Experimental and Model Study on Enantioselective Extraction of

Article pubs.acs.org/IECR

Experimental and Model Study on Enantioselective Extraction of Phenylglycine Enantiomers with BINAP−Metal Complexes Kewen Tang,†,* Guohui Wu,‡ Panliang Zhang,† Congshan Zhou,† and Jiajia Liu‡ †

Department of Chemistry and Chemical Engineering, Hunan Institute of Science and Technology, Yueyang 414006, Hunan, China College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, Hunan, China

‡

S Supporting Information *

ABSTRACT: Enantioselective extraction of phenylglycine (PHG) enantiomers with (S)-BINAP−metal complexes as chiral selector was investigated. A reactive extraction model was established to interpret the experimental data. The complexation equilibrium constants and other important parameters required by the model were determined experimentally. The extraction system shows good selectivity toward PHG enantiomers. The complex [(S)-BINAP(CH3CN)Cu][PF6] (BINAP−Cu) exhibits the highest selectivity among the selectors studied, which is dissolved in the organic phase and preferentially extracts L-PHG from aqueous phase. Efficiency of extraction depends, often strongly, on a number of process variables, including types of organic solvents and metal precursors, concentration of selector, pH, and temperature. The model quantitatively predicts extraction performance as a function of key operating parameters, providing a simple computational approach to process optimization. The model was verified experimentally with excellent results.

1. INTRODUCTION Different enantiomers often exhibit a large difference in pharmacological activity and toxicity when ingested by living organisms. Therefore, it is very important to have methods for chiral separation. Enantiomeric separation is a hard task, because the enantiomers, otherwise equal, must be separated on the basis of just a slight difference in stereochemical properties.1 To overcome this difficulty, numerous strategies were developed which are well documented in the literature, such as enzymatic resolution or biocatalysis,2−8 membraneassisted separations,9 crystallization,10 supercritical extraction,11−13 and chromatography.14−16 These methods provide very promising approaches for enantiomeric separation. However, the drawbacks of these current chiral separation methods are either low versatility or that they are relatively expensive. Therefore, there is an urgent need for a new more efficient chiral separation method. Chiral solvent extraction provides a promising approach to fulfill the need.17,18 A partial separation can be obtained in one-stage extraction, and staging in a fractional extraction scheme can be used to obtain both enantiomers with the desired purity.19 Enantioselectivity (α) is the most important parameter for chiral extraction. For example, for a 99% pure product about 190 theoretical stages are required for an enantioselectivity of 1.05, but the number can be decreased to 25 when α increases to a value of 1.50.20 The main attraction of chiral solvent extraction is its advantage in large-scale production. Although ample literature is available for enantioselective extraction investigation,17 only a few studies provide fundamental insights in the reaction engineering mechanisms which is very important for scaling up the process.18,19,21−23 In chiral extraction, enantioselectivity is mainly dominated by the enantioselective extractant (selector). With a highly efficient chiral selector, the stages needed for a certain enantiomeric purity can be reduced considerably. Several chiral selectors have © 2012 American Chemical Society

been developed for the purpose, such as tartaric acid derivatives,24−27 cinchona alkaloids,19,28−30 crown ethers,31−33 and so on.34−39 However, the low versatility and/or enantioselectivity of these selectors limit their wider application. So looking for new chiral selectors with high enantioselectivity will speed up the application of the reactive extraction, and realize its large-scale production. Separations of some hydrophobic enantiomers by reactive extraction with hydrophilic cyclodextrin derivatives have been investigated in our recent work and sufficient enantioselectivities were obtained.18,38,39 Researches have shown that chiral metal complexes show good performance in enantioselectivity.14,34,35,40 On the other hand, the chiral BINAP has been proven to be a highly versatile ligand in asymmetric catalysis.41 Therefore, it is possible to obtain a new and efficient chiral selector based on (S)-BINAP−metal complexes.34,35 Phenylglycine (PHG) enantiomers (Figure 1a) are important in synthesis of several products used in pharmaceutical industry.

Figure 1. Chemical structure of phenylglycine (a) and [(S)BINAP(CH3CN)Cu][PF6] (b). Received: Revised: Accepted: Published: 15233

July 24, 2012 October 21, 2012 November 2, 2012 November 2, 2012 dx.doi.org/10.1021/ie301976h | Ind. Eng. Chem. Res. 2012, 51, 15233−15241

Industrial & Engineering Chemistry Research

Article

volumes (each 2 mL) of the aqueous and organic phases were placed together and shaken sufficiently (12 h) before being kept in a water bath at a fixed temperature of 5 °C to reach equilibrium. Concentration of the PHG enantiomers was kept at 2 mmol/L, and BINAP−Cu concentration was varied from 0.25 to 4 mmol/L. After extraction, phase compositions were analyzed by HPLC. The apparent complexation equilibrium constants are obtained by regression analysis of the experimental data according eqs 19 and 20.

D-Phenylglycine

has outstanding importance in being introduced as a side chain of cephalexin and ampicillin.42 LPhenylglycine is a building block for L-733, 060, a neurokinin NK1 receptor antagonist, which is a constituent of new proctolin analogues and is part of new thymidylate synthase inhibitors.43 Therefore, it is very necessary to separate the PHG enantiomers. This paper reports the enantioselective reactive extraction of PHG enantiomers with a BINAP−metal complex (Figure 1b) as a chiral selector. Effects of process variables such as types of organic solvents and metal precursors, concentration of selector, pH, and temperature, on extraction efficiency were investigated. The mechanism of the extraction was discussed, and a reactive extraction model with an interfacial reaction of PHG enantiomers with the metal complex of BINAP−Cu was established to optimize the extraction process.

3. THEORY 3.1. Mechanism of Reactive Extraction. Knowing the mechanism can improve our understanding of the behavior of the extraction system. In most cases, either a homogeneous reaction model or an interfacial reaction model is applied to understand a reactive extraction system. The main difference between the two models is the locus of the main reactions for reactive extraction. In the reactive extraction of PHG enantiomers with BINAP−Cu as selector, the reactions may take place in either the organic phase, the aqueous phase, or at the interface. Solution experiments demonstrate that BINAP− Cu and its complex with PHG enantiomers cannot be dissolved in the aqueous phase and PHG enantiomers are highly hydrophobic. Therefore, we have applied the interfacial reaction mechanism here. The location of the main reactions is restricted to the interface between the two phases (Figure 2).

2. EXPERIMENTAL SECTION 2.1. Materials. Bi(acetonitrile)dichloropalladium (PdCl2(CH3CN)2, purity >99% (w/w)) was purchased from Metallurgy Institute of Zhejiang (Zhejiang, China). Bis(triphenylphosphine)nickel(II) ([(C6H5)3P]2NiCl2, purity >99% (w/w)) and tetrakis(acetonitrile)copper(I) hexafluorophosphate ([(CH3CN)4Cu]PF6, purity >99% (w/w)) were purchased from Hewei Chemical Co. Ltd. (Guangzhou, China). (S)-(−)-2,2′-Bis(diphenylphosphino)-1,1′-binaphthalene ((S)BINAP) (purity >99% (w/w)) was purchased from Shengjia Chemical Co., Ltd. (Heibei, China). Phenylglycine (PHG) (racemate, purity >99% (w/w)) was purchased from Yuanye Technology Co. Ltd. (Shanghai, China). The solvent for chromatography was of HPLC grade. All other chemicals were of analytical-reagent grade and bought from different suppliers. 2.2. Analytical Method. The quantification of PHG enantiomers in the aqueous phase was performed by HPLC using an Agilent LC 1200 series apparatus (Agilent Technologies Co. Ltd.). An UV detector operated at 254 nm was applied. The column was Inertsill/Wondasil C18, 5 um particle size of the packing material, 250 mm × 4.6 mm i.d. (GL Sciences Inc., Japan). The mobile phase was a 20:80 (v/v) mixture of methanol and an aqueous solution containing 2 mmol/L L-phenylalanine and 0.4 mmol/L copper sulfate. The flow rate was set at 0.3 mL/min and the column temperature was set at 25 °C. Each test was run in triplicate under identical conditions, and the standard deviation is in the range of 2%. 2.3. Extraction Experiments. The aqueous phase was prepared by dissolving racemic PHG in 0.1 mol/L KH2PO4/ K2HPO4 buffer solution, and the organic phase was prepared by dissolving BINAP−metal complex in the organic solvent. BINAP−metal complex was generated in situ by adding the metal precursor and BINAP in equal molar amounts to the appropriate organic solvent. The reaction mixture was stirred overnight and diluted to the desired concentration and the obtained solution was directly applied in extraction experiments. Equal volumes (each 2 mL) of the aqueous and the organic phases were placed together in a 10 mL centrifuge tube and shaken sufficiently (12 h) before being kept in a water bath at a fixed temperature (24 h) to reach equilibrium. After phase separation, the concentrations of PHG enantiomers in the aqueous phase were analyzed by HPLC. The concentration of D- and L-PHG in the organic phase was calculated from a mass balance. 2.4. Determination of Complexation Equilibrium Constants KD and KL. The experiment was carried out at pH of 7 with dichloromethane as organic solvent. Equal

Figure 2. Diagram of the mechanism of reactive extraction.

Mass transfer and chemical reaction are described as serial processes: the reactants are transported to the interface, are enriched at the interface, the reaction takes place at the interface, the products are transported into the bulk.44 3.2. Modeling of the Extraction Equilibrium. Because the extraction mechanism is understood, equilibrium of the extraction system can be modeled by combining a series of equilibrium equations and mass balance equations. Phase compositions of two-phase systems at equilibrium involving formation of multiple chemical complexes are calculated by simultaneous solution of phase equilibrium and chemical equilibrium equations. According to the mechanism shown in Figure 2, the complexation equilibrium constant at the interface can be defined as KD = 15234

[CuBD]org [PF6−]w [CuB]org [D−]w

(1)

dx.doi.org/10.1021/ie301976h | Ind. Eng. Chem. Res. 2012, 51, 15233−15241


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[CuBL]org [PF6−]w

KL =

(KDKL − KDA − KLA + A2 )[CuB]3org

−

[CuB]org [L ]w

tot tot tot + (2KDACCuB + 2KLACCuB − 3A2 CCuB + KDKLC Dtot

(2)

tot − KDC DtotA + KDKLC Ltot − KLC LtotA − KDKLCCuB )

where, KD and KL are the complexation equilibrium constants for D- and L-PHG, respetively; [CuBD]org and [CuBL]org are the equilibrium concentrations of the complexes of [(S)BINAP−Cu][D-PHG] and [(S)-BINAP−Cu][L-PHG] in the organic phase, respectively; [CuB]org is the equilibrium concentration of [(S)-BINAP(CH3CN)Cu][PF6] (BINAP− Cu) in the organic phase at equilibrium; [D−]w and [L−]w are the equilibrium concentrations of ionic D- and L-PHG in the aqueous, respectively; [PF6−]w is the equilibrium concentration of hexafluorophosphate ion in aqueous phase. The dissociation constant of D- and L-PHG in the aqueous phase can be described as following: [D−]w [H+]w [L−]w [H+]w Ka = = [DH]w [LH]w

2 tot tot 2 [CuB]org + (KDC DtotACCuB + KLC LtotACCuB − CCuB KDA

Therefore, [CuB]org can be obtained by solving eq 11. According to eqs 6 and 7, distribution ratios (kD and kL) can be calculated from the following equations: kD =

kL =

Because Vw = Vorg, the following equations represent mass balance for D- and L-PHG, respectively. (4)

C Ltot = [LH]w + [L−]w + [CuBL]org

(5)

Ctot D

C Ltot =

[CuB]org [L−]w KL [L−]w [H+]w + [L−]w + Ka [PF6−]w

(7)

fi =

(8)

[PF6−]w

(kL > kD)

(14) (15)

CL 1 + 1 / kL CL 1 + 1 / kL

− +

CD 1 + 1 / kD CD 1 + 1 / kD

(16)

Citot ,org Citot

(17)

(18)

A performance factor close to unity indicates a high enantiomeric purity in both phases. 3.3. Regression of the Complexation Equilibrium Constants. Regression of the complexation equilibrium constants of the complex formed at the interface (Figure 2) was carried out as follows: combining eqs 1−3, 12 and 13, the following equation can be achieved:

(9)

KDC Dtot[CuB]org [CuB]org KD + A[PF6−]w

KLC Ltot[CuB]org [CuB]org KL + A[PF6−]w

(13)

pfi = fi eeorg

Let A = (1+ ([H+]W)/(ka)) and Ctot CuB can be defined as

+

)

where, Ctot i,org represents the total concentration of the solute i in organic phase at equilibrium, and Ctot i represents the initial total concentration of the solute i. The extraction performance factor (pf) is a very useful tool to optimize an enantioselective extraction and is defined as

[CuB]org [L ]w KL

tot CCuB = [CuB]org +

[H+] Ka

The fraction of the solute i (i = D, L) extracted into the organic phase (f i) is given by

[CuB]org [D−]w KD

[PF6−]w

(

[PF6−]w 1 +

eeorg =

−

+

(12)

KL[CuB]org

(6)

where is the total concentration of BINAP−Cu. Combining eqs 1, 2, and 8, the following equation is deduced, = [CuB]org +

)

A common alternative measure of system performance is provided by the enantiomeric excess (ee). The ee in the organic phase can be expressed in terms of distribution ratio by the following equation:

Ctot CuB

tot CCuB

[H+] Ka

αint = KL /KD

There is the following equation concerning mass balance for BINAP−Cu: tot CCuB = [CuB]org + [CuBD]org + [CuBL]org

(

[PF6−]w 1 +

αop = kL /kD ,

Ctot L

[CuB]org [D−]w KD [D−]w [H+]w + [D−]w + Ka [PF6−]w

KD[CuB]org

The operational selectivity αop is defined by eq 14, which is calculated as the ratio of kL to kD. Its upper limit is the intrinsic selectivity αint, which is the ratio of the complexation equilibrium constants of KL to KD:

where, and are the total concentrations of D- and LPHG, respectively; [DH]w and [LH]w are the equilibrium concentrations of molecular D- and L-PHG in the aqueous phase, respectively. Combining eqs 1−5, eqs 4 and 5 are deduced to C Dtot =

3

(11)

(3)

C Dtot = [DH]w + [D−]w + [CuBD]org

2

2

tot tot tot − CCuB KLA + 3A2 CCuB )[CuB]org − A2 CCuB =0

AkD2C Dtot(kL + 1) + AkDkLC Ltot(kD + 1)

(10)

tot = KD[CCuB (kD + 1)(kL + 1) − kDC Dtot(kL + 1)

With a further treatment of eq 10, the following equation can be deduced

− kLC Ltot(kD + 1)] 15235

(19)



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enantioselectivity are obtained. The highest distribution ratios are obtained with trichloromethane as the organic phase. However, the operational selectivity is lower than that with dichloromethane. With dichloromethane as organic phase, the highest selectivity can be achieved with relatively high distribution ratios. Therefore, dichloromethane is an ideal organic solvent for reactive extraction of PHG enantiomers. 4.3. Complexation Equilibrium Constants KD and KL. A series of extraction experiments with different concentrations of BINAP−Cu in dichloromethane were performed to determine the complexation equilibrium constants KD and KL. In all the extraction experiments, the concentration of PHG enantiomers in the aqueous phase was kept constant at 2 mmol/L with a constant pH value of 7 adjusted by 0.1 mol/L KH2PO4/ K2HPO4 buffer solution and a constant temperature of 5 °C. tot We defined parameter 1 = Ctot CuB (kD + 1)(kL + 1) − kDCD (kL + 2 tot 1) − kLCtot (k + 1) and parameter 2 = Ak C (k + 1) + L D D D L 2 tot AkDkLCtot (k + 1) for D -PHG, parameter 2 = Ak C (k + 1) + L D L L D AkDkLCtot D (kL + 1) for L-PHG. As shown in Figure 3, the plot of

AkL2C Ltot(kD + 1) + AkDkLC Dtot(kL + 1) tot = KL[CCuB (kD + 1)(kL + 1) − kDC Dtot(kL + 1)

− kLC Ltot(kD + 1)]

(20)

By linear regression of the experimental data according to eqs 19 and 20, the complexation equilibrium constants (KD and KL) are evaluated from the slope of the fitting lines.

4. RESULT AND DISSCUSSION 4.1. Influence of Metal Precursor. The effect of structural variation of a metal precursor was investigated. As is shown in Table 1, the structure of the metal precursor has a clear Table 1. Influence of Metal Precursor Typea metal precursor

kD

kL

α

PdCl2(CH3CN)2 [(CH3CN)4Cu]PF6 [(C6H5)3P]2NiCl2

0.135 0.281 0.062

0.266 0.609 0.102

1.96 2.15 1.64

a Aqueous phase: [PHG]0 = 2 mmol/L; pH = 6.0. Organic phase: organic solvent = dichloromethane; [metal precursor]0 = 1 mmol/L; [BINAP]0 = 1 mmol/L; temperature, 5◦C.

influence on the extraction efficiency. With [(CH3CN)4Cu]PF6 as metal precursor, the highest enantioselectivity of 2.15 is achieved. BINAP−Pa complex used as a chiral selector has been previously investigated by Verkuijl, et al., and a series of amino acid enantiomers were separated with good enantioselectivity.34,35 Enantioselectivity of 1.9 toward PHG enantiomers was obtained.34 Compared with Verkuijl’s work, BINAP−Cu can provide a higher enantioselectivity toward PHG enantiomers and replacing Pa with Cu will be economically more interesting. It is also observed that the metal complex with Ni only has very weak complexing ability and enantioselectivity toward PHG enantiomers. Although high distributions can be achieved with PdCl2(CH3CN)2, the obtained enantioselectivity is relatively low. Therefore, we used BINAP−Cu as the suitable selector for the reactive extraction of PHG enantiomers. 4.2. Influence of Organic Solvent. The distribution ratios and enantioselectivity for PHG enantiomers with four different organic solvents were investigated to find out the influence of the organic solvent type. The nature of organic solvent can influence the distribution behavior of the enantiomers because of the fact that organic solvent can influence the noncovalent interactions and affect the formation of the ternary complex during the enantioselective host−guest complexations.45 Moreover, it should be taken into consideration that the hydrophobicity of the solvents can influence the solubility of the complex of BINAP−Cu with PHG enantiomers in the organic phase. As shown in Table 2, when 1,2-dichloroethane and chlorobenzene are used, relatively low distribution ratios and

Figure 3. Linear regressions of experimental data for determination of complexation equilibrium constants. Parameter 1 = Ctot CuB(kD + 1)(kL + tot 2 tot 1) − kDCtot D (kL + 1) − kL CL (kD + 1); Parameter 2 = AkLCD (kL + 1) + 2 tot (k + 1) for D -PHG; Parameter 2 = Ak C AkDkLCtot L D L D (kD + 1) + 2 2 AkDkLCtot D (kL + 1) for L-PHG; R = 0.9993 for L-PHG and R = 0.9994 for D-PHG.

parameter 2 versus parameter 1 for D-PHG yields a straight line and the slope of the line was used to evaluate KD as 1.11 (dimensionless quantity). Similar data treatment according to eq 20 can be performed to evaluate KL as 2.39. The intrinsic selectivity αint (KL/KD) is estimated as 2.15. The correlation between the complexation equilibrium constants and the extraction performance is significant. A high complexation equilibrium constant indicates the selector can extract the target enantiomers with high distribution ratios and a high intrinsic selectivity is the most important guarantee of a high enantioselectivity. 4.4. Influence of pH. The pH of the aqueous phase is a significant issue in a reactive extraction system. In reactive extraction of PHG enantiomers, pH influences the distribution ratio of the substrate, but not the enantioselectivity, which is predicted by the model (eqs 12 and 13). Experiments with different pH were carried out to test the model predictions. Comparison of the experimental data with the model predictions is shown in Figure 4, from which it can be figured

Table 2. Influence of Organic Solvent Typea organic solvent

kD

kL

α

1,2-dichloroethane trichloromethane dichloromethane chlorobenzene

0.215 0.305 0.281 0.208

0.415 0.610 0.609 0.407

1.93 2.00 2.15 1.96

a

Aqueous phase: [PHG]0 = 2.0 mmol/L; pH = 6.0. Organic phase: [BINAP−Cu]0 = 1 mmol/L; temperature, 5 ◦C. 15236



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out that the model predictions of distribution ratios and enantioselectivities are in good agreement with the experiment.

Figure 5. Species fraction as a function of pH.

constants of the two complexes of BINAP−Cu with PHG enantiomers. 4.5. Influence of the Concentration of BINAP−Cu. The influence of BINAP−Cu concentration on the distribution behavior of PHG enantionmers was investigated by varying the concentration from 0 to 4 mmol/L, at pH 7 and 5 °C. Comparison of the experimental data with the model predictions is shown in Figure 6. It is concluded from Figure 6 that the model predictions are in good agreement with the experiment. It is observed from Figure 6a that kD and kL increase with the increase of the concentration of BINAP−Cu. The distribution of PHG enantiomers in the organic phase is carried out by the interfacial reaction, in which PHG enantiomers react with BINAP−Cu to form two ternary complexes. With the increase of BINAP−Cu concentration, more ternary complexes are formed in organic phase, and the distribution ratio consequently increases. At the same time, enantioselectivity is independent of BINAP−Cu concentration, which agrees with the model prediction well (Figure 6b). 4.6. Influence of Temperature. The influence of temperature on the distribution ratios and enantioselectivity was determined in the range of 5−30 °C. From Figure 7, it is observed that distribution ratios increase (Figure 7a) with rising temperature, while enantioselectivity decreases (Figure 7b) at the same time. Good enantioselectivity is achieved at lower temperature with moderate distribution ratios. 4.7. Model Prediction in the Extraction System. Comparison of the experimental data with model predictions indicates the model provides a powerful tool to predict the enantiomer-partition over a range of experimental conditions. Thus, we used the model to explore the influence of various operating conditions on extraction efficiency in a single stage. Figure 8 panels a and b show the distribution ratios of D- and L-PHG as a function of pH and BINAP−Cu concentration, respectively. It can be observed from Figure 8a,b that kD and kL have a similar tendency with the change of pH and BINAP−Cu concentration. The increase of pH and BINAP−Cu concentration can lead to the increase of distribution ratios of the two enantiomers. Figure 9 shows the enantiomeric excess (ee) of L-PHG in organic phase as a function of pH and BINAP−Cu concentration. The ee is relatively high at the conditions

Figure 4. Influence of pH on k and α: (Solid lines) model predictions; (symbols) experimental data. Conditions: organic solvent = dichloromethane; [BINAP−Cu]0 = 1.0 mmol/L; [PHG]0 = 2.0 mmol/L; temperature, 5 °C.

The relationship between the pH of the aqueous phase and the distribution ratio is caused by the shift of association− dissociation equilibrium of PHG. As shown in Figure 4a, distribution ratios (kD and kL) increase with the rise of pH value. Meanwhile, physical extraction experiments (extraction without extractant) indicate that no significant physical partition is observed in the measured pH range. It is shown in Figure 5 that, at pH lower than 3, most of enantiomers are present in cationic form. But it is anionic PHG that distributes in the organic phase by binding to the BINAP−Cu complex. Therefore, lower pH values result in a decrease in distribution ratio. With a rise of pH, the amount of PHG anion increases (shown in Figure 5), which leads to an increase of distribution ratios. However, the enantioselectivity remains constant (Figure 4b), which is determined only by the complexation equilibrium 15237



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Figure 6. Influence of the selector concentration on k and α. (Solid lines) model predictions; (symbols) experimental data. Conditions: organic solvent = dichloromethane; [PHG]0 = 2.0 mmol/L; pH = 7.0; temperature, 5 °C.

Figure 7. Influence of temperature on k and α. Conditions: organic solvent = dichloromethane; [BINAP−Cu]0 = 1.0 mmol/L; [PHG]0 = 2.0 mmol/L; pH = 7.0.

where pH and BINAP−Cu concentration are low. But the distribution ratios of PHG enantiomers in the organic phase are very low in this case, which is not conducive to increasing of yield. Besides a satisfactory ee value, a good yield is also needed. Figure 10 shows the fraction of L-PHG extracted into the organic phase (f L) as a function of pH and BINAP−Cu concentration. Increasing BINAP−Cu concentration and pH enhances the extraction of L-PHG. The extraction fraction reaches a plateau where the pH value is above 6 and BINAP− Cu concentration is more than 0.3 mmol/L. It is concluded from Figures 9 and 10 that it is somehow contradictory to achieve a good ee value with a high yield. To facilitate optimization of the reactive extraction system, performance factor (pf) is introduced, which is defined as the product of ee in the organic phase and the fraction of an enantiomer extracted into the organic phase. A good performance factor indicates that the given enantiomer can be purified to high purity with maximum yield. Performance factors

calculated from ee and f L data in Figures 9 and 10 are shown in Figure 11. It shows that the performance factor is strongly influenced by BINAP−Cu concentration and pH. Performance factor reaches a maximum where the pH value is about 6 and BINAP−Cu concentration is about 1 mmol/L. The model predictions were validated by determining performance factors for PHG enantiomers experimentally. Figure 12 and Figure 13 show the plots of performance factor versus pH value and BINAP−Cu concentration, respectively. Both experimental results and model predictions are presented. It is observed from Figure 12 that performance factor increases with an increase of pH and reaches a plateau at pH above 6. On the other hand, Figure 13 shows that the performance factor reaches a maximum where BINAP−Cu concentration is about 1 mmol/L. It can be concluded from Figure 12 and Figure 13 that the model predicts experimental results accurately, including the maximum shown in Figure 11. Application of the model for system optimization is therefore proved to be convincing. 15238



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Figure 10. Calculated fraction of the L-PHG extracted into the organic phase (f L) as a function of pH and [BINAP−Cu]0. Conditions: organic solvent = dichloromethane; [PHG]0 = 2.0 mmol/L; temperature, 5 °C.

Figure 8. Calculated distribution ratios (kD and kL) as a function of pH and [BINAP−Cu]0. Conditions: organic solvent = dichloromethane; [PHG]0 = 2.0 mmol/L; temperature, 5 °C. Figure 11. Calculated performance factor (pf) as a function of pH and [BINAP−Cu]0. Conditions: organic solvent = dichloromethane; [PHG]0 = 2.0 mmol/L; temperature, 5 °C.

results show that the efficiency is strongly influenced by the process variables such as types of metal precursors and organic solvents, concentration of selector, pH, and temperature. The reactive extraction system was modeled based on an interfacial reaction mechanism. The model involving acid−base dissociation of solute, interfacial reaction equilibrium and mass balance, quantitatively predicts distribution ratios and enantioselectivities at various system conditions with excellent accuracy. It can therefore be used for the optimization of the reactive extraction system. Best conditions involving pH value of about 6 and BINAP− Cu concentration of about 1 mmol/L are obtained by modeling and optimization relying on a maximum performance factor. The model predicts were validated by experiments. The presented data indicate that the model provides a powerful tool for modeling a two-phase reactive extraction system. Full separation of the PHG enantiomers cannot be achieved in a single equilibrium step but can be achieved by multistage extraction. With α of 2.15, full separation of the PHG

Figure 9. Calculated enantiomeric excess (eeorg) as a function of pH and [BINAP−Cu]0. Conditions: organic solvent = dichloromethane; [PHG]0 = 2.0 mmol/L; temperature, 5 °C.

5. CONCLUSIONS Enantioselective reactive extraction of PHG enantiomers with BINAP−Cu as chiral selector was investigated. Experimental 15239



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ACKNOWLEDGMENTS This work was supported by the National Science Foundation of China (No. 21171054), the Open Fund Project of Key Laboratory in Hunan University (No. 11K029), Hunan Provincial Natural Science Foundation of China (No. 10JJ1004), and Aid program for Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Province.

■ Figure 12. Experimental values (symbols) and model predictions (solid line) of performance factors as a function of pH. Conditions: organic solvent = dichloromethane; [BINAP−Cu]0 = 1.0 mmol/L; [PHG]0 = 2.0 mmol/L; temperature, 5 °C.

NOTATION PHG = D/L-phenylglycine BINAP = 2,2′-bis(diphenylphosphino)-1,1′-binaphthalene BINAP−Cu = [(S)-BINAP(CH3CN)Cu][PF6] (selector) k = distribution ratio, org/aq concentration, dimensionless kD = distribution ratio of D-enantiomer, org/aq concentration, dimensionless kL = distribution ratio of L-enantiomer, org/aq concentration, dimensionless KD = complexation equilibrium constant for D-enantiomer, dimensionless KL = complexation equilibrium constant for L-enantiomer, dimensionless Ka = acid dissociation constant, mol/L ee = enantiomeric excess, dimensionless f = the fraction of an enantiomer extracted into the organic phase, dimensionless pf = performance factor, dimensionless C = total concentration, mol/L [ ] = equilibrium concentration, mol/L T = temperature, °C

Greek Letters

α = enantioselectivity, dimensionless δ = species fraction, dimensionless Subscripts

D = D-enantiomer L = L-enantiomer w = aqueous phase org = organic phase 0 = initial value int = intrinsic Figure 13. Experimental values (symbols) and model predictions (solid line) of performance factor as a function of [BINAP−Cu]0. Conditions: organic solvent = dichloromethane; [PHG]0 = 2.0 mmol/ L; pH = 7.0; temperature, 5 °C.

Superscript

enantiomers is completely possible when about 16 theoretical stages are used.

(1) Maier, N. M.; Franco, P.; Lindner, W. Separation of enantiomers: Needs, challenges, perspectives. J. Chromatogr. A 2001, 906, 3. (2) Hungerhoff, B.; Sonnenschein, H.; Theil, F. Separation of enantiomers by extraction based on lipase-catalyzed enantiomerselective fluorous-phase labeling. Angew. Chem., Int. Ed. 2001, 40, 2492. (3) Wegman, M. A.; Heinemann, U; van Rantwijka, F.; Stolz, A.; Sheldon, R. A. Hydrolysis of D,L-phenylglycine nitrile by new bacterial cultures. J. Mol. Catal. B: Enzym. 2001, 11, 249. (4) Okudomi, M.; Shimojo, M.; Matsumoto, K. Easy separation of optically active products by enzymatic hydrolysis of soluble polymersupported substrates. Tetrahedron Lett. 2007, 48, 8540. (5) Miyako, E.; Maruyama, T.; Kamiya, N.; Goto, M. Enzymefacilitated enantioselective transport of (S)-ibuprofen through a supported liquid membrane based on ionic liquids. Chem. Commun. 2003, 2926. (6) Hensel, M.; Lutz-Wahl, S.; Fischer, L. Stereoselective hydration of (RS)-phenylglycine nitrile by new whole cell biocatalysts. Tetrahedron: Asymmetry. 2002, 13, 2629.

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ASSOCIATED CONTENT

S Supporting Information *

Detailed derivation process of the model; detailed derivation process for regression of the complexation equilibrium constants; information about the structure of the selector; chromatogram of enantiomeric separation of phenylglycine. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest. 15240

tot = tot

REFERENCES



Article

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Experimental and Model Study on Enantioselective Extraction of

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