient of linear regression. SE is the standard error of Y estimated.
(Figure 1). To the contrary, the former compounds’ interactions with the LiPFOS micelles are smaller than the latter HBA solutes. These results are consistent with the LSER conclusion that the SC micellar environment is less cohesive with stronger HBA affinity, while the LiPFOS micelles have more HBD characteristics and favor interactions with the HBA bases (vide infra). LSER Analysis. Kamlet, Taft, and co-workers24 reported the LSER modeling of l-octanol-water partition coefficients for 245 aliphatic and aromatic compounds as
log Pow= 0.35
+ 5.35F/100 - 1.04 (n* - 0.356) 3.48&
n = 245, r = 0.9959, SD = 0.131
+ O.lOa, (3)
where log Powis the logarithm of l-octanol-water partition coefficients, VI is the intrinsic (van der Waals) molar volume, n*, Bm,and a,are the solvatochromic parameters that measure solute dipolarity/polarizability, hydrogen bond acceptor basicity, and hydrogen bond donor acidity respectively, and 6 is a “polarizability correction”parameter. In a recent we reported the initial results of our LSER analysis of MEKC migration behavior for a group of 25 aromatic compounds along with that for retention in MLC. The LSER models were derived for MEKC migration (where SP = log k’ in eq 2) as well as log Powfor comparative purposes. The following LSER equations were observed for a 40 mM SDS MEKC system
log k’ = -1.88
+ (4.42 f O.O5)V1,/100 - (0.15 & 0.05)n* (1.88 k 0.05)p - (0.07 f 0.07)a
n = 25, r = 0.9885, SE = 0.081
(4)
for a 60 mM SC MEKC system log k‘ = -2.07
+ (4.56 f 0.09)&/lo0 - (0.24 & 0 . 0 6 ) ~ *(2.84 f 0.06)B + (0.26 k 0.04)a n = 25, r = 0.9903, SE = 0.086
(5)
for l-octanol-water system log Pow= 0.11 + (5.49 f O.O8)VI/lOO - (0.43 f 0.05)~*(3.88 f 0.05)8 (0.02 f 0.04)a
+
n = 25, r = 0.9952, SE = 0.080 (6) In eqs 4 and 6, the a coefficientsare not statistically si&cant at the 95% confidence level. In this work, a group of 60 aromatic compounds with known solvatochromicparameter values (Table 1)was selected from the test set used by Kamlet, Taft, and co-workers.” The extended test set includes representative compounds from three main subgroups: (1) non-hydrogen bonding solutes that include alkyland halo-substituted benzenes and polyaromatic hydrocarbons. These compounds do not have any hydrogen-bonding functional groups; however, they are weak hydrogen bond acceptors (Le., E, I0.2) due to the aromatic ring($; (2) compounds with hydrogenbonding acceptor functional group(s) on the aromatic ring; and (3) compounds with hydrogen-bonding donor functional group (s). The LSER models were derived for three surfactant systems at different concentrations, and the results are listed in Tables 2-5. The high correlation coefficients and small errors indicate the suitability of LSER models for description of migration in MEKC. The coefficient values for the larger set (n = 60), however, are different from those reported earlier for n = 25.31 Note that these 25 compounds were mainly halogenated aromatic compounds. These variations are even more pronounced for the three subsets of the 60 compounds that have been grouped as NHB, HBA, and HBD compounds (Tables 3-5). The differences in the LSER coefficients are indicative of variations in the types of interactions between micellar systems and various groups of solutes. This can be due to the heterogeneous nature of micellar media, which are different from the homogeneous isotropic liquids like l-octanol. As a result, microenvironments of solutes in micelles vary significantly. Solute interactions with micelles occur through various mechanisms such as surface adsorption, comicellization, or partitioning into the hydrophobic core of micelles. The location of solubilization in/on micelles depends on the physicochemical and structural properties of the solute molecules. Since various compounds occupy different locations in/on micelles, the LSER models for the three subgroups can be different as the underlying mechanisms or interactions are not identical. By including all compounds in one set, the observed MEKC coefficients might be weighted averages of the coefficients for the constituent subsets. It is also important to differentiate between the variations caused by such chemical effects from those due to statistical artifacts that might be involved in multiple linear regression analysis of the LSER models. In fact, the robustness of the LSER models is an important criterion for evaluating the Analytical Chemistry, Vol. 67, No. 3, February 1, 1995
503
Table 3. Non-Hydrogen-BondingCompounds (Alkylbenzenes, Halobenzener, PAHr).
SP
SPO
m
S
b
-b/m
n
r
SE
log k’ (0.02 M SDS) log k’ (0.04 M SDS) log k’ (0.06 M SC) log k‘ (0.08 M SC) log k’ (0.04 M IiPFOS) log P o w
-2.51
5.22 (0.09) 5.02 (0.09) 4.51 (0.13) 4.43 (0.16) 2.75 (0.14) 5.57 (0.11)
-0.32 (0.05) -0.30 (0.05) -0.18 (0.08) -0.28 (0.09) -0.46 (0.08) -0.47 (0.05)
-3.12 (0.22) -2.84 (0.21) -3.27 (0.31) -3.49 (0.38) -1.23 (0.32) -3.97 (0.26)
0.60
17
0.9962
0.057
0.57
17
0.9965
0.054
0.73
17
0.9892
0.082
0.79
17
0.9821
0.101
0.45
17
0.9706
0.085
0.71
17
0.9949
0.070
-2.08 -2.04 -1.73 -1.48 0.10
See Table 2 for the definitions of n, r, and SE.
Table 4. Hydrogen Bond Acceptors (Alkylphenoner, Bensonltrile, Nitrobenzenes, Aromatic Esters, Aromatic Ethers, Anlllner)a
SP
SPO
m
S
b
a
log k’ (0.02 M SDS) log k’ (0.04 M SDS) log k’ (0.06 M SC) log k’ (0.08 M SC) log k‘ (0.04 M LiPFOS) log Pow
-1.85
3.75 (0.09) 3.73 (0.09) 3.29 (0.14) 3.30 (0.13) 2.78 (0.11) 5.58 (0.15)
-0.33 (0.07) -0.32
-1.32 (0.10) -1.27 (0.10) -2.26 (0.14) -2.28 (0.13) 0.47 (0.11) -3.07 (0.15)
0.37 (0.10) 0.35 (0.10) 0.61 (0.14) 0.56 (0.14) -2.01 (0.12) O.Nb (0.15)
-1.55 -1.25 -1.04 -1.92 -0.04
(0.07)
-0.51 (0.09) -0.56 (0.09) -0.13’ (0.08) -0.75 (0.10)
n
r
SE
0.35
23
0.9766
0.085
0.34
23
0.9749
0.088
0.69
23
0.9469
0.123
0.69
23
0.9504
0.120
-0.17
23
0.9741
0.103
0.55
23
0.9781
0.130
-b/m
See Table 2 for the definitions of n, r, and SE. * Value is not statistically significant at the 95%confidence level.
Table 5. Hydrogen Bond Donors (Phenols, Benzyl Alcohols)a
SP
SPO
m
S
b
a
-b/m
n
r
SE
log k‘ (0.02 M SDS) log k’ (0.04 M SDS) log k‘ (0.06 M SC) log k‘ (0.08 M SC) log k’ (0.04 M LiPFOS) log Pow
-4.03
4.43 (0.11) 4.43 (0.11) 4.07 (0.14) 4.15 (0.15) 2.72 (0.15) 5.78
0.39 (0.06) 0.34 (0.06) 0.62 (0.07) 0.61 (0.08) -0.43 (0.08) 0.28 (0.09) -0.93 (0.05)
-0.86 (0.16) -0.96 (0.16) -1.01 (0.19) -1.04 (0.21) -0.52 (0.21) -2.02 (0.24) -4.70 (0.12)
1.65 (0.14) 1.51 (0.15) 2.73 (0.18) 2.67 (0.19) -0.96 (0.19) 3.01 (0.22) -0.16’ (0.09)
0.19
19
0.9857
0.053
0.22
19
0.9849
0.054
0.25
19
0.9859
0.067
0.25
19
0.9835
0.072
0.19
19
0.9574
0.071
0.35
19
0.9891
0.082
0.81
32c
0.9778
0.106
-3.56 -4.53 -4.40 0.07 -2.98
(0.17)
log P o w
24).
0.75
5.77 (0.12)
See Table 2 for the definitions of n, r, and SE. Value is not statistically significant at the 95%confidence level. HBD solutes in Table 6 (ref
LSER m e t h o d o l ~ g y .This ~ ~ ~means ~ that LSER models should be independent of the number of compounds in the test set, assuming that there are s a c i e n t number of compounds in a set (Le., at least three times the number of independent variables) for a robust multiple linear regression. For a typical LSER model, this means that at least 12-15 compounds are required to build a robust LSER model. This criterion has been successfully examined for log Po,, and the results shown in Tables 2-5 and eq 6 would provide further support. Some variations in the LSER coefficients are expected in any multiple linear regression as the number objects (Le., solutes) in the subsets are significantly different from the main set (e.g., from 60 to -20). 504 Analytical Chemistry, Vol. 67,No. 3,February 1, 1995
The test set of 60 aromatic compounds in this study was carefully selected to represent a wide range of classes with various functional groups and hydrophobicity. The aliphatic compounds were excluded due to detection problems that also limit the application of MEKC for their analysis. Inclusion of aliphatic and aromatic solutes in one set would further complicate the LSER analysis. However, in future studies, aliphatic molecules will be examined in order to achieve a comprehensive understanding of migration behavior in MEKC. As mentioned earlier, through comparison of the regression coefficients (m,s, b, a) one can achieve a better understanding of the exact nature of different types of interactions that control migration behavior in MEKC.
According to the LSER models for SDS and SC micelles (listed in Tables 2-5), the size and basicity of the solutes are the two predominant factors that determine the extent of retention in these MEKC systems. The positive m and negative b values show that retention increases with the size of the solutes and decreases with their hydrogen bond acceptor strength. The effects of dipolarity/ polarizability and hydrogen bond donor strengths of solutes are less important. This is a behavior similar to the LSER results reported for log Powand retention in reversed phase HPLC.”*Z This seems to be a general trend among systems where hydrophobic interactions control solute partitioning from an aqueous phase into a hydrocarbon organic phase. Despite some apparent similarities, however, there are sign& cant differences between micellar pseudophases. For the MEKC system with the anionic fluorocarbon surfactant LiPFOS,size of the solutes and their acidity are the predominant factors. Again, retention in LiPFOSMEKC increases with solute size, however, to a much smaller extent than that in SDS or SC systems. On the other hand, stronger HBA basic solutes (i.e., larger j3) interact more with the LiPFOS micelles (and are retained longer) due to the positive b coefficient in the LSER models (Table 4), while stronger HBD acidic solutes (Le., larger a) have smaller affinity for the anionic fluorocarbon micelles due to negative a coefficient (Table 5). Effect of Surfactant Concentration. In MEKC, capacity factor k’ is directly related to partition coefficients between aqueous bulk solvent and micelles, Pmw
k ’ = P -=Pmw Vmc mw Vaq
v(Csf - cmc) 1 - v(Csf - cmc)
(7a)
where v is the molar volume of surfactant, Csf is the surfactant concentration, cmc is the critical micelle concentration, and Pmw is the partition coefficient of a solute between the micellar pseudophase and the aqueous phase. VJV, is the phase ratio of the system. At low micelle concentrations, the second term in the denominator of eq 7a becomes negligible and eq 7a can be rewritten as follows:
k’ = Pmwv(C,- cmc) = Kmw(Csf - cmc)
(7b)
where Kmwis solute-micelle binding constant and is defined as K,, = PmWv.l1 The LSER models at different SDS and SC concentrationswere derived (Tables 2-5). The surfactant concentration has basically little or no effect on the four regression coefficients (m, s, b, a). Only the regression constant SP,, which includes information about the chromatographic phase ratio, has changed. The dependence of k’ on surfactant concentration is through the variations in the phase ratio of micellar systems and has no bearings on the type and extent of solute interactionswith micelles (represented by P, or K , ) that control migration and selectivity. In other words, the LSER models of migration behavior in MEKC also reveal information about the nature of solute interactions with micelles. Solute Size and Cavity Term. The large positive m values indicate that the endoergic (disfavorable) cavity formation term has the most important effect on retention. It shows that capacity factor in MEKC increases with solute size. The
coefficient m is directly related to the difference in the cohesive energies of the aqueous phase and the organic phase (l-octanol or micelles) as shown by
where 6 is the Hildebrand solubility parameter and d2 is directly related to the cohesive energy, the subscript aq represents the aqueous phase and subscript o is for the organic phase (either l-octanol or micelles). M is a proportionality factor. By comparing the m values derived for the three micellar systems and that for 1-octanol, one can shed light on the relative cohesiveness of the organic phases. An assumption is made that d2, is the same for these systems, even though the bulk aqueous phase in micellar solutions contains monomer surfactants (at a concentration about the cmc) as well as buffer salts. However, one can still recognize a general trend in the results. The larger the m value, the smaller d2, or cohesive energy is; i.e., the organic phase is less cohesive. The positive sign of m coefficients indicates that solutes prefer to transfer from the more cohesive aqueous environment to the less cohesive organic phase. As the solutes’ sizes increase, their interactions with the organic phase are more favored. According to Table 2, m(LiPF0S) < m(SC) < m(SDS) < m(1octanol); thus, 62(LiPFOS) > Sz(SC) > dZ(SDS)> 62(1-octanol). Consequently, the fluorocarbon micelles of LiPFOS provide the most cohesive environment and the SDS micelles have the least cohesive (more apolar) media. The three micellar media are considerably more cohesive than l-octanol. Note that the cohesive energy increases with “polarity”,water being a highly cohesive phase with 6 = 23.4 as compared to 6 = 11.5 for 2-propanol and 6 = 7.54 for n-octane.22 Typically, fluoro compounds have lower cohesive energy than corresponding hydrocarbons; for example, 6 = 9.7 for CHzClz and 6 = 5.5. for cF~C12.3~Therefore, the results presented in Tables 2-5 do not agree with the trend in the cohesive energy of the bulk organic solvents. Sadek et al. also noted a similar anomaly in the LSER analysis of retention in reversed phase LC where the m values for hydrocarbon bonded stationary phases were larger than that for a fluorocarbon bonded stationary phase; i.e., the latter had a more cohesive energy. This was attributed to the existence of favorable dispersive interactions between hydrocarbon moieties of solutes with hydrocarbon bonded phases. It was also noted that alkyl bonded phases cannot be treated as bulk liquids. A similar situation also exists for the interaction between hydrocarbon solutes with the hydrocarbon micelles. The lack of affinity for interactionbetween hydrocarbons and fluorocarbons is often explained by the existence of a “phobia effect” that is also recognized as the reason behind the demicellization of fluorocarbon-hydrocarbon mixed surfactants into separate mixed micelles. We recently reported that solute capacity factors in MEKC systems with mixed micelles of lithium dodecyl sulfate (IDS) and LiPFOS decreased as the mole fraction of the fluorocarbon surfactant was in~reased.~~,~’ The capacity factors of larger, more hydrophobic members of an alkyl homologous series decreased to a greater extent as the mole fraction of WFOS was increased. The smaller m coefficients show that the endoergicity of cavity formation is smaller in the LiPFOS micellar systems (as compared to, for example, SDS); that is the main (36) Khaledi, M. G.; Hadjmohammadi, M. R, unpublished results. (37) Ye, B.; Hadjmohammadi, M. R; Khaledi, M. G. J. Chromatogr., in press.
Analytical Chemistry, Vol. 67, No. 3,February 1, 1995
505
reason for smaller retention in the anionic fluorocarbon MEKC system. The m values for the three subset groups of NHB, HBA, and HBD compounds are different from one another and for the whole set (Tables 3-5); however, the overall trend and their ranking remain the same, i.e., m(LiPF0S) < m(SC) m(SDS) < m(1octanol). For the non-hydrogen-bonding subgroup (Table 3) the m coefficients are larger than those for the main set and the gap between the m values of MEKC (specially for SDS) and that of l-octanol is smaller. This shows that the micellar microenvironments for these hydrophobic compounds are actually less cohesive (i.e., more nonpolar, hydrocarbon-like) than what is predicted by the LSER models in Table 2 for the whole set that also contained polar components. The data show that SDS micelles provide a slightly more nonpolar, hydrocarbon-like environment than SC micelles for solutes. This observation is in contrast with the results reported in the literature based upon fluorescence studies using pyrene as a p r ~ b e . ~ ~Also, - ~ O better correlation coefficients were observed for this subset (Table 3) as compared to that for the entire set (Table 2). For the hydrogen bond acceptor bases group (Table 4), the m values are smaller than those for the main set, which suggests that the compounds in this group are located in more polar environments of the micelles. For the third subgroup with hydrogen bond donor acids (Table 5), the m values are larger than those for the hydrogen bond acceptor bases but smaller than the non-hydrogen bond subset. This means that solutes in this group experience a slightly more nonpolar environment than the hydrogen bond acceptor bases. Overall, small variations in m values among the different solute groups are observed for LiPFOS, while the largest changes occur in the SDS system. Hydrogen Bonding. The two terms b#3 and a a show the sign5cance of hydrogen-bondmg effects between HBD solventHBA solutes and HBA solvent-HBD solutes, respectively. The second most important factor in the LSER models in SDS, SC, and 1-octanol systems is coefficient b, which represents hydrogen bond donor strength of the interactive (aqueousorganic) phases. The b coefficient is proportional to the difference in HBD acidity of the organic phase (e.g., l-octanol or micelles) and that of the aqueous phase as
where a is the solvatochromic parameter for measuring solvent HBD acidity and subscripts o and aq represent the organic phase (1-octanol or micelles) and the aqueous phase, respectively. B is a proportionality factor. The negative signs for b coefficients (Tables 2-5) show that 1-octanoland two of the micellar systems (SDS and SC) are less acidic than the aqueous phase; i.e., a, < aaq The larger b coefficient means higher HBD strength of the organic phase; thus the relative HBD strength of the systems under study can be ranked as LiPFOS > SDS > SC =- l-octanol. As the HBA strengths of solutes increase, their interactions with the SDS and SC micelles or 1-octanolwould decrease due (38) Zana, R;Guveli, D.J. Phys. Chem. 1985,89, 1687. (39) Ueno, M.; Kimoto, Y.; keda, Y.; Momose, H.; h a , R J. Colloid Interface Sci. 1987, 117, 179. (40) Hashmoto, S.; Thomas, J. K /. Colloid Interface Sci. 1984, 102, 152. 506 Analytical Chemistry, Vol. 67, No. 3, February 1, 1995
to the negative b coefficients. In other words, the more HBA basic solutes favor the more acidic aqueous media over that of the organic phase. It is interesting to note that the sign of the b coefficient for the HBA in the WFOS system (Table 4) is positive, which indicates the HBA bases find the LiPFOS microenvironments more acidic than the bulk aqueous solvent. As a result, in contrast to the other two micellar systems and l-octanol, solutes interact to a greater extent with the LiPFOS as their HBA strengths increase. For the NHI3 subset and HBD solutes (Tables 3 and 5), the b coefficient for LiPFOS is negative, but still the results are consistent in terms of HBD strength of the organic phase; i.e., the b values for LiPFOS are the largest or least negative. These results show that HBA bases have the strongest interactions with the LiPFOS micelles and are least attracted to the SC micelles (which is also evident in Figures 1and 2). This favorable hydrogen-bonding interaction is offset by the relative smaller cavity formation effect (as compared to other micelles) such that solutes have the smallest overall interaction with the WFOS micelles. The a coefficient corresponds to the difference in HBA (basicity) strength of the interactive phases as a =Avo
- Pa,)
(10)
where #3 is the solvatochromic parameter for hydrogen bond acceptor basicity and the subscripts o and aq refer to the interactive organic (l-octanol or micelles) and aqueous phases. A is a proportionality factor. Typically, the a coefficients in the LSER models for aqueous-organic partitioning systems are small and sometimes even negligible (e.g., in eq 3 for the octanolwater system). This is not the case, however, for the LiPFOS system or for HBD solutes for any of the systems (see Table 5). According to the results in Tables 4 and 5 in the LiPFOS system, the second most important factor (after the m coefficient) that determines the extent of solute retention is the a coefficient. According to eq 10, a positive a coefficient means that the HBA strength of the organic phase is greater than the aqueous phase. Thus, based on Table 5, the HBA strength of the systems can be ranked as l-octanol > SC > SDS > LiPFOS. In other words, the SC micelles provide the most HBA basic environments among the three micelles, while LiPFOS micelles have the weakest basic media. The a values in Table 5 are significantly larger than what has been usually observed in the LSER models of similar systems such as log Pow.This has also been the case for the SDS and SC micelles (Table 2, n = 60). Kamlet and Taft had demonstrated the robustness of the LSER models previously. Surprisingly, however, even for the log Powmodel with n = 19, a = 3.01, which is even more sigrdicant than the b coefficient. One might suspect the existence of statistical artifacts; however, there is no apparent reason for it. The correlation coefficients for the LSER models in Table 5 are quite high and the coefficients’ errors are reasonable. The set of 19 compounds should be adequate to provide robust multiple linear regression models. Typically the number of objects for a multiple linear regression should be at least three times the number of independent variables (i.e., a set of 15 compounds should be enough for this case). The overall m and b coefficients in Table 5 are also consistent with the other results shown in Tables 1-4. To further examine this, the LSER model for log Powwas examined by including 13 additional HBD compounds to this set.
Using the extended set of n = 32 (as reported by Kamlet and Taft in ref 24), the coefficient values changed dramatically. The larger set also contained substituted benzoic acids, in addition to substituted phenols and benzyl alcohols. Unfortunately this set could not be extended for the micellar systems due to the following pH limitations in the MEKC systems. In order to prevent the ionization of the new HBD solutes, it would be necessary to operate to pH values much smaller than 7.0. This would create problems since SC would precipitate at lower pH values and the retention behavior in the SDS system become irreproducible.2 Work is underway to examine this group of solutes in other MEKC systems. In spite of anomalous results of Table 5, the overall trend is consistent with the retention behavior of solutes. The migration behavior of the HBD compounds is further examined in Figure 3. The wide range of behavior (represented by three separate lines) among the solutes in this group is a result of different hydrogen-bondingdonor-acceptor balance. Note that the solutes in the HBD group have both HBD and HBA properties, Le., measurable a and j3 values. Overall, the HBD solutes can be divided into three subgroups according to their similar migration behavior (Figure 3): first is halophenols (largest a,smallest j3, Le., strongest HBD), second is alkylphenols and chlorobenzyl alcohols, and third is alkylbenzyl alcohols (smallest a,largest /?). As a result, in the SC system, which is a stronger HBA compared to the other two micellar systems, the strongest HBD solutes in the group (e.g., halogenated phenols) have the largest interactions (Figure 3a, filled squares). This same group of solutes, however, has the smallest retention in the LiPFOS system, which is the strongest HBD among the three micellar systems (filled squares, Figure 3b). An opposite trend is observed for alkylbenzyl alcohols; Le., they have the largest interaction with LiPFOS and smallest affinity for SC micelles. Dipolarhteractions.The coefficientsrepresentsthedifference in dipolarity/polarizability of the interactive organic and aqueous phases as s = S(n*, - n*aq)
9 log k' (40 m M
SDS)
.0.1-
-0.2-
-0.3-
8 -0.4-
{
-3
-0.5-0.8-
k
3-0.7-0.8-0.91, -0.4
.0.2
0
0.2
0.4
0.8
C
(11)
where x* is the solvatochromic parameter for dipolarity/polarizability and S is a proportionality factor. The negative s values show that the solutes experience an environment that has less dipolar/polarizable characteristics than the aqueous phase. This is the case for the main set and for the NHB as well as for the HBA sets (Tables 2-4). However, the results for the HBD set (Table 5) show an anomalous behavior as the positive s values for the HBD set indicate these solutes find a more dipolar environment in the organic phases than in the aqueous media. According to the results for the whole set, solutes experience identical microenvironments in terms of dipolar interactions in all three micellar systems. Based on the s values for the NHB and HBA subsets, however, there exists some differences between the dipolar interactions in different micellar media. As mentioned earlier, some variations in the coefficient values in different sets should simply be attributed to the different number of objects, especially once the main set (n = 60)is compared to the subsets (a = 20). Therefore, it is difficult to differentiate between the changes caused by chemical effects from those due to the regression procedure with different number of compounds in the sets. Another factor that should be considered is the possibility of ion-dipole interactions between solutes and' the ionic groups
of surfactants that are not included by the LSER modeling. In general, dipolar interactions play a minor role in influencing log Pow,retention in reversed phase LC,and retention in MEKC. Polar Functional Group Selectivity. Another useful method for investigating solute-micelle interactions in MEKC is to determine the free energy of transfer of the substituted functional groups from the aqueous phase into the micellar p~eudophase.~~ Functional group selectivity, t, is defined as the ratio of the (41) Yang, S.;Khaledi, M. G. Anal. Chim. Acta 1994, 294, 135.
Analytical Chemistry, Vol. 67, No. 3, February 1, 7995
507
Table 7. Migration Behaviors of Homologous Serks In MEKC. In K = mN, b
Table 6. Effect of Mlcelles on Functional Group Sekctlvity
+
n
r
SE
-0.083 -0.492
4 4
0.9995 0.9984
0.050 0.073
0.060 M SC 0.955 (0.043) -0.659 alkylphenonesC 0.751 (0.095) -1.860
4 4
0.9996 0.9966
0.045 0.099
0.040 M LiPFOS 0.706 (0.026) -1.330 0.622 (0.028) -0.407
4 4
0.9997 0.9996
0.027 0.029
compds
AAGa kJ/mol) . -. .
functional 1 F
c1 Br I
2 3 4 5 6 7 8
9 10 11
CH? CHiCH3 CHzCHzCH3 NHz CHO CN NOz 02CCH3 COCH3 COCHZCHR COCHiCHiCH3 COCHzCHzCHzCH3
12 13 14 15 16 17 18 19 20 COiCHiCH3 21 CHzOH 22 OH-
-0.537 -3.093 -3.947 -5.341 -2.532 -4.753 -7.419 1.869 -0.013 -0.172 -0.543 -0.982 -1.167 -2.950 -5.002 -7.301 -1.007 -2.773 -2.898 -5.069 1.597 1.745
-0.521 -3.357 -4.258 -5.674 -2.570 -4.842 -7.134 3.246 1.925 1.718 0.444
1.565 0.856 -0.650 -2.527 -4.724 -0.525 -2.054 -0.845 -2.556 2.733 1.565
-1.008 -1.709 -1.774 -2.142 -1.820 -3.446 -5.295 1.425 -2.490 -2.795 -2.685 -3.446 -3.990 -5.317 -6.898 -8.511 -2.032 -3.610 -4.816 -6.646 0.420 1.987
The difference in free energy of transfer (AAG) is defmed as AAG -RT In t (tis the functional group selectivity). (1
=
m
0.040 M SDS 0.060 M SC 0.040 M LiPFOS
b 0.04 M SDS
alkylbenzenesb 0.988 (0.048) alkylphenonesC 0.825 (0.071) alkylbenzenesb
alkylbenzenesb alkylphenonesc a
Nc is the number of methylene (CH2) uNts in the side chains.
* Include benzene (N, = O), toluene, ethylbenzene, and propylbenzene.
Include acetophenone (N, = 1), propiophenone, butyrophenone, and valerophenone. Table 8. Hydrophobic (Methylene Group) Selectlvky in MEKC
AAG w/mol)
compds alkylbenzenes propylbenzene
0.04 M SDS 0.060 M SC 0.040 M LiPFOS
-2.656
-2.292
-1.849
-2.230
-2.272
-1.626
-2.298
-2.197
-1.613
-2.052
-1.877
-1.581
-2.182
-2.254
-1.759
-2.078
-1.689
-1.631
ethylbenzene capacity factor of a substituted benzene (ph-R) over the capacity factor of benzene cph-H). Since k’ is directly related to the solutemicelle binding constant (eq %), the functional group selectivity is a direct measure of the interaction of a functional group with micelles as
toluene alkylphenones valerophenone butyrophenone propiophenone alkylphenols kthylphenol Ilrmethylphenol alkylbenzyl alcohols Sphenyl-1-propanol
and
AAG = -RT In t
(13)
where t is functional group selectivity and AAG is the difference in free energy of transfer of a functional group from the aqueous phase to micelles. The differences in free energies of transfer for various functional groups are listed in Table 6. A negative AAG value means that the addition of a functional group R to the parent compound, benzene, leads to an increase in the interaction with the micelles and retention, i.e., t > 1 or k’(Ph-R) > k’(Ph-H). A positive AAG value, on the other hand, has the opposite meaning, i.e., t < 1or k’(7h-R < k’(ph-H). The larger negative AAG shows more favorable and larger positive AAG indicates less favorable interactions between the substituted solutes with micelles (as compared to that between the parent solute-micelles). As shown in Table 6, for nonpolar functional groups (halogens and alkyl) (1-7), the AAG values are all negative, and as expected, more hydrophobic and larger groups interact stronger with the micelles. The extent of interactions of these groups with the SDS and SC micelles are nearly equivalent and much larger than that with LiPFOS (with the exception of the F group, which has a stronger interaction with the fluorinated surfactant). The second set consists of HBA functional groups (8-21), which show stronger interactions with the LiPFOS than SDS 508 Analytical Chemistry, Vol. 67,No. 3,February 1, 1995
phenethyl alcohol
micelles with a much smaller a€finity for the SC micelles. These results can be attributed to the fact that LiPFOS micelles are stronger HBD acids than SDS and SC, which confirms the conclusion based on LSER The differences in AAG values between the three surfactants are especially large for the small, “polar”functional groups (e.g., 8-13 or 17-19 in Table 6). The larger, more hydrophobic functional groups (e.g., alkyl ketones 14 -16) have favorable interactions even with the SC micelles (i.e., due to m coefficients in LSER models). Interestingly, the alcohol functional group (21) behaves like a HBA rather than a HBD. As mentioned earlier, benzyl alcohols have dual acceptordonor characteristics as shown by their ,!?and a parameters (Table 1). Another interesting observation is the negative AAG values for “polar”functional groups (e.g., 9-13) in the LiPFOS and SDS micelles, which means that substitution of a “polar” functional group on the benzene ring would lead to stronger interactions and larger retention in MEKC (i.e., k’(Ph-R) > k’cph)). For example, “polar”, less hydrophobic compounds such as nitrobenzene, benzonitrile, or benzaldehyde are retained longer than benzene with the LiPFOS or SDS micelles. This is mainly due to
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Figure 4. MECK elution patterns for (a, left) 40 mM SDS, UV detection at 1= 210 nm, (b, middle) 40 mM LiPFOS, UV detection at , I = 214 nm, and (c, right) 80 mM SC, UV detection at 1 = 254 nm. Experimental conditions: 50 mM phosphate, pH 7.0, 20 kV. See Table 1 for peak identification.
the hydrogen bonding between the acceptor functional groups and donor micelles. Therefore, the general belief that solute retention in MEKC is according to their lipophilic character is not completely accurate and is sometimes even misleading. For surfactant systems such as LiPFOS, this is certainly not t r ~ e . 3 ~ The only HBD functional group (22), has a stronger interaction with the SC micelles (which is the strongest HBA micelle) and has the least afsnity for the fluorocarbon micelles. Homologous Series and Hydrophobic Selectivity. Studies of migration behavior of homologous series can also provide useful information about the underlying interaction mechanisms. Homologous series have been used extensively for probing the structure of micelle^.^^-^^ There is a linear relationship between logarithm of capacity factor, In k’, and the number of CHZunits in alkyl homologous ~ e r i e s . ~The ~ - ~linear ~ increase in In k’ of a homologue upon addition of a CH2 group to the alkyl chain is a measure of hydrophobic interaction in a micellar system. Table 7 shows excellent correlations between In k’ vs N, for two classes of alkyl homologous series, alkylbenzenes and alkyl aromatic ketones, in the MEKC systems. The slope of In k’ vs N, is a measure of retention (or interaction) of a CH2 group and is called methylene group selectivity or hydrophobic selectivity. Again, the free energy difference is directly related to hydrophobic selectivity (AAG = -RT In a(CH2)). As shown in Tables 7 and 8, the a(cHd and AAG values are different for the two homologous series in all three micellar systems. The change in free energy of transfer of a methylene group (AAG) from the bulk aqueous media to micelles is a function of the microenvironment polarity of the localized homologous compounds. The increasingly nega(42) Khaledi, M. G.;Peuler, E.; Ngeh-Ngwainhi, J. Anal. Chem. 1987,59,2738. (43) Khaledi, M. G. Anal Chem. 1988,60, 876. (44)Yang,S.; Kruk, L.; Khaledi, M. G. 1.Chromatog. 1994,664, 1. (45) Gmshka, E.;Colin, H.; Guiochon, G. /. Chromutogr. 1982,248,325. (46) Colin, H.;Guiochon, G.; Yun, Z.; Diez-Masa,J. C.; Jandera, P.1. Chromatogr. Sci. 1983,21,179.
tive AAG values show that the homologues are penetrating into more hydrophobic environments of micelles and experience an overall larger difference in polarity between the bulk aqueous phase and the micellar aggregates. For example, the homologues with longer alkyl chain lengths in a series occupy the more hydrophobic environment of a micelle. This is reflected in more negative AAG(cH~ values. Apparently, alkylbenzenes are located in more hydrophobic environments than alkylphenones (Tables 7 and 8). Likewise, different classes of homologous series occupy various locations in/on micelles, depending on the polar nature of their class functional groups. For example, the alkyl-substituted compounds from four different classes (Table 8) find SDS and SC environments more hydrophobic than the LiPFOS micelles. Again this is consistent with the LSER results and polar functional group selectivity. Similarly, different AAG(cH,) values from the same series in two different micelles indicate that the homologous pairs do not experience the same microenvironments in those organized media. The results presented in Tables 7 and 8 illustrate these points. CONCLUSION
The differences in chemical selectivity between the three micellar systems used in this study are clearly illustrated in Figure 4, where different elution patterns are observed. For the fluorocarbon micelles (Figure 4b), the HBA solute (29;see Table 1) is the longest retained and the HBD phenolic compound (38) has the shortest retention. The opposite is observed for the SC micellar system (Figure 4c). In summary, the interactions of the NHB compounds (Table 2) with the SDS and SC micelles are closely related, although they find the environments of SDS micelles slightly more lipophilic. Their dipolar interactions with the SC micelles are slightly stronger. However, this effect is offset by a more endoergic cavity formation in SDS micelles (larger positive m) and less exoergic hydrogen-bonding interactions between acceptor solutes and Analytical Chemistry, Val. 67, No. 3, February 7, 1995
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donor micelles. Even though this group was termed NHB, they are in effect weak HBA solutes with B 5 0.20. Overall, they prefer the SDS micelles slightly more than the SC micelles. Their interactions with the LiPFOS micelles are significantly smaller than those for SDS and SC systems, mainly due to a relatively much smaller m and more negative s values. This is in spite of more favorable hydrogen bonding between the weak acceptor solutes and stronger HBD micelles of LiPFOS (as compared to SDS or SC) as shown by the less negative b coefficient (Table 2). The HBA group (Table 4) seems to prefer SDS micelles over the SC micelles because of the more acidic, dipolar, and less cohesive environments that they experience in the former. These solutes have a much stronger hydrogen bonding with the donor LiPFOS micelles (positive b coefficient). The HBD solutes (Table 5), on the other hand, seem to have stronger interactions with the SC micelles. The positive a
510 Analytical Chemistry, Vol. 67, No. 3, February 1, 1995
coefficients (Tables 2 and 5) indicate that the SC environment is more HBA basic than SDS and LiPFOS. This is also confumed through group selectivity studies. ACKNOWLEDGMENT
We gratefully acknowledge a research grant (GM 38738) from the US.National Institutes of Health. We also thank 3M Co. for the donation of LiPFOS surfactant. Received for review August 11, 1994. Accepted November 18, 1994.@ AC940806F 0 Abstract
published in Advance ACS Abstracts, December 15,1994.
