Modeling the Phase Behavior of Essential Oils in Supercritical CO

Article pubs.acs.org/IECR

Modeling the Phase Behavior of Essential Oils in Supercritical CO2 for the Design of a Countercurrent Separation Column Cristina Gutiérrez, Juan Francisco Rodríguez, Ignacio Gracia, Antonio de Lucas, and M. Teresa García* Department of Chemical Engineering, University of CastillaLa Mancha, Avenida Camilo José Cela 13004 Ciudad Real, Spain S Supporting Information *

ABSTRACT: This work describes a generalized procedure for high pressure equilibrium calculations for terpene oils. A simple semiempirical model allows the prediction of the solubilities of essential oils at high pressure on the basis of the physicochemical properties of their compounds (molecular weight, boiling temperature, density, and solubility parameter). This easy model can be useful for the determination of the fractionation and for the preliminary scale-up and economic evaluation. The theoretical basis considers any essential oil composed of two types of components: oxygenated and nonoxygenated. Vapor−liquid equilibrium data of binary systems (terpenoids/CO2) are used to correlate the semiempirical model proposed. Validity of the prediction is checked by comparison with literature data concerning ternary systems (limonene + linalool + CO2) and real mixtures (lemon and orange oils + CO2). Finally, the simulation and optimization of a countercurrent column for the fractionation of terpenes from lemon oil are performed. reason, the solubilities of terpenoids in CO2 could be fitted as a function of pressure and temperature in order to generalize and predict easily the behavior of essential oils in a wide range of conditions. The aim of this work is the design of a countercurrent column for the fractionation of essential oils. The uncertainty about the VLE data could be overcome using a very simple semiempirical model to predict the solubilities of essential oils at high pressure on the basis of the physicochemical properties of their compounds. Vapor−liquid equilibrium data of binary systems (terpenoids/CO2) from the literature or determined in our research group are used to correlate the semiempirical proposed model. The selection of the terpene oils is based on the majority composition of several essential oils: lemon, mandarin, and citrus oils;3,14,15 bergamot oil;16 Coriandrum sativum;17 Lippia alba;18 or eucalyptus leaf oils.13 The fitted constants of the models are related to the physicochemical properties of the terpenoids in order to infer the predictions. The validity of estimations is checked by comparing the predicted solubilities of multicomponent mixtures with the values shown in the literature. Once the solubilities of terpenoids in CO2 are determined and confirmed, the design of a countercurrent column to separate lemon oil is proposed according to the distribution coefficients and separation factors previously calculated.

1. INTRODUCTION The properties of essential oils are attributed to the presence of terpene hydrocarbons or their derivatives such as oxygenated compounds, pigments, waxes, resins, and flavonoids.1 Generally, terpenes are obtained through traditional separation processes: steam or vacuum distillation, liquid−liquid extraction, and adsorption. Nevertheless, during distillation high temperatures are needed and some terpenes could be lost or damaged. Vacuum distillation could avoid the degradation of thermolabile compounds, but the quality of the final product is not achieved.2 Finally, during liquid−liquid extraction organic solvents are employed which involves an additional separation process to recover the essential oils.3 Compressed supercritical fluids (SCFs) have been proposed as an alternative for several extraction and purification processes since the separation of essential oils can be performed at low temperature, which makes them suitable to preserve the thermolabile compounds of the natural oils.4,5 Furthermore, high selectivity allows achieving different fractions from the natural compounds in a single step or sequential extractions, and in contrast to a liquid solvent, the selectivity of a supercritical solvent can be significantly changed by varying both pressure and temperature.6,7 Although supercritical carbon dioxide (scCO2) has been shown to be a promising and suitable technique for the fractionation of natural oils, there is an important lack of information on the vapor−liquid equilibrium (VLE) data. The solubility dependence of the terpene oils on pressure and temperature forms the basis for the design of the conditions in the separator unit. Nevertheless, the predictive capabilities of solubility models are rather limited and several authors concluded that it is mostly necessary to determine the solubility experimentally.8 Considering the general VLE behavior of terpenes in CO2, it was observed that all pure components behaved similarly on all pressures when subjected to different temperatures.9−13 By this © 2014 American Chemical Society

2. EXPERIMENTAL SECTION 2.1. Chemicals. Carbon dioxide (99.8%) was purchased from Carburos Metálicos España S.A. (Madrid, Spain). pCymene (1-methyl-4-isopropylbenzene; CAS Registry No. 9987-6) that was ≥97% pure was supplied by Sigma-Aldrich and Received: Revised: Accepted: Published: 12830

May 6, 2014 July 4, 2014 July 7, 2014 July 7, 2014 dx.doi.org/10.1021/ie501834h | Ind. Eng. Chem. Res. 2014, 53, 12830−12838

Industrial & Engineering Chemistry Research

Article

Figure 1. Schematic diagram of the high-pressure view cell setup. D valve, CO2 inlet; E valve, gas sample outlet; G1 and G2, liquid sample outlet; PG, pressure generator; PI-1, manometer; PI-2, pressure digital indicator; T, liquid supply tank; TI, temperature digital controller.

used without further purification. α-Terpinene ((1-methylethyl)-1,3-cyclohexadiene; CAS Registry No. 99-86-5) of 95% purity was supplied by Panreac and used without further purification. 2.2. Apparatus. A high-pressure variable-volume view cell Model ProVis 500 (from Eurotechnica, Germany) was used to perform the experimental measurements. Figure 1 shows a schematic diagram of the experimental setup consisting of a variable-volume cell with front and upper sapphire windows and light for visual observations. The cell has a maximum capacity of 50 cm3, and a piston system is provided to keep the pressure constant. All the system is heated externally by an air bath made of poly(methyl methacrylate) which resists temperatures up to 80 °C, which is the temperature inside the equilibrium chamber measured by a thermocouple coupled to a digital LED Model Testo 925 (Lenzkirch, Germany). p-Cymene or γ-terpinene is introduced into the cell and it is purged with CO2 at low pressure to remove the residual air. Then CO2 is allowed to flow into the cell through valve D and the operating pressure and temperature are reached. Once the temperature is stabilized and the desired pressure is achieved, the magnetic stirrer and the gear pump are turned on. When the equilibrium conditions are reached (∼48 h), stirring is stopped, and the mixture is allowed to repose in order to favor the separation of the phases. Samples from the top and the bottom of the equilibrium cell are withdrawn using capillary lines and needle valves (F and F1 for the vapor phase and G1 and G2 in the case of the liquid phase). After that, they are decompressed to atmospheric pressure and collected in glass vials placed in an ice bath in order to avoid the evaporation of the samples. Valves are also thermostatized at the same temperature as the equilibrium cell.

The manual pressure generator is employed to keep the pressure constant during sampling (±0.01 MPa). For the determination of the amounts of CO2 and terpene in each phase, two samples are withdrawn from the bottom and the top of the equilibrium cell. The vials are weighted in a precision analytical balance with 0.0001 g accuracy to determine the amount of terpene oil collected (0.1−0.2 g). The amount of CO2 is measured during the sampling through a gas meter.

3. DATA MODELING Semiempirical models reported in the literature19 and new proposals shown in this work are used to correlate experimental vapor−liquid equilibrium (VLE) data and to provide a high versatility for the prediction of the behavior of essential oils and CO2. The vapor phase is correlated following the traditional Chrastil’s equation19 which is based on the hypothesis that each molecule of solute (terpene) associates with k molecules of supercritical solvent (CO2) to form a solvate complex, which is in equilibrium with the system. ln S = C1 +

C2 + k ln ρ T

(1)

where S is the solubility in kg/m3, C1 is a constant dependent on the molecular weights of the solute and solvent and on the association constant, C2 is a constant dependent on the total heat of vaporization, T is the temperature in K, k is the association number of molecules in the solvate complex, and ρ is the CO2 density in kg/m3. The liquid phase is correlated according to a new and very simple empirical relationship. This equation is obtained as the best option from a wide set of different equations, where the 12831

dx.doi.org/10.1021/ie501834h | Ind. Eng. Chem. Res. 2014, 53, 12830−12838


Article

Table 1. Chemical Structures, Ranges of Pressure and Temperature, Experimental Method, and Source for the Binary System Terpenoids/Supercritical CO2

subscript j varies from 1 to 5. The properties of the terpenes are the following: MW is the molecular weight in g/mol, Tb is the boiling point temperature in K, ρ is the density in kg/m3, and δ is the solubility parameter calculated following the method previously described in the literature.20 Once the composition of the essential oils is defined, the prediction of the vapor− liquid equilibrium data for the essential oils in carbon dioxide could be achieved with the simple knowledge of the described properties. The essential oil solubility is the weighted average of the individual solubilities of each of the terpenes in CO2. The global procedure for the determination of VLE data for essential oils is described in Figure 2. The validity of the predictions is checked by comparison to literature data concerning ternary systems (limonene + linalool + CO2) and real mixtures (lemon and orange oils + CO2) which contain compounds whose VLE data are not described in the literature.

composition of the liquid phase is related to pressure and temperature. The versatile empirical relationship proposed in this work for the correlation of the liquid phase is xCO2 =

A1P + A 2 exp(P) T

(2)

where xCO2 is the mole fraction of CO2 in the liquid phase, Ai are the correlated variables, P is the pressure in MPa, and T is the temperature in K. Initially, the estimation of Ai, Ci, and k is carried out from experimental data obtained from the literature or in our research group (Table 1). They are calculated by performing a multiple linear regression and minimizing the sum of the square differences between experimental and calculated solubilities. Although there are some binary systems well described in the literature, there is also an important deficiency on VLE data of minority or uncommon compounds of the essential oils. The presence of the cited components could modify significantly the solubility of the terpenoids in CO2. By this reason, the fitted constants (Ai, Ci, and k) are related to the physical properties of the terpenes in order to get an empirical relationship which allows the prediction of new components whose VLE data in CO2 were not previously described in the literature. This semiempirical relationship, proposed in this work, provides an important tool for the generalization and prediction of minority species which will enhance the estimation of the global phase behavior of the essential oils. The equation which allows the calculation of Ai, Ci, or k constants from the physical properties of the terpenoids is Zi = zi ,1MW + zi ,2Tb + zi ,3ρ + zi ,4δ + zi ,5

4. RESULTS AND DISCUSSION The design of a countercurrent column for the separation of essential oils is mainly based on the knowledge of the vapor− liquid equilibrium. Nevertheless, the lack of data in the literature makes an initial estimation difficult. In this work, a very simple model is proposed to perform a first approach to the column design from the knowledge of the composition and some physicochemical properties of the main compounds that make up the essential oils. This section is divided into three parts: initially, in section 4.1 the correlation of binary systems is carried out to extract general conclusions and to compile VLE data. Next, in section 4.2 the validity of the approaches is performed by comparison with multicomponent mixtures. Finally, in section 4.3 the optimum number of stages of the

(3)

where Zi means A i, Ci , or k; z i,j means ai,j , ci,j , or k i (respectively); and the subscript i means 1 or 2 and the 12832



Article

Table 1 shows a good range of the available data from the literature about the equilibria of the selected terpenoids in CO2 as a function of pressure and temperature. VLE measurements of terpenoids are carried out in a pressure range from 0.78 to 13.34 MPa and in a temperature range from 303 to 343 K. Different methods could be employed to determine the vapor− liquid equilibria for the binary systems containing CO2/ terpenoids, but according to the literature the static method is the most commonly used.9−12 Figure 3 (and figures in the Supporting Information) shows the experimental data (symbols) and the correlation (lines) of the solubility of the binary system CO2/limonene at different temperatures. From the correlation of the experimental data following eqs 1 and 2, the constants Ai, Ci, and k are obtained. The values for the fitting constants employed in the solubility modeling of terpenoids using the semiempirical equation are shown in the Supporting Information (see Table SI1). In all cases, the deviations are below the values of the constants. According to Figure 3, it is observed that the semiempirical model tested for the liquid and vapor phases fit well the experimental data, but the model of Chrastil for the vapor phase presents a lower standard deviation than the semiempirical equation which describes the liquid phase. The values of Ai, Ci, and k constants should be in a narrow range since they belong to the same compound family, which implies similar structures and properties. Nevertheless, some differences in the values of Ai, Ci, and k of the different terpenoids are observed. From the study of the fitted constants and the chemical structures of the terpenes, the classification of data into different groups could be suggested. Thus, those compounds exhibiting an oxygen atom in their structure present higher molecular weights and boiling points which lead to lower solubility of the terpene in CO2. Following this argument, we propose the classification of terpenoids into oxygenated (linalool, carvone, and eucalyptol) and nonoxygenated compounds (limonene, γ-terpinene, α-pinene, and p-cymene) in order to get the fitting parameters which correlate the physicochemical properties of the compounds with Ai, Ci,

Figure 2. Process scheme to correlate and predict essential oil equilibrium data.

fractionation column and the solvent to feed ratio are determined. 4.1. Literature Data and Correlation of Binary Systems Terpenoids/CO2. Essential oils are a complex mixture of terpenes or their derived compounds, but data for natural and well-characterized oil mixtures with supercritical CO2 are scarce in the literature. Our approach considers that essential oils consist mainly of limonene, linalool, γ-terpinene, carvone, α-pinene, p-cymene, and eucalyptol. It is necessary to emphasize that large databases for CO2 and the cited terpenoids are available in the literature, which enhances the accuracy of the estimation of the constants but also increases the dispersion of the data.

Figure 3. Solubility of limonene in CO2. Symbols represent experimental data at (■) 313.8, (○) 323.2, and (△) 333.2 K obtained from ref 11, and lines represent the correlation at ()313.8, (---) 323.2, and (···) 333.2 K. 12833



Article

or k. The physicochemical properties required for the correlation of eq 3 are shown in Table 2.

VLE data have not been described in the literature, and the prediction of Ai, Ci, and k constants based on their properties is very useful for the prediction of their behaviors. In the case of lemon oil, limonene and citral are assumed to be the majority compounds, and in orange oil, the prediction of solubility is based on limonene, linalool, and citral. The solubility of lemon oil in CO2 is initially predicted. Gironi and Maschietti determined the composition of lemon oil by means of gas chromatographic analysis and concluded that the main classes of compounds were monoterpenes (93.7 wt %), monoterpene oxygenated derivatives (4.3 wt %), and sesquiterpenes (2 wt %).24 In this work, we consider that lemon oil could be modeled using limonene as a monoterpene and citral as a monoterpene oxygenated derivative because they are the most relevant compounds of each class, while the sesquiterpenes are minority components and we do not predict their behavior. The prediction of the Ai, Ci, and k constants of citral is carried out on the basis of the physicochemical properties shown in Table 3. Once the constants are obtained, the prediction of the VLE of lemon oil is achieved employing eqs 1 and 2 and considering the composition of the mixture. The experimental measurements are performed at 323.15 and 343.15 K in a pressure range between 8.1 and 13 MPa. The experimental and predicted values of the solubility of lemon oil are shown in the Supporting Information (see Table SI4). The predicted data fit accurately the experimental solubility, although as observed previously, deviation increases at high pressure. In this case, the average standard deviation is 4.6 kg of lemon oil/m3 of CO2. It is important to emphasize that the solubility of lemon oil could vary in comparison with its pure components (limonene and citral) because, when a component takes part in a complex real mixture, the accompanying compounds affect the global solubility. This could be the reason for the underestimation of the predicted data. Next, the prediction of the behavior of orange oil in CO2 is studied since this is a complex multicomponent mixture of terpenoids. The monoterpene content of orange peel oil depends on the origin of the oranges, and in this work three different compositions are studied (named as A, B, and C). In general, they present from 98.26 to 98.77 wt % monoterpenes, where the most common are limonene (∼95.35 wt %) and linalool (∼0.39 wt %) obtained from Budich and Brunner.25 Decanal and citral are also presented in the composition of the orange oil, but in this work only citral is considered in the mixture since decanal is not a terpenoid. As far as we know, VLE data of citral have not been studied yet, although it is present in several plants and fruits.26−31 According to the described procedure, the Ai, Ci, and k constants for citral are predicted based on its physicochemical properties (Supporting Information, Table SI4) and, considering the composition of the mixture,25 the prediction of the VLE of three different types of orange oil is achieved. Figure 4 shows the composition of the mixtures CO2 + orange peel oil (three types: A, B, C) determined

Table 2. Physicochemical Properties of the Terpenoidsa carvone p-cymene eucalyptol linalool limonene α-pinene γ-terpinene

MW (g/mol)

Tb (K)

ρ (g/L)

δ (MPa)1/2

150.22 134.22 154.25 154.25 136.24 136.23 152.23

504.15 450.15 449.15 471.65 449.65 428.65 458.15

960.00 857.00 922.50 863.00 841.10 858.00 850.00

19.70 19.76 19.04 19.58 17.91 19.30 18.47

a MW, molecular weight; Tb, boiling point temperature; ρ, density; δ, solubility parameter.

The values obtained from the fitting of the Zi (Ai, Ci, and k) constants using eq 3 attending the classification of oxygenated and nonoxygenated terpenes are shown in the Supporting Information (see Table SI2). The fit of the constants as a function of the molecular weight, the boiling point temperature, the density, and the solubility parameter of the terpenoids is so accurate that the values of solubility obtained overlay the correlation data shown in Figure 3. The low values of the standard deviation shown in Table SI2 (Supporting Information) confirmed that the fit of Ai, Ci, and k following eq 3 is highly accurate. 4.2. Prediction of Multicomponent Mixtures and Essential Oils. The feasibility of the prediction of the VLE data of terpenoids in CO2 is checked using the mixture of limonene and linalool. The ternary system limonene/linalool/ CO2 has been studied since they are considered to be key compounds of citrus oil, and they are the most difficult compounds to separate.21,22 The literature data are obtained from Cháfer et al.,21 and the comparison with the prediction is shown in the Supporting Information (see Table SI3) at 318.15 and 328.15 K in a pressure range between 7 and 11 MPa. According to the results, the proposed semiempirical model predicts well the solubilities of limonene and linalool in CO2, although higher deviations are observed at higher pressure. However, in the range of pressure between 7 and 9 MPa the prediction is accurate. These pressures are particularly relevant for the natural oils rich in terpenoids since they represent potential working conditions for the efficient application of the supercritical processes.23,24 The predicted values are underestimated, but according to the VLE data used for correlation,11 the maximum solubilities of the terpenoids at 323.15 K are 20 kg of limonene/m3 of CO2 and 15 kg of linalool/m3 of CO2. Experimentally, the mixture reaches solubility values of 133 kg of limonene/m3 of CO2 and 63 kg of linalool/m3 of CO2; the increase of solubility in the ternary mixture is attributed by some authors to the interactions between the compounds.13 With the aim of validating the semiempirical model, the prediction of the solubilities of natural oils in CO2 is carried out.24,25 The lemon and orange oils contain terpenoids whose Table 3. Physicochemical Properties of Citrala

a

MW, molecular weight; Tb, boiling poiont temperature; ρ, density; δ, solubility parameter. 12834



Article

Figure 4. Comparison between experimental solubility data25 for three different types of orange oils (A, B, and C) at (■) 313.15 and (△) 323.15 K, and predictions at ()313.15 and (− −)323.15 K.

Figure 5. Evolution of (a) distribution coefficients and (b) distribution coefficients expressed as solvent free of limonene and citral at 323.15 K (filled symbols) and 343.15 K (empty symbols).

12835



Article

decreased. Figure 6 shows the separation factor together with the solubility of lemon oil (previously calculated in Table SI4

experimentally (symbols) and by means of the proposed prediction (lines) at 313 and 323 K and in a pressure range from 7 to 13 MPa. In this case, the solubility of the ternary mixture (limonene, linalool, citral) is comparatively lower than those of the single components. According to the prediction of VLE for multicomponent mixtures which contain compounds described or not in the literature, the semiempirical model proposed is validated and the procedure can be used to estimate the solubilities of natural oils in CO2 in a range of temperatures between 313 and 333 K and at from atmospheric pressure up to 12 MPa. 4.3. Lemon Oil Fractionation. The most interesting application of the VLE data prediction for essential oils is the design of an equilibrium fractionation process.32 In order to develop the separation analysis for the study of a countercurrent extraction column which gets the fractionation of lemon oil using CO2, the knowledge of the phase behavior of the system is crucial. In this system, limonene and citral are assumed to be the majority components of lemon oil. With respect to a separation process, the distribution coefficients (Ki) are more relevant than the solubility. Ki is a key thermodynamic parameter, which is defined as the ratio of the mole fraction of the component in the top phase (yi) to that in the bottom phase (xi), and it is expressed by eq 4. y Ki = i xi (4)

Figure 6. Solubility and separation factor (αHVC/LVC) as a function of the density in the vapor phase for the system CO2−lemon oil at 323.15 and 343.15 K.

(Supporting Information)) in order to check the decrease of αHVC/LVC when the pressure and the solubility increase. The selection of the most suitable operational conditions to perform the separation process is carried out considering the separation factor and the solubility. In Figure 6 there are two regions where the separation process should not be carried out: low solubility and flooding of the column. At low solubility values (S < 4 kg/m3 of CO2) huge amounts of CO2 are necessary, which increases the operation cost of the process. When the difference in density between the liquid phase and the gas phase is below 150 kg/m3, the solubility enhances but the countercurrent flow cannot be assured and there could be flooding.34 Considering the density of the gas phase as the density of scCO2 and the density of the liquid phase similar to the density of lemon oil (∼855 kg/m3), the limit of this region is located at a density around 700 kg/m3. In the case of lemon oil, flooding problems were avoided because the maximum allowable solvent density was not reached in the range of the studied conditions. The establishment of the most suitable working conditions is based on the interception between the solubility and the separation factor avoiding the undesirable areas. These conditions correspond to 313.15 K/8.2 MPa, 323.15 K/8.8 MPa, and 333.15 K/10.1 MPa, where the solubility of lemon oil is between 6 and 15 kg of oil/m3 of CO2 and the separation factor is between 2 and 6. Similar conditions are shown in the literature to perform the fractionation of citrus oil.5,23 The most interesting application of this approach is related to the theoretical design of countercurrent columns. The separation of limonene and citral from lemon essential oil in a multistage process using scCO2 is analyzed. The studied variables are the number of theoretical stages and the solvent to feed ratio; the last variable is an indicator for operation costs. Figure 7 shows the influence of theoretical stages and solvent to feed ratio on the composition and the selectivity of limonene in the extract. According to Figure 7a, when the number of theoretical stages increases, the limonene composition (left abscissa axis) in the top of the fractionation column increases, but the selectivity decreases (right abscissa axis). Regarding Figure 7b, an increase in the solvent to feed ratio enhances the

Figure 5a shows the evolution of the distribution coefficients for the selected terpenoids in lemon oil. As it is shown, the increase in pressure produces an increase in Ki, due to the increase in the solubility of each compound. Considering the design of a column to separate the lemon oil mixture in which CO2 is used as supercritical solvent, the distribution coefficient of the compounds should be expressed as solvent free (Ki(solvent free)). The terpenoid which presents a distribution coefficient above 1 will be enriched in the gas phase and could be obtained as top product in the separation column.33 Figure 5b represents the distribution coefficients expressed as solvent free for the separation of the studied terpenoids in lemon oil by means of CO2. According to the values of Ki(solvent free) shown in Figure 5b, the nonoxygenated compounds are obtained as top product while the oxygenated terpenoids are enriched in the bottom phase along the studied interval of pressure and temperature analyzed. The lower solubility of citral may be explained due to the presence of an oxygen atom in its structure, its higher molecular weight, and its lower vapor pressure.13 According to the results shown in Figure 5, limonene is defined as the high volatility compound (HVC) and citral as the low volatility compound (LVC). To determine the feasibility for the separation in two main components of lemon oil, the calculation of separation factors (αHVC/LVC) between limonene and citral is performed. αHVC/LVC =

y x LVC KHVC = HVC KLVC x HVCyLVC

(5)

The separation process is enhanced when αHVC/LVC increases, while values of αHVC/LVC equal to unity inhibit a separation. As a general rule, higher values of the separation factor could be achieved at lower pressure because of the increasing capacity of the solvent which enhances the solubility of all compounds when pressure increases, but the selectivity of the process is 12836



Article

Figure 7. (a) Influence of the number of theoretical stages on the composition of the extract (left axis) and the selectivity (right axis) of limonene. (b) Effect of solvent to feed flow ratio on the selectivity (left axis) and the extraction recovery (right axis) of limonene for a countercurrent extraction of lemon oil.

■

ACKNOWLEDGMENTS Financial support from Consejeria de Educacion y Ciencia (PBI06-0139, PBI08-0248-9341), Junta de Comunidades de CastillaLa Mancha, Spain, and Tecnove-Fiberglass is gratefully acknowledged. We also acknowledge Spanish MEPSYD for providing an FPU grant for a Ph.D. student.

selectivity, but the recovery of limonene in the extract reaches a maximum from which an increase in the solvent to feed ratio does not significantly affect the recovery. In order to maximize the recovery of limonene in the top of the fractionation, the optimum number of stages in the studied working conditions is between 5 and 6 and the solvent to feed ratio is around 10.

■

5. CONCLUSIONS A generalized procedure for the prediction of high pressure equilibria of essential oils based on the physicochemical properties of the majority components (terpenoids) is proposed. The semiempirical model describes the liquid and vapor phases in a range of temperature between 313 and 333 K and at pressures up to 10 MPa reasonably. It can be applied for the interpolation of unmeasured solubility data or for the prediction of terpenes not described in the literature, but with known properties of the pure substances (molecular weight, density, boiling point temperature, and solubility parameter). The knowledge of the phase behavior allows the determination of the most suitable operational conditions to perform the fractionation of essential oils using a countercurrent column. Finally, a preliminary study about column design determined the minimum number of stages and the ratio between CO2 and the feed for the fractionation of lemon essential oil.

■

ASSOCIATED CONTENT

S Supporting Information *

Figures showing solubilities of different terpenoids in CO2 in a temperature range between 303.5 and 343.5 K and tables showing fitted constants, errors, correlation, and comparison between experimental and predicted solubility values. This material is available free of charge via the Internet at http:// pubs.acs.org.

■

REFERENCES

(1) Espinosa, S.; Diaz, S.; Brignole, E. A. Optimal design of supercritical fluid processes. Comput. Chem. Eng. 2000, 24 (2−7), 1301−1307. (2) Reverchon, E.; Sesti Osseo, L.; Gorgoglione, D. Supercritical CO2 extraction of basil oil: Characterization of products and process modeling. J. Supercrit. Fluids 1994, 7 (3), 185−190. (3) Diaz, S.; Espinosa, S.; Brignole, E. A. Citrus peel oil deterpenation with supercritical fluids: Optimal process and solvent cycle design. J. Supercrit. Fluids 2005, 35 (1), 49−61. (4) Raeissi, S.; Diaz, S.; Espinosa, S.; Peters, C. J.; Brignole, E. A. Ethane as an alternative solvent for supercritical extraction of orange peel oils. J. Supercrit. Fluids 2008, 45 (3), 306−313. (5) Sato, M.; Goto, M.; Hirose, T. Fractional extraction with supercritical carbon dioxide for the removal of terpenes from citrus oil. Ind. Eng. Chem. Res. 1995, 34 (11), 3941−3946. (6) Richter, M.; Sovová, H. The solubility of two monoterpenes in supercritical carbon dioxide. Fluid Phase Equilib. 1993, 85 (C), 285− 300. (7) Varona, S.; Martin, A.; Cocero, M. J.; Gamse, T. Supercritical carbon dioxide fractionation of Lavandin essential oil: Experiments and modeling. J. Supercrit. Fluids 2008, 45 (2), 181−188. (8) Wubbolts, F. E.; Bruinsma, O. S. L.; Van Rosmalen, G. M. Measurement and modelling of the solubility of solids in mixtures of common solvents and compressed gases. J. Supercrit. Fluids 2004, 32 (1−3), 79−87. (9) Gamse, T.; Marr, R. High-pressure phase equilibria of the binary systems carvone-carbon dioxide and limonene-carbon dioxide at 30, 40 and 50°C. Fluid Phase Equilib. 2000, 171, 165−174. (10) Matos, H. A.; De Azevedo, E. G.; Simoes, P. C.; Carrondo, M. T.; Da Ponte, M. N. Phase equilibria of natural flavours and supercritical solvents. Fluid Phase Equilib. 1989, 52, 357−364. (11) Chang, C.-M. J.; Chen, C.-C. High-pressure densities and P-T-xy diagrams for carbon dioxide+linalool and carbon dioxide+limonene. Fluid Phase Equilib. 1999, 163 (1), 119−126. (12) Akgün, M.; Akgün, N. A.; Dinçer, S. Phase behaviour of essential oil components in supercritical carbon dioxide. J. Supercrit. Fluids 1999, 15 (2), 117−125. (13) Francisco, J. d. C.; Sivik, B. Solubility of three monoterpenes, their mixtures and eucalyptus leaf oils in dense carbon dioxide. J. Supercrit. Fluids 2002, 23 (1), 11−19.

AUTHOR INFORMATION

Corresponding Author

*Tel.: +34-926295300, ext 3511. Fax:+34-926-295318. E-mail: [email protected]. Author Contributions

The manuscript was written through the contributions of all authors. All authors have given approval to the final version of the manuscript. Notes

The authors declare no competing financial interest. 12837



Article

countercurrent gas extraction column. J. Supercrit. Fluids 2011, 57 (1), 1−8. (34) Wypych, G. Handbook of Solvents. ChemTec Publishing: Toronto, 2001.

(14) Danielski, L.; Brunner, G.; Schwänke, C.; Zetzl, C.; Hense, H.; Donoso, J. P. M. Deterpenation of mandarin (Citrus reticulata) peel oils by means of countercurrent multistage extraction and adsorption/ desorption with supercritical CO2. J. Supercrit. Fluids 2008, 44 (3), 315−324. (15) Franceschi, E.; Grings, M. B.; Frizzo, C. D.; Oliveira, J. V.; Dariva, C. Phase behavior of lemon and bergamot peel oils in supercritical CO2. Fluid Phase Equilib. 2004, 226 (1−2), 1−8. (16) Chiyoda, C.; Capellini, M. C.; Geremias, I. M.; Carvalho, F. H.; Aracava, K. K.; Bueno, R. S.; Gonçalves, C. B.; Rodrigues, C. E. C. Deterpenation of bergamot essential oil using liquid-liquid extraction: Equilibrium data of model systems at 298.2 K. J. Chem. Eng. Data 2011, 56 (5), 2362−2370. (17) Grosso, C.; Ferraro, V.; Figueiredo, A. C.; Barroso, J. G.; Coelho, J. A.; Palavra, A. M. Supercritical carbon dioxide extraction of volatile oil from Italian coriander seeds. Food Chem. 2008, 111 (1), 197−203. (18) Braga, M. E. M.; Ehlert, P. A. D.; Ming, L. C.; Meireles, M. A. A. Supercritical fluid extraction from Lippia alba: Global yields, kinetic data, and extract chemical composition. J. Supercrit. Fluids 2005, 34 (2), 149−156. (19) Chrastil, J. Solubility of solids and liquids in supercritical gases. J. Phys. Chem. 1982, 86 (15), 3016−3021. (20) Gutiérrez, C.; García, M. T.; Gracia, I.; De Lucas, A.; Rodríguez, J. F. A practical approximation to design a process for polymers recycling by dissolution. Afinidad 2011, 68 (553), 181−188. (21) Cháfer, A.; Berna, A.; Montón, J. B.; Mulet, A. High Pressure Solubility Data of the System Limonene + Linalool + CO2. J. Chem. Eng. Data 2001, 46 (5), 1145−1148. (22) Vieira de Melo, S. A. B.; Costa, G. M. N.; Uller, A. M. C.; Pessoa, F. L. P. Modeling high-pressure vapor-liquid equilibrium of limonene, linalool and carbon dioxide systems. J. Supercrit. Fluids 1999, 16 (2), 107−117. (23) Kondo, M.; Akgun, N.; Goto, M.; Kodama, A.; Hirose, T. Semibatch operation and countercurrent extraction by supercritical CO2 for the fractionation of lemon oil. J. Supercrit. Fluids 2002, 23 (1), 21−27. (24) Gironi, F.; Maschietti, M. Phase equilibrium of the system supercritical carbon dioxide-lemon essential oil: New experimental data and thermodynamic modelling. J. Supercrit. Fluids 2012, 70, 8−16. (25) Budich, M.; Brunner, G. Vapor−liquid equilibrium data and flooding point measurements of the mixture carbon dioxide+orange peel oil. Fluid Phase Equilib. 1999, 158, 759−773. (26) Mesomo, M. C.; Corazza, M. L.; Ndiaye, P. M.; Dalla Santa, O. R.; Cardozo, L.; Scheer, A. D. P. Supercritical CO2 extracts and essential oil of ginger (Zingiber officinale R.): Chemical composition and antibacterial activity. J. Supercrit. Fluids 2013, 80, 44−49. (27) Marongiu, B.; Piras, A.; Porcedda, S.; Tuveri, E. Comparative analysis of the oil and supercritical CO2 extract of Cymbopogon citratus Stapf. Nat. Prod. Res. 2006, 20 (5), 455−459. (28) Carlson, L. H. C.; Machado, R. A. F.; Spricigo, C. B.; Pereira, L. K.; Bolzan, A. Extraction of lemongrass essential oil with dense carbon dioxide. J. Supercrit. Fluids 2001, 21 (1), 33−39. (29) Argenta, L. C.; Mattheis, J. P.; Fan, X.; Finger, F. L. Production of volatile compounds by Fuji apples following exposure to high CO2 or low O2. J. Agric. Food Chem. 2004, 52 (19), 5957−5963. (30) Besada, C.; Sanchez, G.; Salvador, A.; Granell, A. Volatile compounds associated to the loss of astringency in persimmon fruit revealed by untargeted GC-MS analysis. Metabolomics 2013, 9 (1), 157−172. (31) Kirbalar, Š. I.; Gök, A.; Kirbašlar, F. G.; Tepe, S. Volatiles in Turkish clementine (Citrus clementina Hort.) peel. J. Essent. Oil Res. 2012, 24 (2), 153−157. (32) Gracia, I.; García, M. T.; Rodríguez, J. F.; Fernández, M. P.; de Lucas, A. Modelling of the phase behaviour for vegetable oils at supercritical conditions. J. Supercrit. Fluids 2009, 48 (3), 189−194. (33) Fernández-Ronco, M. P.; Gracia, I.; Zetzl, C.; De Lucas, A.; García, M. T.; Rodríguez, J. F. Equilibrium data for the separation of oleoresin capsicum using supercritical CO2: A theoretical design of a 12838


Modeling the Phase Behavior of Essential Oils in Supercritical CO

Recommend Documents