Kinetics of Cholesterol Extraction Using ... - ACS Publications

Aug 5, 2008 - ... Chennai–600020, India,. Monash UniVersity, P. O. Box 8975, Sunway Campus, 46780 Kelana Jaya, Selangor, Malaysia, and Technische...
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Ind. Eng. Chem. Res. 2008, 47, 6727–6733

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SEPARATIONS Kinetics of Cholesterol Extraction Using Supercritical Carbon Dioxide with Cosolvents N. Vedaraman,† C. Srinivasakannan,*,‡ G. Brunner,§ and P. G. Rao† Chemical Engineering DiVision, Central Leather Research Institute, Sardar Patel Road, Chennai–600020, India, Monash UniVersity, P. O. Box 8975, Sunway Campus, 46780 Kelana Jaya, Selangor, Malaysia, and Technische UniVersitaet Hamburg-Harburg, Eissendorfer Strasse 38, 21073 Hamburg, Germany

Cattle brain is rich in lipids including cholesterol. As a alternative process to extract cholesterol, the ecofriendly solvent supercritical carbon dioxide (SC CO2), along with different cosolvents such as acetone, 2-propanol, and ethanol, was used in an attempt to understand the effect of cosolvents. A maximum of 53% of the total cholesterol in the brain sample could only be extracted either using pure SC CO2 or using cosolvents along with SC CO2. Although the total amount of cholesterol extracted did not differ with the addition of cosolvents, the rate of extraction was found to increase significantly with the addition of cosolvents in small quantities. The kinetics of extraction using pure SC CO2 as well SC CO2 with cosolvents was modeled using conventional differential mass balance equation for packed beds. The effective diffusivity coefficient was found to double with cosolvent acetone, while found to be more than three times with cosolvents 2-propanol and ethanol in comparison with the pure SC CO2. The effective diffusivity coefficient was found to be of the order of 10-13 m2/s, for extraction of cholesterol from cattle brain, either with SC CO2 or SC CO2 with cosolvents. 1. Introduction Animal organs such as brain and liver contain large amounts of lipids which include cholesterol. Cholesterol is the major sterol present in the animal kingdom and is present in various parts of the body to an extent of 2-5 wt % as totally free, bound, and esterified forms with higher fatty acids. Cholesterol is industrially prepared from the brain and spinal cord of cattle. It is an important raw material for the preparation of a large number of pharmaceuticals such as vitamin D3 and finds use in several cosmetic preparations. Cow brain although edible is not being eaten by large sections of people, due to high cholesterol content in addition to the recent threat of bovine spongiform encephalopathy. The residual brain material after cholesterol extraction, which is rich in protein, can be used as a protein food.1 There are several reported methods to extract the cholesterol, and most of them employ toxic solvents such as dichloroethane (DCE).2 In contrast, carbon dioxide is an ecofriendly solvent, but under normal conditions its solvent power is small. However, under supercritical (SC) conditions, it is a good solvent for many compounds including cholesterol. Application of supercritical fluids (SCF), especially carbon dioxide for biomaterial extraction, has been well-known for several years due to its advantages over the conventional organic extraction methods. A wide range of application of SCF for a variety of selective separations has been detailed in literature. Some which is relevant to the present work include extraction of cholesterol and other lipids from spraydried egg yolk powders,3,4 extraction of lipids and cholesterol from fish muscles,5,6 reduction of cholesterol and total lipid content of the ground beef,7 and extraction of lipids from meat products.8 * To whom correspondence should be addressed. † Central Leather Research Institute. ‡ Monash University. § Technische Universitaet Hamburg-Harburg.

Extraction of cholesterol from cattle brain using SC CO2 has been detailed in our earlier publication.9 The present work attempts to investigate the effect of cosolvents added in small quantities to the SC CO2 in terms of assessing the rate of extraction and the total amount of extractable cholesterol. Further attempts are made to model the kinetics of cholesterol extraction, and the unknown model parameter effective diffusivity coefficient is estimated. 2. Experimental Section Experiments are carried out using the experimental setup as shown in Figure 1, detailed subsequently in section 2.3, to investigate the extraction of cholesterol from cattle brain either by using pure SC CO2 or SC CO2 along with cosolvents such as acetone, ethanol, and 2-propanol added in small quantities ranging from 2 to 6 wt % SC CO2. The experiments are conducted for different time periods, under identical conditions, to estimate the amount of cholesterol extracted. The total amount of extractable cholesterol as well as the rate of extraction of cholesterol, is calculated from the experimental data. The details of the methods of analysis of cholesterol are detailed in section 2.5. The experimental data are represented in the form of relative cholesterol concentration (Cs/Ci) against the time of extraction in Figures 2–6 for various cosolvents, in comparison with pure SC CO2. Cs/Ci is the ratio of the concentration of cholesterol remaining within the brain particles to the concentration of cholesterol initially present. Each of the experiments is repeated to ensure the repeatability of the data. The experimental data are found to vary within an acceptable maximum error of (2%. An average of the two sets of data is utilized and is represented as data points in Figures 2–6. 2.1. Materials. The cow brain obtained from the slaughterhouse (Lipeck & Richer, Hamburg, Germany) is washed and cut into small pieces and freeze-dried at -50 °C for 72 h. After removing the moisture totally, the brain sample is ground

10.1021/ie070703q CCC: $40.75  2008 American Chemical Society Published on Web 08/05/2008

6728 Ind. Eng. Chem. Res., Vol. 47, No. 17, 2008

Figure 1. Schematic diagram of the experimental set up: (a) compressor, (b) extractor, (c) separator, (d) mass flow meter, and (e) constant-temperature bath; V1, V2, and V3, pressure control valves; T1 and T2, thermocouples; PG1 and PG2, pressure gauges.

Figure 3. Comparison of extraction of cholesterol using pure SC CO2 with SC CO2 with 2-propanol at different amounts (wt %) of cosolvent: d, 6.45 × 10-4 m; T, 60 °C; Gsc, 3 kg/h; P, 250 bar.

Figure 4. Comparison of extraction of cholesterol using pure SC CO2 with SC CO2 with ethanol at different amounts (wt %) of cosolvent: d, 6.45 × 10-4 m; T, 60 °C; Gsc, 3 kg/h; p, 250 bar. Figure 2. Comparison of extraction of cholesterol using pure SC CO2 with SC CO2 with acetone at different amounts (wt %) of cosolvent: d, 6.45 × 10-4 m; T, 60 °C; Gsc, 3 kg/h; p, 250 bar.

manually. The ground particles were sieved, to a size range of 600-710 µm using DIN Standard Sieves. 2.2. Chemicals. Acetone, 2-propanol, and ethanol used for extraction were of analytical grade (SD Fine Chemicals). 2.3. Extraction. The experimental setup consists of a compressor (a), extractor (b), separator (c), mass flow meter (d), and constant-temperature baths (e) (Julabo, Seelbach, Germany), and the schematic diagram is shown in Figure 1. The compressor is a part of supercritical extractor (NOVA Werke AG, Effretikon, Switzerland), which has two pumps with the maximum discharge pressure of 800 bar. The extractor is made of stainless steel grade 316 with an internal diameter of 16.5 mm and length of 330 mm, while the separator is a 250 mL vessel (saturator), and part of NOVA extractor (NOVA Werke AG). The cosolvent pump is an HPLC pump (Shimadzu LC 10 A), which can compress the liquid to the operating pressure. The freeze-dried and powdered brain samples were carefully placed inside the tube, and the tube was closed, after placement of both cotton and wire mesh on both of the extractor ends. The extractor and the separator are placed in the appropriate

Figure 5. Comparison of extraction of cholesterol using pure SC CO2 with SC CO2 with acetone, 2-propanol, and ethanol at optimum amounts of cosolvent: d, 6.45 × 10-4 m; T, 60 °C; Gsc, 3 kg/h; P, 250 bar.

bath in order to maintain the extraction and separation temperatures. Gaseous carbon dioxide from the storage tank is then compressed to the required pressure and sent into the extractor.

Ind. Eng. Chem. Res., Vol. 47, No. 17, 2008 6729

also analyzed using pulsed FT-NMR spectrometer (MSL 300P, Bruker) by dissolving the extracted cholesterol in CDCl3 (200 mg/mL). 3. Modeling

Figure 6. Comparison of model prediction with the experimental data: d, 6.45 × 10-4 m; T, 60 °C; Gsc, 3 kg/h; P, 250 bar.

The extracting gas is heated to the extraction temperature, by passing the gas through the coils immersed in a constanttemperature bath in which the extractor was also immersed. The cosolvent pump (HPLC pump) compresses the liquid to the operating pressure and gets mixed with carbon dioxide before it enters into the extractor. The high-density, pressurized carbon dioxide passes through the packed bed from the bottom to the top. The mass flow rate is recorded using a digital mass flow meter (RHE-01, Rheonik). Both the extractor and separator are fitted with pressure gauges by which the pressure can be read within a 5 bar accuracy. The temperature of the extractor and the separator are measured by thermocouples T1 and T2, respectively. The extraction is a semicontinuous process with the batch of solids continuously contacted with fresh solute free solvent, entering at the bottom of the bed of particles held in extractor column b. In the extractor column, the brain material is packed with four layers of packing material (raschig rings) in order to avoid channel formation of the solvent during extraction. The carbon dioxide and extracted solute, after passing through the extractor column, passes through a preheated expansion valve, which is maintained at 60 bar and 42 ( 1 °C. The pressure drop causes the solute and cosolvent to separate from carbon dioxide in the separator c. The low-density/low-pressure solute free carbon dioxide is then recycled to the compressor and heat exchanger, which resort to high density and high pressure. The pressure drop due to sampling is compensated by purging fresh carbon dioxide by opening valve V3, and the experiments are continued. 2.4. Characterization of Brain before and after Cholesterol Extraction. Protein content (Kjeldahl method), total lipids, cholesterol and cholesteryl esters, and phospolipids were analyzed as per the well-known methods9 in the brain sample before and after extractions. The chemicals used are analytical grade (AR) reagents obtained from SD Fine Chemicals. 2.5. Extracted Cholesterol Analysis. The purity of extracted cholesterol was analyzed by gas chromatography (Auto System XL, gas chromatograph, Perkin-Elmer) after silylation using N-methyl-N-trimethylsilylheptofluorobutyamide (MSHFBA; Mekery-Nagel).10 The extracted cholesterol is also analyzed for its melting, crystal-crystal transition temperatures using differential scanning calorimetry (DSC; Model 2910, Du Pont) at a heating rate of 5 °C/min. Extracted cholesterol was then characterized for its structure using FT-IR (Avatar Model 360, Nicolet) by potassium bromide (KBr) pellet. Measurements are made between 4000 and 400 cm-1 wavenumbers. The samples are

Different authors have described modeling of the extraction process using supercritical fluids in different ways. The extraction process is widely modeled either by differential mass balance equation, in the case of extraction in packed columns or by simple lumped parameter model which basically expresses the concentration profile inside the solid particle as a function of time, assuming all the particles are exposed to the same extraction conditions.11–14 The differential mass balance equation is widely used to model packed beds for processes such as adsorption and extraction, etc. The differential mass balance across the column, as popularly given in textbooks,15 is utilized in the present study, eliminating the term accounting for axial dispersion of solute in the bed as follows: uV

∂Cf ∂Cs ∂Cf + εV + (1 - ε)V )0 ∂h ∂t ∂t

(1)

Basically the difference among various models depends on the method in which the change in concentration of the solute with respect to time is expressed. In general the transport in solids can be classified in two categories: (1) diffusion not dependent on the structure of the solid and (2) diffusion dependent on the structure and void channel of the particles. The first category assumes that the solute diffusing is actually dissolved in the solids to form a more or less homogeneous solution. This process is popularly expressed using Fick’s law of diffusion, which represents the change in the concentration profile inside the solid particle with respect to time and position. Another simpler way of expressing the rate of extraction is by using a simple mass-transfer equation involving the masstransfer coefficient and the concentration driving force.16,17 This does not explain the mechanism of transfer from the solids; rather it tries to fit experimental data with the mass-transfer coefficient which is expressed to account for both the external and internal mass-transfer resistances. The rate of extraction is represented as δCs ) kmap(Co - Csj) δt

(2)

where kmap )

1 1 ⁄ kfap + Rp2 ⁄ 15εpDe

(3)

As mentioned earlier eq 3 represents a linear combination of the mass-transfer resistance corresponding to external mass transfer from the particle surface to bulk liquid phase and the internal pore diffusion with the particle. The present model utilizes the concept of Fick’s law to represent the kinetics of extraction. The concentration profile in the solid phase is defined using Fick’s diffusion equation as follows:

[

∂2Cs 2 ∂Cs ∂Cs ) De + ∂t r ∂r ∂r2

]

The boundary conditions are Cs)Ci for t ) 0, 0 e r e R

(4)

6730 Ind. Eng. Chem. Res., Vol. 47, No. 17, 2008

δCs ⁄ δr ) 0 for t > 0, r ) 0 -De δCs ⁄ δr ) k(Co - Csj) for t > 0, r ) R where Co is the actual concentration just within the sphere and Csj is the concentration required to maintain equilibrium with the surrounding atmosphere. ε is the bed porosity, V is the extractor volume, Cf is the concentration of solute in the fluid phase, Cs is the concentration of solute in the the solid phase, u is the superficial solvent velocity, h is the spatial coordinate along the bed, t is the time of extraction. Ci is the initial concentration of solute in the solid phase, and k is the external mass-transfer coefficient. The fixed bed is divided into n number of stages, and in each stage the fluid- and solid-phase composition is assumed to be uniform. This represents the description of a plug flow extractor through a series of mixed flow extractors. Thus, eq 1 can be transformed into a differential equation of the form V dCfn V dCsn W (Cfn - Cfn-1) + ε + (1 - ε) )0 F n dt n dt

[

]

(5)

where W is the mass flow rate of carbon dioxide, F is the solvent density, Csn is the solid-phase concentration in the nth stage, Cfn is the fluid-phase concentration in the nth stage, and n is the number of stages assumed to solve the differential equation. Equations 4 and 5 are solved simultaneously using finite element method and the Ruge-Kutta-Gill method, by varying the effective diffusivity coefficient to minimize the error between the model prediction and the experimental data. The mass-transfer coefficient, k, is obtained using Wakao and Kaguei,18 where Sh ) 2 + 1.1Re0.6Sc0.3

(6)

where Sh ) kd/D12. The diffusion coefficient of cholesterol in the supercritical fluid carbon dioxide is predicted using the equation due to Catchpole and King19 as follows: D12 ) 5.152DcTr(Fr-2⁄3 - 0.451)K ⁄ X

(7)

where Dc ) 4.30 × 10-7M11⁄2Tc10.75 ⁄ (∑V12⁄3Fc) where X)

[1 + (Vc2 ⁄ Vc1)1⁄3]2 [1 + (M1 ⁄ M2)]

The correction factor K is defined as the ratio of binary to selfdiffusion coefficient as follows: K ) 1 ( 0.1 2 < X K ) X0.17 ( 0.1 2 < X < 10 Tr is the reduced temperature, Dc is the self-diffusion coefficient of CO2 at the critical point (4.937 × 10-8 m2/s), Fr is the reduced density, K is the correction factor, Vc is the molar volume at the critical point, M is the molar mass, subscript 1 refers to CO2, and subscript 2 refers to cholesterol. Substitution of appropriate values in eq 7 results in D12 ) 2.308 × 10-8KTr(δr-2⁄3 - 0.451)

(8)

Although there might be a theoretical variation in the value of D12 due to the influence of the cosolvents, its effect may be considered to be negligible as the amount of cosolvents are low.

The appropriate effective diffusion coefficient that fits the experimental data with the solution of the eqs 4 and 5 was obtained by minimizing root-mean-square error (RMSE) as follows: RMSE )



∑ (C

sa,exp - Csa,pred) 2

ndp - 1

(9)

The estimated effective diffusivity coefficients along with the RMSE values are listed in Table 4. 4. Results and Discussion The extraction of cholesterol from cow brain using pure SC CO2 has been reported in our earlier publication,9 which covers the effect of extraction operating parameters such as the pressure, temperature, and flow rate of the SCF. The optimum conditions of extraction derived from our earlier study has been utilized for assessing the effect of various cosolvents such as acetone, 2-propanol, and ethanol added in percentages ranging from 2 to 6 along with the pure SC CO2. These solvents are not toxic, and they are widely used in many industries. The addition of a relatively small amount of cosolvent in the SCF can improve the solubility of the solvent. Cosolvents are liquids or gaseous material, which increase the solubility of the interested compound in SC phase. The addition of cosolvent will generally increase the mixture density, which may also contribute to the overall solubility enhancement. Figures 2–4 are the plots of the experimental data in terms of the relative concentration of cholesterol in cow brain (Cs/Ci) with respect to extraction time, for the various cosolvents, showing the effect of the concentration of the cosolvent. In all experiments the amount of cholesterol extracted after 5 h range from 50 to 53% of the total cholesterol present in the brain sample irrespective of the solvent being either pure SC CO2 or SC CO2 with cosolvents (figures show the relative concentration of the unextracted cholesterol). It should be noted that the amount extracted using supercritical carbon dioxide is higher compared to a conventional method of extraction1 using a large amount of dichloroethane, where only 48% of the total cholesterol could be extracted. The rest of the cholesterol may not be in a free form; instead they are bound with phospholipids by specific attachment as reported in the literature.20 Figures 2–4 show an increase in the amount of cholesterol extracted or in other words a lower relative concentration of cholesterol in the cow brain using SC CO2 with cosolvents as compared to extraction with pure SC CO2.. The increase in the rate of extraction is not linear with the increase in the amount of cosolvents, and the addition of cosolvents is effective only until an optimum amount. With acetone as the cosolvent (Figure 2), the rate of extraction is not altered as the amount of acetone is varied from 2 to 6%. However, in the case of 2-proponal a significant increase in the rate of extraction is observed with the increase in the amount of cosolvent from 1 to 2.22% (Figure 3), with no further increase beyond. Similarly with ethanol a significant increase in the rate of extraction was observed with the increase in the amount of cosolvent from 1.5 to 3% (Figure 4) with no further increase beyond. In general, it can be summarized that the rate of extraction of cholesterol increased with the addition of cosolvent and the optimum amount varied with the type of cosolvent, varying within a maximum of 3%. The optimum amount was found to be less than 2% with acetone as cosolvent, while with 2-propanaol it was between 1 and 2.25% and with ethanol between 1.5 and 3%. Figure 5 compares the relative magnitude of the

Ind. Eng. Chem. Res., Vol. 47, No. 17, 2008 6731 Table 1. Physical Properties of Carbon Dioxide, Cosolvents, and Cholesterol cosolvent

π*

R

β

µ (D)

acetone 2-propanol ethanol CO2 cholesterol

0.71 0.48 0.54

0.06 0.76 0.83

0.48 0.95 0.77

2.9 1.7 1.7 0 2.0

three cosolvents, and it can be observed that the rate of extraction with 2-propanol and ethanol is significantly higher than the acetone as the cosolvent. A higher affinity of ethanol than acetone for cholesterol solubilization, using SCF with cosolvents, have been reported by Tavana et al.,21 This may be due to possible chemical interaction between these cosolvents and cholesterol. The probable mechanism for varying rates of extraction in different cosolvents can be explained by considering their polarity and hydrogen-bonding interactions with cholesterol. Table 1 shows physical properties of various cosolvents studied along with their Kamlet-Taft solvatochromic parameters (π*, R, β)22 and the dipole moments (µ). The parameter R indicates the ability of the solvent to donate hydrogen bonds, β denotes the ability to accept hydrogen bonds, and π* is a measure of solvent polarity/polarizability. It is stressed that R and β are only indications of hydrogen-bonding ability. Acetone does not undergo self-association and is solely a hydrogen bond acceptor. Even though acetone is polar due to the presence of a C · · · O bond, the H-bonding capacity is less compared to ethanol and isopropyl alcohol. This is because of higher β values for ethanol and isopropyl alcohol as compared to acetone. In addition, they also possess a higher R value. So these alcohols can act both ways as hydrogen donor and acceptor. In view of these, it is proposed that the hydrogen-bonding interactions between isopropyl alcohol, ethanol, and cholesterol are the contributing factor for a higher extraction rate. The increase in extraction rate with an increase in the concentration of the cosolvent is only until a critical concentra-

tion beyond which the extraction rate remains constant. This is probably due to increased interaction with solute molecules until the critical concentration with a further increase in the amount of solvent leads to self-association of solvents. Table 2 shows quantitative estimations of various lipids present in brain before and after SC extraction, in which the dried brain sample initially contains 20% cholesterol, out of which, after SC extraction of the brain, the amount of cholesterol removed from the brain was approximately 53% of the total cholesterol (10.6% on a dry brain basis). This shows that only slightly more than 50% of the initial amount of cholesterol can be removed from the brain. The remaining cholesterol present in bound form with other lipids was not extracted even with polar solvents such as ethanol or 2-propanol. There is not much change in the phospolipids content before and after extraction, and the protein content remained almost the same. This also seems to be true with comparison to the conventional method of extraction using a large amount of dichloroethane, where only 48% of the total cholesterol was extracted with 1:20 wt/vol after the first step and 100-fold concentration, and the rest (42%) was obtained after hydrolysing with alcoholic potassium hydroxide and subsequent extraction with petroleum ether. The DSC thermal data and FT-IR spectral data along with GC analysis results of extracted cholesterol are given in Table 3. SCF extraction with propanol or ethanol as cosolvents gave higher purity compared to pure CO2 and CO2 with an acetone mixture. The DSC results show that the standard cholesterol before crystallization does not show any crystal-crystal transition. In the case of extracted cholesterol by SC CO2, CO2 + acetone, CO2 + 2-propanol, and CO2 + ethanol and solvent extraction (DCE), the crystal-crystal transitions were at 3436 °C. The melting temperatures were in the range of 142-147 °C. The crystal-crystal transitions and melting transition and respective enthalpy changes were comparable with the reported values.23 The lower melting temperature for cholesterol extracted by the SC CO2 method may be attributed to the low purity of the sample as indicated by GC.

Table 2. Composition of Brain before and after Supercritical Extraction % based on dry matter extraction methods

total lipidsa

protein content

total cholesterol

cholesteryl esters

phospholipids

unextracted brain brain after CO2 brain after CO2 + acetone brain after CO2 + 2-propanol brain after CO2 + ethanol brain after DCE (in two steps)

60.1 49.69 50.10 50.21 50.45 6.0

39.00 39.00 38.92 39.00 38.99 38.96

20 9.61 9.45 9.36 9.30 2.0

0.026 0.021 0.020 0.022 0.023 0.024

20.2 20.0 20.1 19.9 19.8

a

Includes total cholesterol (free, bound, and esterified), phospolipids, and other lipids.

Table 3. Comparison of DSC, GC, and IR Data of Cholesterol Extracted by Different Methods IR DSC

system std cholesterol (recrystallized) SC CO2 extracted cholesterol solvent (DCE) extracted cholesterol SC CO2 + acetone extracted cholesterol SC CO2 + 2-propanol extracted cholesterol SC CO2 + ethanol extracted cholesterol

bending vibrations (cm-1)

stretching vibrations (cm-1)

crystal-crystal transition melting GC assay % olefinic aliphatic aliphatic aliphatic aliphatic aliphatic temp (°C) temp (°C) purity OH- C-H C-H C-H C-H C-H CdC C-O C-H

C-H

34 35 35

149 142 144

98 86 91

3402 3426 3417

3036 3036 3034

2961 2963 2967

2932 2929 2929

2870 2866 2864

2847 2848 2849

1673 1056 1670 1055 1657 1055

1465 1465 1465

1378 1376 1378

36

146

91

3424

3030

2965

2928

2866

2842

1673 1056

1466

1379

34

146

93

3424

3037

2960

2931

2866

2848

1673 1056

1465

1378

35

147

93

3404

3037

2960

2932

2866

2848

1661 1056

1466

1377

6732 Ind. Eng. Chem. Res., Vol. 47, No. 17, 2008 Table 4. Evaluated Effective Diffusivity Coefficient (Deff) S no. 1 2 3 4

extraction method SC SC SC SC

CO2 CO2 CO2 CO2

extraction + acetone extraction + 2-propanol extraction + ethanol extraction

amount of cosolvent (wt %)

Gsc (kg/h), T (C), P (bar)

Deff × 1013 (m2/s)

RMSE

-4 3.5 3.0

3, 60, 250 3, 60, 250 3, 60, 250 3, 60, 250

2.3 4.8 8.0 8.0

0.021 0.011 0.007 0.008

FT-IR spectra of the cholesterol extracted by various methods are compared with standard cholesterol, for the characteristic vibrational frequencies of cholesterol molecule. All these signals were noticed with comparable vibrational frequencies in extracted cholesterol by different methods. The peak-to-peak correlation of standard cholesterol matches very well with the cholesterol extracted by different methods. This clearly indicates the structural similarity of the compounds extracted by using various methods using SCFE with cosolvents. In addition to FT-IR spectroscopy, proton and 13C NMR measurements were made to confirm the structural similarity of extracted cholesterol by various extraction methods, showing basically three regions. The olefinic protons appeared at 5.31 ppm. The alcoholic protons gave well-resolved signal at 3.49 ppm. The remaining protons gave a group of signals in the range of 0.64-2.27 ppm. The integral of this area contributed for 44-50 protons. However, the proton counts based on the integral values show different values. This may be attributed to the impurities present in the cholesterol. Since proton NMR chemical shift values were overlapping in the region of 0.64-2.27, proton-decoupled 13C NMR spectroscopy was used for the identification of various carbons in the cholesterol. Proton-decoupled 13C NMR spectra of cholesterol extraction by various methods shows 26 well-resolved signals. A closer examination of the data indicates that the chemical shift values as obtained from the spectra match well, thereby indicating the structural similarity. The estimated values of the effective diffusion coefficient along with the RMSE values are reported in Table 4. The RMSE values are low, indicating the goodness of the fit between the experimental data and the model prediction. Figure 6 compares the model prediction with the experimental data. The closeness of the model simulation line with the experimental data indicates the appropriateness of the model in representing the experimental data. Comparing the effective diffusivity coefficient of the system with cosolvents with pure SC CO2, it can be observed the diffusivity coefficient doubles for the system with acetone as cosolvent, while it is more than three times that for 2-propanol and ethanol as cosolvents. The effective diffusivity coefficient was found to be of the order of 10-13 m2/s, for extraction of cholesterol from cattle brain, either with SC CO2 or SC CO2 with cosolvents. The low-cholesterol brain obtained after SC CO2 extraction can be dried in a vacuum oven to remove residual solvent. The solvent free product may be used for human and animal consumption. 5. Conclusions Detailed investigation was attempted to understand the influence of the different cosolvents, such as acetone, 2-propanol, and ethanol added along with the SC CO2, in a small weight percentage ranging from 2 to 6%, for extraction of cholesterol from cow brain. Extracted cholesterol was analyzed for its structure using DSC, IR, and NMR and its purity using GC. A maximum of 53% of the total cholesterol in the brain sample could only be extracted either using a SC CO2 or using

cosolvents along with SC CO2. However, the conventional extraction method, using dichloroethane, could extract only 48% of the total cholesterol. Although the total amount of cholesterol extracted did not differ with the addition of cosolvents, the rate of extraction was found to increase significantly with the addition of cosolvents in small quantities. The kinetics of extraction using SC CO2 as well as SC CO2 with cosolvents was modeled using conventional differential mass balance equation for packed beds, and the effective diffusivity coefficient was found to be 2.3 × 10-13 m2/s for extraction with pure SC CO2, while it was found to be 4.8 × 10-13 m2/s for SC CO2 with acetone and 8 × 10-13 m2/s for 2-propanol and ethanol. Acknowledgment The first author sincerely, thanks Deutscher Akademischer Austausch Dienst (DAAD) for their financial support to conduct this research work under DAAD-Sandwich model programme. Notations ap ) surface area of particles, m2 Ci ) initial cholesterol concentration in the solid phase Cs ) cholesterol concentration in the solid phase Cf ) concentration of cholesterol in fluid phase Csa,exp ) cholesterol concentration in the solid phase (experimentally obtained) Csa,pred ) cholesterol concentration in the solid phase (predicted) d ) diameter of brain particles, m Dc ) self-diffusion coefficient, m2/s D12 ) diffusion coefficient of cholesterol in supercritical carbon dioxide, m2/s De ) effective diffusion coefficient, m2/s Gsc ) mass flow rate of super critical carbon dioxide, kg/h h ) spatial coordinate along the bed, m K ) correlation value k ) mass-transfer coefficient km ) overall mass-transfer coefficient, m/s M1 ) molecular weight of carbon dioxide M2 ) molecular weight of cholesterol n ) number of stages assumed to solved the differential equation ndp ) number of data points in eq 9 P ) extraction pressure, bar Fc ) critical density Fr ) reduced density Re ) Reynolds number, duF/µ Rp ) radius of the particle, m r ) radial coordinate t ) time T ) extraction temperature, °C Tr ) reduced temperature V ) volume of the extractor, m3 Vc1 ) molar volume at critical point for CO2 Vc2 ) molar volume at critical point for cholesterol

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ReceiVed for reView May 17, 2007 ReVised manuscript receiVed January 25, 2008 Accepted May 30, 2008 IE070703Q