Ind. Eng. Chem. Res. 1991, 30, 1222-1231
1222
better methods of estimating these coefficients from fundamental models. Acknowledgment This paper grew out of work based on a project supported by the National Science Foundation under Grant No. CBT 88821005. Supplementary Material Available: Tables listing experimental and predicted diffusion coefficienta for the systems acetone (1)-benzene (2)-carbon tetrachloride (3),methanol (1)-1-propanol (2)-isobutanol(3), and acetone (1)-benzene (2)-methanol (3) (27 pages). Ordering information is given on any current masthead page. Literature Cited Alimadadian, A,; Colver, C. P. A New Technique for the Measurement of Ternary Diffusion Coefficients in Liquid Systems. Can. J. Chem. Eng. 1976,54, 208-213. Bandrowski, J.; Kubaczka, A. On the Prediction of Diffusivities in Multicomponent Liquid Systems. Chem. Eng. Sci. 1982, 37, 1309-1313. Cullinan, H. T. Concentration Dependence of the Binary Diffusion Coefficient. Ind. Eng. Chem. Fundam. 1966,5, 281-283. Cullinan, H. T.; Toor, H. L. Diffusion in the Three-Component Liquid System Acetone-Bemendarbon Tetrachloride. J. Phys. Chem. 1965, 69, 3941-3949.
Cullinan, H. T.; Cusick, M. R. Predictive Theory for Multicomponent Diffusion Coefficients. Ind. Eng. Chem. Fundam. 1967,6, 72-77. Krishna, R. Ternary Mass Transfer in a Wetted Wall Column. Significance of Diffusional Interactions. Part 11: Equimolar Diffusion. Trans. Inst. Chem. Eng. 1981, 59,44-53. Krishna, R. Model for Prediction of Multicomponent Distillation Efficiencies. Chem. Eng. Res. Des. 1985, 63, 312-322. Krishna, R.; Taylor, R. Multicomponent Mass Transfer-Theory and Applications. In Handbook of Heat and Mass Transfer; Cheremisinoff, N. C., Ed.; Gulf Publishing Co.: Houston, TX, 1986; Vol. 2,Chapter 7, pp 259-432. McKeigue, K.; Gulari, E. Affect of Molecular Association on Diffusion in Binary Liquid Mixtures. AZChE J. 1989, 35, 3W310. Reid, R.C.; Prausnitz, J. M.; Poling, B. Diffusion Coefficienta. The Properites of Gases and Liquids, 4th ed.; McGraw-Hill: New York, 1987;Chapter 11, pp 577-631. Renon, H.; Asselineau, L.; Cohen, G.; Raimbault, C. CaZcuZ sur Ordinateur des Equilibres Liquide- Vapeur et -Liquide-Ziquide;Editions Technip, 1971. Shuck, F. 0.; Toor, H. L. Diffusion in the Three-Component Liquid System Methyl Alcohol-n-Propyl Alcohol-Isobutyl Alcohol. J. Phys. Chem. 1963,67,540-545. Vignes, A. Diffusion in Binary Solutions. Ind. Eng. Chem. Fundam. 1966,5, 189-199. Wesselingh, J. A. Is Fick Fout. Procestechnologie 1985, No. 2,3943. Wesselingh, J. A.; Krishna, R. Elements of Mass Transfer; Ellis Horwood: Chichester, U.K., 1990. Received for review October 9, 1990 Revised manuscript received January 18, 1991 Accepted February 4, 1991
Chemical Complexing Agents for Enhanced Solubilities in Supercritical Fluid Carbon Dioxide Richard M.Lemert and Keith P.Johnston* Department of Chemical Engineering, The University of Texas a t Austin, Austin, Texas 78712
The effect of the strong Lewis base tri-n-butyl phosphate (TBP) on the solubility of benzoic acid and hydroquinone (HQ) in supercritical fluid carbon dioxide is reported. TBP is shown to be a much stronger cosolvent for these solutes than methanol. For example, 2% TBP increases hydroquinone’s solubility by a factor of 250. The principles of chemical reaction equilibria are combined with the Peng-Robinson equation of state in order to model these results. The behavior of the hydroquinone-carbon dioxide-TBP system is shown to be attributable to the formation of an HQ-TBPZ complex having an enthalpy of formation of -18.9 kcal/mol. The performance of this chemical model is compared to that of a recently developed density-dependent local composition (DDLC)model. Introduction Ten years ago, studies of supercritical fluid extraction were usually either empirical investigations into the fractionation of complex naturally occurring matrices or rigorous investigations into the behavior of much simpler model systems (see, for example, Johnston, 1984, Paulaitis et al., 1983). Since then, this gap has been bridged to a significant extent as discussed in several reviews (Brennecke and Eckert, 1989a; Brunner, 1988; Johnston et al., 1989~).In some cases, it is now possible to predict the phase behavior of these systems as a function of the molecular structure of the components (Johnston et al., 1989d), something that is particularly useful in process design and evaluation. This early work showed fairly quickly that pure supercritical fluid solvents have some significant limitations for certain separations. Fluids with convenient critical temperatures (defined here as being between 0 and 100 OC), for example, are usually nonpolar.
* T o whom correspondence should be addressed. 0888-5885/91/2630-1222$02.50/O
As a result they are good solvents for solutes such as naphthalene and anthracene (Kurnik et al., 1981; McHugh and Paulaitis, 1980), but are unsuitable for amino acids or sterols (Krukonis and Kurnik, 1985; Wong and Johnston, 1986). In addition, solubilities and selectivities (defined as the ratio of solubilities) are determined primarily by the solute’s vapor pressure (Dobbs and Johnston, 1987; Kurnik and Reid; 1982; Johnston et al., 1989d). Much of the recent research in this area has been designed to enhance the solubilities of polar solutes in these solvents, with the greatest success coming from the use of cosolvents. Nonpolar cosolventa were the first to be studied and were shown to be useful in increasing solute solubilities (Brunner, 1983; Dobbs et al., 1986). This results from their greater polarizability compared to the smaller primary solvent molecules, which leads to increased dispersion forces in the solution. Because these forces are nonselective,however, there is usually no improvement in the selectivity of the process. Polar cosolvents usually produce much larger solubility enhancements (Dobbs et al., 1987; Schmitt and Reid, 1986; van Alsten, 1986),and 0 1991 American Chemical Society
Ind. Eng. Chem. Res., Vol. 30, No. 6, 1991 1223 because the forces between these cosolvents and different solutes are usually more specific, improvements in selectivities are usually also observed (Dobbs and Johnston, 1987). A more recent development in the field has been the use of surfactants to form water-in-oil reverse micelles and microemulsions in supercritical ethane and compressed liquid propane (Fulton et al., 1989; Johnston et al., 1989b). The properties of these microemulsion system are readily adjustable with pressure in the liquid-fluid region of the phase diagram (Yazdi et al., 19901, and their ability to solubilize hydrophilic amino acids has been demonstrated and characterized (Lemert et al., 1990). An important phenomenon in these systems is the density augmentation of both solvent and cosolvent molecules about the solute. This is indicated by the observation of extremely large negative solute partial molar volumes at infinite dilution, with values as great as -16000 cm3/mol near the solvent’s critical point (Eckert et al., 1986, Debenedetti, 1987). Various spectroscopictechniques have been used to verify the existence of these augmented densities (sometimes called clusters) in both pure (Kim and Johnston, 1987a; Brennecke and Eckert, 1989b) and mixed (Kim and Johnston, 1987b; Johnston et al., 1989a) solvent systems. These aggregations are statistical entities in that the solvent and cosolvent molecules interact with a given solute molecule in a nonstoichiometric manner. In this paper we consider phosphate esters as cosolvents, a class of materials often used in conventional liquid-liquid extraction but previously untested in supercritical fluid solvents (King, 1987). These compounds are known to form reversible stoichiometric complexes with alcohols, carboxylic acids, and phenols (Aksnes and Albriktsen, 1986; b k l , 1981; Munson and King,1984; W d y and Coleman, 1983; Wardell and King, 1978). The ester chosen for this work is tri-n-butyl phosphate (TBP), which is readily available, soluble in many nonpolar solvents, and widely characterized (Schulz and Navratil, 1984). The original interest came from the nuclear industry because of TBP’s ability to recover and purify uranium and plutonium, but its ability to extract organic acids from aqueous media was soon recognized (Pagel and McLafferty, 1948). Indeed, TBP has been investigated for recovery of organic compounds from both wastewater streams (Jagirdar, 1982; Joshi et al., 1984) and fermentation broths (Cho and Shuler, 1986; Matsumura and Markl, 1986). Our primary objective is to demonstrate that TBP is an extremely potent cosolvent for organics containing acidic functionality,because of reversible chemical complexation between the solute and the cosolvent. To facilitate the analysis of the results, all of the measurements are made in the solid-fluid equilibrium region where the crystalline solid phase is assumed to be pure. In addition, we seek to demonstrate that the data can be modeled appropriately with an equation of state that incorporates the principles of chemical equilibrium. To further demonstrate the capabilities of this approach, we compare this model to a recently developed density-dependent local composition (DDLC) model. Experimental Section A schematic diagram of the experimental apparatus used in this study is shown in Figure 1. The solvent mixture flows from a solvent reservoir through a heat exchanger, two stainless steel saturators (each 0.79 cm i.d. X 15 cm long) in series, a high-pressure chromatographic switching valve, and a vibrating tube densitometer (Mettler-Paar DMA 512). The flow rate is controlled by a micrometering valve that also reduces the pressure to ambient, and
VENT
Figure 1. Microsampling apparatus for measuring solid-fluid equilibria.
pressure is controlled by a forward-pressure regulator. Pressure was measured to within fO.1% using a Heise 710A digital pressure gauge, and densities were determined to an accuracy of *5.0 X 1Vg/cm3 based on a calibration with pure carbon dioxide and an accurate equation of state (Ely, 1986). Solvent mixtures were prepared by adding a measured amount of TBP to a known amount of COz (Linde Bone-Dry Grade) using the procedure of Dobbs et al. (1986). Sampling was accomplished with the microsampling technique of Dobbs et al. (1986), using a sampling loop with 110-pL internal volume. Other details of the equipment and procedures used are available elsewhere (Dobbs et al., 1986; Lemert and Johnston, 1990). The TBP used in the study was a gift of FMC (Princeton, NJ) while methanol and benzoic acid were obtained from Fisher (ACS) and hydroquinone from Aldrich (no. 24,012-5). All materials were used as received. Analyses were performed on samples collected in ethyl acetate (Fisher ACS), by using a Hewlett-Packard 5890A gas chromatograph equipped with an HP7673A automatic injedor. A 15-m BP-5 capillary column (Hewlett-Packard), 0.32 mm i.d. X 0.52 pm film thickness, was used for the hydroquinone analyses, while a BP-20 column having the same dimensions (SGE, Inc.) was used for benzoic acid. A cool on-column injection technique was used for both solutes. Hexamethylbenzene (Fluka purum) was used as an internal standard for hydroquinone, and benzoic acid was determined using a calibration curve based on peak height due to significant tailing of the solute’s peak. TBPs low volatility allowed it to be recovered quantitatively during the sampling, and measured TBP concentrations were in agreement with the expected values. Results were reproducible to within f2%. In a preliminary set of experiments, samples of different prospective solutes were placed in an annealed Pyrex tube, 75 mm long X 6 mm 0.d. X 2 mm id., and contacted with a C02-TBP (1.9 mol %) solvent mixture at 35 “C and 140 f 2 bar. The purpose of the test was to identify and eliminate from consideration those systems in which a liquid phase formed at the test conditions. In addition to benzoic acid and hydroquinone, the solutes tested included stearic acid (Aldrich no. 17,536-6),2-naphthol(Aldrich no. 18,550-7), resorcinol (Aldrich no. R40-61, and catechol (MCB no. CXO550-1). The view-cell assembly (Dobbs, 1986; Lemert and Johnston, 1989) was shielded to prevent injury in the event of tube failure, and the phase behavior was observed visually. Theory The usual approach for modeling the phase behavior of supercritical fluid systems is to treat the molecular in-
1224 Ind. Eng. Chem. Res., Vol. 30, No. 6, 1991
teractions in the fluid phase with a completely physical model. This approach assumes that the various compounds in the mixture retain their identity as independent chemical species; that is, no chemical reactions take place. The structure of the solution may be described by a density-dependent local composition (DDLC) model (Mathias and Copeman, 1983; Luedecke and Prausnitz, 1985; Stryjek and Vera, 1986a). Recently, a DDLC model was developed in order to treat supercritical fluid solutions (Johnston et al., 1987). The parameters in the model are calculated on the basis of the electronic structures, molecular sizes (polarizabilities),and molecular interactions of the various components in the system. It is fairly predictive for nonpolar systems and can give qualitative predictions of the behavior of polar systems when the binary attraction constants are calculated from component solubility parameters. The solute’s solubility is determined by equating its fugacity in the solid state with its fugacity in the supercritical solution, which results in
The key variable in this expression is the fugacity coefficient, &, which is given in the DDLC model by
the solute and the cosolvent. The reaction is written as qQ + rR C (3) Q
where C refers to the complex (Le., Q,.R,), with q and r the stoichiometric coefficients. The equilibrium constant for this reaction is
where zi represents the “true” mole fraction of species i, @i represents its fugacity coefficient, and the standard state is taken as the ideal gas a t the system temperature and composition. The “true” mole fractions (zi) used in eq 4 are the mole fractions of the various species actually present in the solution. For example, solute molecules would be present as both the free solute (zQ)and as part of the complex (zc). Experimentally,however, the quantities actually measured are the “apparent” mole fractions (yi) of the components in the mixture. In other words, YQ includes not only the free solute molecules but also those in the complex. This terminology can be somewhat confusing, but it is used here to maintain consistency with the earlier papers in this area. It is suggested, however, that the term “bulk” mole fraction could be used in place of “apparent” mole fraction. The two types of mole fractions are related through material balances, which for the solute and the cosolvent, gives nQo = nQ + qnc (5) and nRo = nR + mc
The first term is the repulsive contribution to the fugacity coefficient, calculated from a hard-sphere equation of state. The second term is a long-range attractive contribution, obtained by using a van der Waals 1mixing rule, that accounts for nonspecific molecular interactions. Finally, the last term takes into account the specific shortrange forces that depend on the strength of the unlike-pair interactions. An alternative approach may be used to model the behavior of systems with a high degree of association. This approach retains the physical interactions described by an equation of state, but superimposes on this an appropriate series of chemical reaction equilibria. The various species can be assumed to form dimers, trimers, tetramers, etc., with appropriate assumptions made regarding the equilibrium constants for the different reactions (Heidemann and Prausnitz, 1976). Both association (i-i interactions) and solvation (i-j interactions) can be treated in this manner, and the resulting mathematics can be simplified significantly if particular stoichiometries can be assumed. The approach has been applied to the modeling of vapor-liquid equilibrium data using the Redlich-Kwong equation of state (Hu et al., 1984; Hong and Hu, 1989) and has been used by Donohue with the associated perturbed anisotropic chain theory (APACT) equation of state to explain the effects of cosolvents in supercritical fluid systems (Walsh et al., 1987, 1990). In this paper, we develop a chemical equilibrium model based on the Peng-Robinson equation of state (Peng and Robinson, 1976). The system being modeled contains three components, the solute Q, the cosolvent R, and an inert solvent S, and it is assumed that the only reaction occurring is the formation of a stoichiometric complex with
(6) The terms on the left of the equal signs are the total number of moles of component i (e.g., the solute Q ) in any form, and the terms on the right are the number of moles of component i present as species j (e.g., the complex). The apparent mole fractions are defined as yi = nio/no = nio/(nQo+ nRo + nso) (7) By introduction of the ratio of total apparent moles to total true moles no/n,, where n, = nQ + nR + ns + nc, the apparent mole fractions can be written in terms of the true mole fractions as ys(no/nt) = 2s
(8)
yQ(no/nt) = ZQ + q Z C
(9)
+ rzc
(10)
and Y R ( ~ ~ / =~ ZR J
with (no/n,) = 1 + (q
+ r - l)zc
(11)
Note that both types of mole fractions sum to unity but that the mole fractions for the individual components (e.g., the solute) are equal only when zc is zero; i.e., when no complex has formed. The solution of eq 4 requires the determination of the fugacity coefficients of the various species in solution. These are complex functions of the composition of the mixture, but tremendous simplification results from the choice of an appropriate approximation for the properties of the complex. Thus, the attraction (ai) and size (bi) parameters are determined in the conventionalmanner for the Peng-Robinson equation for the various pure components, while the following combining rules are used for the complex (Hong and Hu, 1989; Hu et al., 1984);
Ind. Eng. Chem. Res., Vol. 30, No. 6, 1991 1225
1
1.41
J
and
1.2 -
The mixture constants, ci and
6,are determined from
-
e
0.8 1.0 0.6
and
-
0.4-
Empirical binary interaction parameters kij are used in eq 14 to adjust the unlike-pair attraction constants from the geometric mean. Because these parameters have different values for the different interactions, they cannot be factored out of eq 14, and the equation is therefore in its simplest form. If all of the kij are set to zero, however, eqs 8-12 can be used to rewrite this equation as
Similarly, eq 15 can be rewritten as
6 = (no/nt)CYkbk k
(17)
FO 0
-
o 0
0 0
0 0
E 0
A
0.2-
A
A
A
A
00
Pressure (Bar) Figure 2. Benzoic acid solubilities in supercritical carbon dioxide at 35 O C with various cosolvents: (A) pure CO,; ( 0 ) 3.5 mol % acetone (Dobbs et al., 1987); (0) 3.5 mol % methanol (Dobbs et al., 1987); ( 0 )1.1 mol % TBP;(-1 correlated using the DDLC model (see Table 11). Table I. Benzoic Acid Solubilities in a Mixed Carbon Dioxide-TBP (1.10 mol % on a Solute-Frec Basis) Solvent at 35 OC P, bar p, satd soln, g/cm9 Y2 ~
Differentiating eqs 14 and 15 with respect to ni and substituting the results into the general expression for the fugacity coefficient (Stryjek and Vera, 1986b) produces
bi - 1) - In (2 - B)In 4i = -(Z b
(-
2(2t2)B)(i)
3 - 7
b
Z
+ (1 + 2 '12)B
Z - (1 - 2 '/')B
)
(18)
137.8 138.1 172.4 172.4 239.8 241.2 287.1 287.4
0.8446 0.8455 0.8808 0.8786 0.9217 0.9223 0.9448 0.9445
7.74 x 10-3 7.77 x 10-9 9.23 X 8.93 X 9.87 x 10-3 9.83 x 10-3 10.3 x 10-3 10.4 x 10-3
procedure with different values of Kq to obtain the minimum in the function
where 2 is the compressibility of the mixture, and A and B are as defined by Peng and Robinson. The i and j indices represent the "true" species present in solution, while the index k represents the "apparent" components of the mixture. To use these equations to calculate a solubility, the first step is to assume a reasonable stoichiometry for the complex. An estimate of the "true" composition of the mixture is made, and eq 18 is solved for the fugacity coefficients of the various species. For the first iteration it is convenient to assume that no complex has formed, i.e., that zc = 0 and n,/n, = 1, and that the true composition of the solution is the m e as the experimental composition. The solute's true mole fraction can then be determined from
To obtain zR and Z C , this value is inserted into eqs 4 and 10, and these equations are solved simultaneously. A convenient way to do this is to use eq 10 to develop an expression for zR in terms of zc, substitute this expression into eq 4, and solve the resulting polynomial for zc. Notice that this also requires that a value for K , has been specified. Once zc has been determined, a new estimate of no/& is obtained using eq 11. The procedure is repeated to convergence of the various true mole fractions, at which point eq 9 can be used to calculate the predicted value of y~ The equilibrium constant is obtained by repeating the
Not only is the precision in the estimated value of K , improved by examining several different cosolvent concentrations, but this is also required in order to be able to differentiate between various feasible complex stoichiometries.
Results and Discussion Solute Selection. As pointed out earlier, TBP is known to form strong hydrogen bonds with alcohols, phenols, and carboxylic acids. Several phenols and acids were considered for this study, but of these only benzoic acid and hydroquinone were found convenient. Resorcinol and catecho1were not used, for example, because a liquid phase formed during preliminary testing when they were exposed to the C0,-TBP test mixture. Benzoic acid and hydroquinone, on the other hand, exhibited only solid-fluid equilibrium at the same conditions. It is interesting to note that, on the basis of visual observationsof the systems that formed a liquid phase, the liquid formed by the fluid phase condensing rather than by the solute phase melting as has been described elsewhere (Lemert and Johnston, 1989). Higher pressures and/or temperatures might have prevented the liquid phase from forming, but since the test was conducted only to screen potential solutes this was not investigated. Solubility Behavior. In Table I and Figure 2, data are shown for the C02-benzoic acid-TBP system. For com-
1226 Ind. Eng. Chem. Res., Vol. 30, No. 6, 1991
lo.?
I
10.31
Table 11. Hydroquinone Solubilities in Binary Solvents Containing Methanol or TBP in Carbon Dioxide. Cosolvent Concentrations &ported on a Solute-Free Basis P,bar p , satd soh, g/cm3 YZ 2.8% Methanol, 35 "C 6.22 X lo4 0.7524 103.4 6.57 X lo4 0.7945 128.1 7.36 X 0.8287 153.2 7.63 X 0.8548 177.2 7.74 x 104 0.8544 177.2 8.43 x 10-6 0.8767 203.0 8.81 X 10" 0.9068 252.9 9.22 X 0.9409 327.8
O.O008% TBP, 35 O C 10.6 50
150
250
350
Pressure (Bar) Figure 3. Hydroquinone solubilitiesin supercritical carbon dioxide containing different concentrations of TBP at 35 O C : (m) 8.0 X lo-' mol %; ( 0 )0.099 mol % ( 0 )0.62 mol %; ( 0 )2.0 mol %; (-) correlated using the DDLC model (see Table 11).
IU
100
200
300
400
Pressure (Bar) Figure 4. Hydroquinone solubilities in supercritical carbon dioxide containing either TBP or methanol at 35 O C : ( 0 )2.8 mol % methanol; ( 0 )2.0 mol % TBP; (-) correlated wing the DDLC model (see Table 11).
parison, benzoic acid solubilities in C02,COz-acetone (3.5 mol %), and COpmethanol(3.5 mol %) mixtures are also given (Dobbs et al., 1987). TBP is the strongest of the three cosolvents shown, since it affects benzoic acid as much as either of the other two cosolvents even though it is present at only one-third the concentration. However, benzoic acid does not provide a stringent test of the cosolvent since it is already appreciably soluble even in pure COP It is also well-known to form dimers in solution, setting up a competing equilibrium that limits the effect produced by the cosolvent. TBP has a much more significant effect on the solubility of hydroquinone, as shown in Table I1 and Figure 3 (Johnston et al., 1989~).Hydroquinone's solubility increases by a factor of 250 with only 2.0 mol % TBP in the solvent mixture. Unlike benzoic acid, hydroquinone is relatively insoluble in pure COz, and there is therefore greater opportunity for enhancement in this system. To further illustrate this enormous enhancement of hydroquinone's solubility, Figure 4 compares the effect of 2.0 mol % TBP and 3.8 mol % methanol. Even though the methanol concentration is nearly twice that of the TBP,
104.4 104.8 172.8 174.8 241.5 308.8
0.7336 0.7354 0.8403 0.8459 0.8981 0.9344
7.81 X 10" 6.66 X 10" 8.14 X lo4 9.90 x lo" 10.8 X 10" 11.2 x lo"
105.1 173.5 241.5 308.8
0.0008% TBP, 45 OC 0.5875 0.7862 0.8578 0.8980
1.10 x 10" 1.24 X 1.50 X 10" 1.68 X lo-'
105.1 172.1 239.5 309.2
0.099% TBP, 35 "C 0.7417 0.8459 0.8980 0.9362
1.51 X 1.92 X 1.35 X 2.58 X
104.4 172.4 240.8 307.1
0.62% TBP, 35 "C 0.7698 0.8595 0.9081 0.9409
2.44 X lo-' 2.66 X lo-' 2.88 X lo-' 3.26 X lo-'
104.1 172.1 240.1 306.8
0.62% TBP, 45 "C 0.6378 0.8050 0.8543 0.9064
1.98 x 3.09 X 3.36 X 3.74 x
10-4 lo-' lo-' 10-4
137.8 179.9 179.9 221.1 261.9 299.3 340.8
2.0% TBP, 35 "C 0.8644 0.8913 0.8909 0.9154 0.9351 0.9501 0.9657
2.55 x 2.34 x 2.29 x 2.43 x 2.33 x 2.31 X 2.46 x
10-3
10" 10" 10" lo6
10-3 10-3 10-3 10-3 lo4 10-3
the latter produces solubilities that are 25 times greater. Unfortunately, data are not reported for the binary mixture of hydroquinone and COP The isotherm obtained with the solution containing 8.0 X lo-" mol % TBP was supposed to provide this data, but residual TBP was present at detectable levels. The hydroquinone solubilities obtained under these conditions are at the limit of detectability for this procedure, and it was therefore decided that there was little to be gained from attempting to use purer solvent. It should also be pointed out that these results are consistent with the single data point reported for the binary mixture at 55 "C by Krukonis and Kurnik (1985) which supports the use of this isotherm for the determination of the binary solute-solvent interaction parameters. The solid lines drawn in Figures 2-4 represent the predictions of the DDLC model. In Figure 2, only the regressed isotherm for TBP is shown since the results for the other cosolvents are available elsewhere (Johnston et al., 1987). The values of the attraction constants, listed in Table 111,were either regressed from the data or taken from the literature (Wong, 1986),while selected physical
Ind. Eng. Chem. Res,, Vol. 30, No. 6, 1991 1227 Table 111. Regressed Values of the Solvent-Solute (a and Solutdosolvent (ea)Attraction Constants, Obtained from the DDLC Equation of State for Supercritical Carbon Dioxide at 35 OC 107a12, 107azs, solute cosolvent baracme bar.cme % AAD" benzoic acid methanol 1.52b 3.866 18.5 TBP 1.52b 12.1 2.79 hydroquinone methanol 1.35 5.70 16.0 TBP 1.35 21.7 26.9
i
0
0
0
0
0
10'~
*
Average value of ((ysrp - y d c ) / y m ) x 100. Wong, 1986.
properties used in the correlations are listed in Table IV. In the C02 (1)-hydroquinone (2)-TBP (3) system, u12was regressed from the data for the 8.0 X lo4 mol % TBP isotherm, while all of the remaining data for the system were used in the regression of ~ 2 3 .The model agrees well with the experimental data for the lowest and highest TBP concentrations but underpredicts solubilities for the two intermediate isotherms. Consider the behavior of each solute with a given cosolvent, e.g., methanol. On the basis of the values of a23 in Table 111, hydroquinone's interactions with methanol are roughly 50% stronger than are benzoic acid's. This is because hydroquinone is a stronger acid than benzoic acid, as reflected by the acid component solubility parameters listed in Table IV, so that it is able to interact with methanol's basic nature to a greater extent. Since methanol also has a significant acidic character, hydroquinone's basicity also contributes to the strength of these interactions. Similar arguments can be used to explain the relative strengths of the hydroquinone-TBP interactions compared to those between benzoic acid and TBP. In this case, however, it is unlikely that TBP has any acidic character to interact with hydroquinone's basicity. It is also informative to compare the strengths of the interactions of each cosolvent with a given solute. For both solutes, the interactions with TBP are 3-4 times as strong as those with methanol. Part of this is because TBP is a much larger molecule (see Table IV), which makes it more polarizable. This influence can be treated with component solubility parameters (Dobbs et al., 1987). It is likely that the more important factor, however, is the relative strengths of the hydrogen bonding, or equivalently, the acid-base forces between the solutes and the cosolvents. Although accurate acid-base component solubility parameters are not available for TBP, TBP is clearly more basic than methanol. It is suggested that FTIR and/or NMR studies would be useful in quantifying these observations. The results of applying the chemical model to the data of Figure 3 are shown in Figure 5. The solvent-solute
10-6'
50
150
250
I
350
P r e s s u r e (Bar) Figure 5. Hydroquinone solubilities in supercriticalcarbon dioxide containing different concentrations of TBP at 35 O C : (W) 8.0 X lo-' mol %; (0) 0.099 mol %; ( 0 )0.62 mol %; (0) 2.0 mol %; (-) correlated using the chemical equilibrium model with klz = 0.167, Kq = 59850 bar-2.
binary interaction parameter (kl2) was fit to the 8.0 X lo4 mol % TBP isotherm, and K was adjusted to give the optimum fit to the rest of thee8ata. All other binary interaction parameters were zero. The best results were obtained when the stoichiometry of the complex was assumed to be HQ.TBP2, where HQ represents the hydroquinone. Excellent agreement with the experimental data is seen at all TBP concentrations, in contrast to the performance of the DDLC model. Figure 6 plots the predictions of the chemical model as a function of TBP concentration (expressed on a solutefree basis). A t low levels of TBP, the total amount of hydroquinone in solution is independent of the cosolvent concentration, but it is strongly dependent on pressure (or, more directly, density). Very little of the complex is formed under these conditions, and the effect of pressure on the fugacity of the solute dominates the behavior of the system. As more cosolvent is added to the system, a point is reached where the solute's solubility becomes a strong function of the cosolvent concentration and only a weak function of pressure. In this region most of the hydroquinone in solution is in the complex and the chemical term dominates the pressure effect. This is shown more clearly in Figure 7, where the ordinate gives the fraction of the total dissolved hydroquinone that is in the complex. Kim and Johnston (1987a) reported a similar saturation of the hydrogen bonding in the phenol blueCHFa system
Table IV. Physical Properties and Component Solubility Parameters of the Solids and Cosolvents Used during DDLC Modeline T,,O C P,,bar PMt(35 "C),lO'bar b,' cma/mol uL, cms/mol benzoic acid 4792 45.62 359 65 1044 hydroquinone 5576 74.56 1.026 61.7 78.7 methanol 513* 79.98 21.0 41.7O TBP 6631° 158.9 274.012 hT, ( c a l / ~ m ~ ) ~hD,/ ~(cd/cma)1/2 60, (cal/cm3)1/2 61, (cd/cma)1/2 a*, (cd/cms)1/2 P,(cd/cma)'/2 benzoic acidg 13.0 8.9 2.5 0.3 9.3 hydroquinone 8.113 1.19 0.4l' 13.216 2.318 methanolg 14.5 6.8 4.9 0.8 8.3 8.3 TBP 8.8517 7.P 1.19 0.29 "References: (1) Bondi, 1968; (2) Dobbs, 1986; (3) Colomina et al., 1982; (4) Dobbs et al., 1987; (5) estimated using Lyderson's method (Benton and Hewitt, 1989); (6) de Kruif et al., 1981; (7) Ziger, 1983; Henley and Seader, 1981; (9) Wong, 1986; (10) estimated using Goldburg's rule (Benton and Hewitt, 1989); (11) estimated using PMiat T, (Putfrom Schulz and Navritil, 1984); (12) Weast, 1986; (13) Barton, 1983, using p-xylene as a homomorph; (14) Wong, 1986, using phenol's dielectric constant; (15) Karger et al., 1976; (16) Karger et al. (1976), using the value for phenol; (17) Barton, 1983.
1228 Ind. Eng. Chem. Res., Vol. 30, No. 6, 1991 10-2
1 0 . ~
4
-5
10.~
10
10
10
10.' 1 0.4
1o
- ~
10"
Mole Fraction TBP Figure 6. Predicted hydroquinone solubilities in supercritical carbon dioxide at 35 O C and 150, 200, 250, and 300 bar, in order of increasing pressure (in the vertical direction),as a function of total TBP concentration.
Mole Fraction TBP Figure 8. Concentration of "free"and "complexed"hydroquinone in supercritical carbon dioxide at 35 O C as a function of preasure and TBP concentration. Both seta of curves are drawn for 150,200,250, and 300 bar in order of increasing preasure (in the vertical direction).
Table V. Hydroquinone Solubilities in a Mixed Carbon Dioxide-TBP (0.62 mol % on a Solute-Free Basis) Solvent at 175.1 bar T. "C o. satd soh. (a/cm3) N9 2.66 X lo-' 35.0 0.8595 2.86 X IO-' 40.0 0.8342 3.09 X lo-' 45.0 0.8050 3.68 X IO-' 50.0 0.7767 3.64 X lo-' 55.0 0.7457 4.06 X lo-' 0.7134 60.0
Mole Fraction TBP Figure 7. Fraction of total hydroquinone dissolved in supercritical carbon dioxide that is in a complex with TBP at 35 O C and 150,200, 250, and 300 bar, shown in order of decreasing pressure (in the vertical direction).
a t low densities. A similar curve can be drawn for TBP, but since the cosolvent is always in excess no more than 20% of the TBP is ever found in the complex. The influences of the pressure effects and the chemical effects on hydroquinone solubilities can be seen more clearly in Figure 8. At any given pressure, the concentration of the free solute remains constant over a wide range of cosolvent concentrations. The effect of composition on the fugacity coefficient is dominated by the inert solvent which is always at least 95% of the solution. The effect of pressure does not depend on the cosolvent concentration, however, so it remains significant at all cosolvent concentrations. The concentration of the complex, however, is directly related to the cosolvent. In addition, a small pressure effect is also observed, although this is not as significant as it is for the free solute. This is an indirect effect, as it occurs because the increased concentration of the free solute shifts the equilibrium further toward the side of the complex. At this point, it is clear that both the DDLC model and the chemical equilibrium model may be used to successfully correlate the phase behavior of supercritical fluid
systems that exhibit very strong intermolecular interactions. The advantage of the DDLC model is that, in principle, quantitative predictions of the phase behavior can be obtained with the use of physical property data for the pure components. It predicts a smooth increase in solubilities with cosolvent concentration, and is unable to handle the abrupt increase that occurs when a stoichiometric complex forms. Because of this, it is more suited to those cases where stoichiometric complexes are not expected. The chemical model, on the other hand, is able to recognize the rapid rise in solubilities at low cosolvent concentrations. Its major limitations are that it is primarily a correlative model instead of a predictive one and that more data are required as a function of cosolvent concentration in order to reliably determine the stoichiometry of the complex. It becomes more predictive, at least for solubilities, if the stoichiometry and the equilibrium constant can be obtained from independent measurements such as those obtained from spectroscopy. Temperature Effects. Table V lists isobaric data for the carbon dioxide-hydroquinone-TBP system obtained at 175 bar. The effect of temperature can be seen to be surprisingly minor. For example, solubilities increase only about 55% despite a 1900% increase in the vapor pressure. With other cosolvents this might be attributed to the decreased density of the solution at the higher temperatures, but we have already shown that the density effect is dominated by chemical (hydrogen bonding) effects at these cosolvent concentrations. Since hydrogen bond formation is an exothermic process, higher temperatures shift the equilibrium to the side of the reactants. This is shown in Figure 9, which is a semilogarithmic plot of the equilibrium constants obtained from the isobaric data in
Ind. Eng. Chem. Res., Vol. 30, No. 6, 1991 1229 3
lute-cosolvent interactions are stoichiometric.
Acknowledgment Acknowledgment is made to the National Science Foundation under Grant No, CBT 8513784, the Camille and Henry Dreyfus Foundation for a Teacher-Scholar Grant (K.P.J.), the Separations Research Program and the University of Texas, the State of Texas Energy Research in Applications Program, and the Shell Development Company.
Y
:0030
0.0031
0.0032
0.0033
1IT Figure 9. Equilibrium constante for formation of hydroquinone TBP, complex aa a function of reciprocal temperature. The enthalpy of reaction for the formation of the complex is -18.9 kcal/mol, with two hydrogen bonds formed in each molecule of the complex.
Table V as a function of the reciprocal temperature. In order to determine the values of the equilibrium constant at the various temperatures, the Peng-Robinson binary interaction parameter kI2 was assumed to be a linear function of temperature. This assumption was based on the values obtained during the regressions of the 8.0 X lo4 mol 9% TBP isotherms at both 35 and 45 "C. The figure shows that the equilibrium constant for this reaction decreases by an order of magnitude with only a 25 "C increase in temperature, corresponding to an enthalpy of formation for the complex of -18.9 kcal/mol. This value is consistent with the formation of two hydrogen bonds (Prausnitz, 1969). Conclusions Polar solutes that normally exhibit a limited solubility in supercritical carbon dioxide may become very soluble with the use of cosolventa that form a chemical complex. The enhancement produced by the complexing agent TBP is at least 1 order of magnitude greater than that which has been obtained with cosolventa that do not form complexes. Many of these complex-forming reagents are insoluble in aqueous media, leading to the possibility of using these solutions to recover solutes from wastewater streams and fermentation broths. Further work is required, however, to determine conditions in which an undesirable third cosolvent-rich phase may form. The chemical reaction equilibrium-equation of state model developed in this paper offers several advantages compared to other modeling approaches. The primary advantage is that it is more successful in modeling the very large solubility enhancements produced in these complex-forming systems. It also allows the effects of temperature to be more easily interpreted and understood. Finally, it can provide new insights into the nature and specificity of the interactions between the components of these systems, as for example by demonstrating whether a stoichiometric or nonstoichiometric complex is formed. Extension of the model to include other equilibrium reactions is simple and straightforward. The DDLC model, on the other hand, offers the advantage in principle that semiquantitative predictions can be obtained without the need for any adjustable parameters. The choice between the chemical equilibrium model and the physical DDLC model should be based on the degree to which the so-
Nomenclature ai = attraction parameter in equation of state ci = mixture attraction parameter in equation of state A = parameter defined by Peng-Robinson equation of state bi = size parameter in equation of state b = mixture size parameter in equation of state B = parameter defined by Peng-Robinson equation of state C = denotes the complex Q,.R, c1 = integration constant used in the derivation of eq 2 to convert Lennard-Jones constants to van der Waals attraction constants k . . = Peng-Robinson binary interaction parameter = equilibrium constant L = dimensionless cutoff parameter for the first coordination shell ni = number of moles of true species i actually present in solution nj" = apparent number of moles of component j in solution no = total number of moles of apparent components present in solution n, = total number of moles of true species present in solution P = pressure Pisat= vapor pressure of solid component q = stoichiometriccoefficient for species Q Q = denotes the solute in the chemical model r = stoichiometriccoefficient for species R R = denotes the cosolvent in the chemical model R = ideal gas constant in the DDLC model S = denotes the inert solvent in the chemical model T = temperature 8, = solid molar volume yi = apparent mole fraction, which includes both free and complexed species zi = true mole fraction 2 = compressibility factor a = dimensionless degree of nonrandomness parameter #j = fugacity coefficient of species i
zq
Registry No. TBP,126-73-8; HQ, 123-31-9; COz, 124-38-9; CsHsCOzH, 65-85-0.
Literature Cited Aksnes, G.; Albriktaen, P. Intermolecular hydrogen bonding between organic phosphoryl compounds and phenol. Acta Chem. Scand. 1968,22, l&6. Barton, A. Handbook of Solubility Parameters and Other Cohesive Parameters; CRC Press: Boca Raton, FL, 1983. Benton, C. F.; Hewitt, G.F. Physical Property Data for the Design Engineer; Hemisphere: New York, 1989. Bondi, A. Physical Properties of Molecular Crystals; Wiley: New York, 1968. Brennecke, J. F.; Eckert, C.A. Phase equilibria for supercritical fluid process design. AIChE J . 1989a. 35,1409. Brennecke, J. F.; Eckert, C. A. Fluorescence spectroscopy studies of intermolecular interactions in supercritical fluids. In Supercritical Fluid Science and Technology; Johnston, K. P., Penninger, J. M. L., Eds.; ACS Symposium Series 406; American Chemical Society: Washington, DC, 1989b; p 14. Brunner, J. Selectivity of supercritical compounds and entrainere with respect to model substances. Fluid Phase Equilib. 1983, 10, 289. Brunner, J. Mixed solvents in gas extraction and related processes. In Solvent Extraction and Ion Exchange; Marinsky, J. A., Mar-
1230 Ind. Eng. Chem, Res., Vol. 30, No. 6, 1991 cus, Y., Eds., Marcel Dekker: New York, 1988;Vol. 10. Cho, T., and Shuler, M. L. Multimembrane bioreactor for extractive fermentation. Biotechnol. h o g . 1986,2,53. Colomina, M.; Jiminez, P.; Turrion, C. Vapour pressures and enthalpies of sublimation of naphthalene and benzoic acid. J. Chem. Thermodyn. 1982,14,779. Debenedetti, P. G. Clustering in dilute, binary supercritical mixtures: A fluctuation analysis. Chem. Eng. Sci. 1987,42,2203. de Kruif, C. G.; Smit, E. J.; Govers, H. A. J. Thermodynamic properties of 1,4-benzoquinone (BQ), l,4-hydroquinone (HQ), 1,4naphthoquinone (NQ) 1,4-naphthohydroquinone (NHQ), and the complexes BQ-HQ 1:1, NQ-HQ 1:1, NQ-NHQ 2:1, and NQ-NHQ 1:l. J. Chem. Phys. 1981, 74,5838. Dobbs, J. M. Modification of Supercritical Fluid Equilibrium and Selectivity Using Polar and Non-polar Co-solvents. Ph.D. Dissertation, The University of Texas, 1986. Dobbs, J. M.; Johnston, K. P. Selectivities in pure and mixed supercritical fluid solvents. Znd. Eng. Chem. Res. 1987,26,1476. Dobbs, J. M.; Wong, J. M.; Johnston, K. P. Non-polar co-solvents for solubility enhancement in supercritical carbon dioxide. J. Chem. Eng. Data 1986,31,303. Dobbs, J. M.; Wong, J. M.; Laheire, R. J.; Johnston, K. P. Modification of supercritical fluid phase behavior using polar co-solvents. Ind. Eng. Chem. Res. 1987,26,56. Eckert, C. A.; Ziger, D. H.; Johnston, K. P.; Kim, S. Solute partial molar volumes in supercritical fluids. J. Phys. Chem. 1986,90, 2738. Ely, J. F. An equation of state model for pure COP and COP-rich mixtures. Proc. GQSProcess. Assoc. Cono. 1986,65th, 185. Fulton, J. L.; Blitz, J. P.; Tingey, J. M.; Smith, R. D. Reverse micelles and microemulsions in supercritical fluids. J . Phys. Chem. 1989, 93,4198. Heidemann, R. A,; Prausnitz, J. M. A van der Waals-type equation of state for fluids with associating molecules. Proc. Natl. Acad. Sci. 1976,73,1773. Henley, E. J.; Seader, J. D. Equilibrium-Stage Separation Operations in Chemical Engineering; Wiley: New York, 1981. Hong, J.; Hu, Y. An equation of state for associated systems. Fluid Phase Equilib. 1989,51, 37. Hu, Y.; Azevedo, E.; Luedecke, D.; Prausnitz, J. Thermodynamics of associated solutions: Henry’s constanta for nonpolar solutes in water. Fluid Phase Equilib. 1984,17,303. Jagirdar, G. C. Extractive separation of acetic and monochloroacetic acids from aqueous solutions by tri-n-butylphosphate. Indian Chem. Eng. 1982,24,15. Johnston, K. P. Supercritical fluids. In Encyclopedia of Chemical Technology, 3rd ed., suppl. vol; Wiley: New York, 1984; p 872. Johnston, K. P.; Kim, S.; Wong, J. M. Local composition models for fluid mixtures over a wide density range. Fluid Phase Equilib. 1987,38,39. Johnston, K. P.; Kim, S.; Combes, J. R. Spectroscopic determination of solvent strength and structure in supercritical fluid mixtures. In Supercritical Fluid Science and Technology; Johnston, K. P., Penninger, J. M. L., Eds.; ACS Symposium Series 406; American Chemical Society: Washington, DC, 19898; p 52. Johnston, K. P.; McFann, G.; Lemert, R. Pressure tuning of reverse micelles for adjustable solvation of hydrophile5 in supercritical fluids. In Supercritical Fluid Science and Technology; Johnston, K. P., Penninger, J. M. L., Eds.; ACS Symposium Series 406; American Chemical Society: Washington, DC, 198913,p 140. Johnston, K . P.; McFann, G.; Peck, D.; Lemert, R. Design and characterization of the molecular environment in supercritical fluids. Fluid Phase Equilib. 1989c,52,337. Johnston, K. P.; Peck, D. G.; Kim, S. Modeling supercritical mixtures-how predictive is it? Ind. Eng. Chem. Res. 1989d,28, 1115. Joshi, D. K.; Senetar, J. J.; King, C. J. Solvent extraction for removal of polar-organic pollutants from water. Ind. Eng. Chem. Process Des. Dev. 1984,23,748. Karger, B. L.; Snyder, L. R.; Eon, C. An expanded solubility parameter treatment for classification and use of chromatographic solvents and adsorbents. Parameters for dispersion, dipole and hydrogen bonding interactions. J. Chromatogr. 1976,12Fj,71. Kim, S.; Johnston, K. P. Molecular interactions in dilute supercritical fluid solutions. Ind. Eng. Chem. Res. 19878,26, 1206.
Kim, S.; Johnston, K. P. Clustering in supercritical fluid mixtures. AIChE J. 1987b,33,1603. King, C. J. Separation processes based on reversible chemical complexation. In Handbook of Separation Process Technology; Rousseau, R. W., Ed.; Wiley-Interscience: New York, 1987;p 760. Krukonis, V. J.; Kurnik, R. T. Solubility of solid aromatic isomers in carbon dioxide. J. Chem. Eng. Data 1985,30,247. Kurnik, R. T.; Reid, R. C. Solubility of solid mixtures in supercritical fluids. Fluid Phase Equilib. 1982,8,93. Kurnik, R. T.; Holla, S. J.; Reid, R. C. Solubility of solids in supercritical carbon dioxide and ethylene. J. Chem. Eng. Data 1981, 26,47. Lemert, R.M.; Johnston, K. P. Solid-liquid-gas equilibria in multicomponent supercritical fluid systems. Fluid Phase Equilib. 1989, 45, 265. Lemert, R. M.; Johnston, K. P. Solubilities and selectivities in supercritical fluid mixtures near critical end points. Fluid Phase Equilib. 1990,59, 31. Lemert, R. M.; Fuller, R. A,; Johnston, K. P. Reverse micelles in supercritical fluids. 3. Amino acid solubilization in ethane and propane. J. Phys. Chem. 1990,94,6021. Luedecke, D.; Prausnitz, J. M. Phase equilibria for strongly nonideal mixtures from an equation of state with density-dependent mixing rules. Fluid Phase Equilib. 1985,22,1. Markl, H. Extraction of aromatic carboxylic acids and phenols by strongly solvating organophosphorous compounds and sulfoxides. Mikrochim. Acta 1981,19811, 107. Mathias, P. M.; Copeman, T. W. Extension of the Peng-Robinson equation of state to complex mixtures: evaluation of the various forms of the local composition concept. Fluid Phase Equilib. 1983,13,91. Matsumura, M.; Markl, H. Elimination of ethanol inhibition by perstraction. Biotechnol. Bioeng. 1986,28,534. McHugh, M. A.; Paulaitis, M. E. Solid solubilities of naphthalene and biphenyl in supercritical carbon dioxide. J. Chem. Eng. Data 1980,25,326. Munson, C. L.; King, C. J. Factors influencing solvent selection for extraction of ethanol from aqueous solutions. Ind. Eng. Chem. Proces Des. Dev. 1984,23,109. Pagel, H. A.; McLafferty, F. W. Use of tributyl phosphate for extracting organic acids from aqueous solution. Anal. Chem. 1948, 20,272. Paulaitis, M. E.; Krukonis, V. J.; Kurnik, R. T.; Reid, R. C. Supercritical fluid extraction. Reu. Chem. Eng. 1983,I, 179. Peng, D.-Y.; Robinson, D. B. A new two-constant equation of state. Ind. Eng. Chem. Fundam. 1976,15,59. Prausnitz, J. M. Molecular Thermodynamics of Fluid-Phase Equilibria; Prentice-Hall; Englewood Cliffs, NJ, 1969. Roddy, J. W.; Coleman, C. F. Distribution and miscibility limits in the system ethanol-water-tri-n-butyl phosphate-diluent. Ind. Eng. Chem. Fundam. 1983,22,51. Schmitt, W. J.; Reid, R. C. The use of entrainers in modifying the solubility of phenanthrene and benzoic acid in supercritical carbon dioxide and ethane. Fluid Phase Equilib. 1986,32,77. Schulz, W. W.; Navratil, J. D. Science and Technology of Tributyl Phosphate; CRC Press; Boca Raton, FL, 1984; Vol. 1. Stryjek, R.; Vera, J. H. PRSV An improved Peng-Robinson equation of state for pure compounds and mixtures. Can. J. Chem. Eng. 1986a,64, 323. Stryjek, R.; Vera, J. H. PRSV-An improved Peng-Robinson equation of state with new mixing rules for strongly nonideal mixtures. Can. J. Chem. Eng. 1986b,64, 334. van Alsten, J. G. Structural and Functional Effects in Solutions with Pure and Entrainer-Doped Supercritical Solvents. Ph.D. Thesis, University of Illinois, 1986. Walsh, J. M.; Ikonomou, G. D.; Donohue, M. D. Supercritical phase behavior: the entrainer effect. Fluid Phase Equilib. 1987,33,295. Walsh, J. M.; Greenfield, M. L.; Ikonomou, G. D.; Donohue, M. D. FTIR spectroscopic study of hydrogen-bonding competition in entrainer cosolvent systems. Int. J. Thermophys. 1990,II,119. Wardell, J. M.; King, C. J. Solvent equilibria for extraction of carboxylic acids from water. J. Chem. Eng. Data 1978, 23, 144. Weast, R. C., Ed. Handbook of Chemistry and Physics, 67th ed.; CRC Press: Boca Raton, FL, 1986. Wong, J. M. Molecular Thermodynamics of Steroids and Polyfunctional Organic Solids in Supercritical Fluid Mixtures; Ph.D. Dissertation, The University of Texas, 1986. Wong, J. M.; Johnston, K. P. Solubilization of biomolecules in carbon dioxide based supercritical fluids. BiotechnoL Prog. 1986,2, 29.
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Yazdi, P.; McFann, G. J.; Johnaton, K. P.; Fox, M. A. Reverse micellee in supercritical fluids. 2. Fluorescence and absorption spectral probes of adjustable aggregation in the two-phase region. J. Phys. Chem. 1990,94,7224. Ziger, D. H. Solid-SupercriticalFluid Equilibrium: Experimental
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and Theoretical Studies of Partial Molar Volumes of Solubilities; Ph.D. Dissertation, University of Illinois, 1983. Received for review July 9, 1990 Accepted October 23, 1990
Continuous Membrane Dialysis Using Ion-Exchange Resin Suspension for Extracting Metal Ions Xinming Shao, Shangxu Hu, and Rakesh Govind* Department of Chemical Engineering, Uniuersity of Cincinnati, Cincinnati, Ohio 45221
A continuous membrane dialysis process using ion-exchange resin suspension has been developed for extracting metals from industrial waste streams. The basic idea is to use a chelating ion-exchange resin in conjunction with a semipermeable membrane. The membrane is capable of retaining the resin and its metal complex while allowing the free metal ion to permeate freely. The process consists of a chelating unit and a stripping unit. In the chelating unit, the resin reacts with certain metal ions and forms a metal complex. In the stripping unit, metal ions are released and the resin is regenerated a t a lower pH. The resin suspension is continuously circulated between the chelating and stripping units. Experimental studies have been conducted on the removal of copper ion. The results show that the extraction of metals can be significantly enhanced in comparison with a nonchelating system. In addition to experimental studies, a mathematical model for the process has been proposed and verified on the basis of system identification of the overall physicochemical parameters by fitting the experimental data. The basic process has also been optimized by using the validated model to explore the optimal (minimum operating cost with a specified feed stream and output) process structure and operating conditions.
Introduction There is a growing need for developing novel separation techniques for selectively extracting metals from industrial proceas streams. This is required not only to remove water bearing ion contaminants to meet environmental legislation for wastewater discharges, but also to selectively recover valuable metals from hydrometallurgical liquors, spent electroplating baths, and metal finishing wastewaters. Solvent extraction is a commonly used conventional technique. It is well-established and widely used. However, in handling of large volume solutions containing low metal concentrations, the solvent extraction process becomes uneconomical. Recently, there have been several membrane separation processes under development, which are as follows: supported liquid membrane (Lee et al., 1978; Komasawa et al., 1983;Danesi, 1985),liquid surfactant membrane (Gu et al., 1985), membrane-based solvent extraction (Strathmann, 1980;Kim, 1984;Heuckroch et al., 1986;Prasad and Sirkar, 1987),and affinity dialysis using dialysis membrane and water-soluble polymers (Davis et al., 1988;Hu and Govind, 1988). Due to their potential for lower energy utilization and significant increases in throughputs, these novel methods are attractive. However, these techniques still have some problems to overcome, such as solvent entrainment or washout, poor system durability, low extraction rate, and inadequate stability of membrane (Kordosky et al., 1987; Tavlarides et al., 1987). Generally, these membrane techniques remain immature and need more effort for industrial applications. Ion-exchange resins including chelating ion-exchange resins (Grinstead, 1978;Loureiro et al., 1988) and impregnated ion-exchange resins (Warshawsky, 1981)have been widely studied for the recovery of metals from dilute
* Correspondence should be directed to this author.
leach liquors. In most commercial ion-exchange processes such as fEed bed or continuous packed bed,feed solutions directly contact with resins. Fine particles in the feed solutions may contaminate the resin and tend to block the bed and increase the pressure drop. This requires that feed solutions must have a low suspended solids content. Though a backwash cycle may be incorporated, it is still undesirable to use these processes with more than lo00 ppm undissolved solids (Streat and Naden, 1987). This limits the flexibility of using ion-exchange resins in most metal recovery processes. In addition, fixed bed or packed bed ion-exchange operations require high mechanical strength and toughness of the ion-exchange particles. The resin should be resistant to abrasion and crushing, and it also should withstand continuous rapid swelling when loaded with hydrated ions and shrinking with less hydrated ions. Resin attrition, abrasion, and fracture may cause serious problems in actual process operations. Even in fluidized beds or continuous ion-exchange beds, resin particle attrition is still one of the major concerns. These requirements greatly increase the manufacturing cost of ion-exchange resins. Thus, any losses of the resin during regeneration are undesirable. In this work, by employing the ion-exchange chelating resin as an alternative for extractant agent in solvent extraction, a continuous membrane dialysis process using ion-exchange-resin suspension has been developed. This new process consists of a chelating unit and a stripping unit. Both of them are membrane hollow fiber cartridges operating at different pHs. The original resin was ground to form a resin suspension which can be circulated along the chelating unit where the resin reacts with metal ions selectively and the stripping unit where the resin is regenerated. The transport of free metal ion across the membrane is controlled by its concentration gradient across the membrane. The process combines membrane
0888-5885/91/2630-1231$02.50/00 1991 American Chemical Society
