+ Glycerol + Methanol - American Chemical Society

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Novel Approach for Liquid−Liquid Phase Equilibrium of Biodiesel (Canola and Sunflower) + Glycerol + Methanol Maziar Hakim,† Hamed Abedini Najafabadi,† Gholamreza Pazuki,‡ and Manouchehr Vossoughi*,†,§ †

Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran 145888-9694, Iran Department of Chemical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran 15875-4413, Iran § Institute for Nanoscience and Nanotechnology, Sharif University of Technology, Tehran 145888-9694, Iran ‡

ABSTRACT: In this study, a novel experimental approach was used to overcome the lack of phase equilibrium information to obtain data that is more applicable to industrial situations. Liquid−liquid equilibrium (LLE) data, tie-lines, and phase boundaries were carried out for two systems of canola oil methyl esters (containing 1 wt % KOH) + glycerol + methanol and sunflower oil methyl esters (containing 1 wt % KOH) + glycerol + methanol at three different temperatures (303.15, 313.15, and 323.15 K). The quality of data was also ascertained using Othmer−Tobias correlations. The experimental LLE data was also correlated by the nonrandom two-liquid (NRTL) and the Wilson−NRF Gibbs free energy models. The energy interaction parameters of both models were obtained for both systems. The results indicated that the Wilson−NRF provided an accurate correlation of LLE behavior with average absolute deviation (AAD%) inferior to 8.78% and 10.80% for canola and sunflower biodiesel systems, respectively. However, the NRTL model presented a more accurate correlation of LLE behavior of both studied systems with AAD% inferior to 6.26% and 7.43% for canola and sunflower biodiesel systems, respectively. equilibrium (LLE). Negi et al.12 determined experimental data for the glycerol + methanol + methyl oleate and glycerol + monoolein + methyl oleate ternary systems and evaluated the ability of two models, the UNIFAC and UNIFAC− Dortmund models, to predict the experimental data. Rostami et al.13,14 studied phase behavior of four ternary mixtures (glycerol + methanol + palm, soya, sunflower, and canola oil biodiesel) at three different temperatures (293.15, 303.15, and 313.15 K) and predicted the experimental data, using the UNIQUAC model. Felice et al.15 correlated the Wilson activity coefficient based on thermodynamic data available in the literature including mixtures of two (biodiesel and glycerol), three (biodiesel, glycerol, and methanol), and four (biodiesel, glycerol, methanol, and water) components, without the addition of any empirical fitting parameter. Oliveira et al.16,17 measured LLE data for the ternary system of canola oil biodiesel + ethanol + glycerol, evaluated the performance of commonly used excess Gibbs energy (gE) models, and showed the capability of cubic-plus-association (CPA) EoS to predict the phase equilibrium used for the design and optimization of biodiesel production plants. Mesquita et al.18 reported experimental LLE data for two systems of soybean and sunflower oil biodiesel + ethanol + glycerol at two different temperatures (293.15 and 323.15 K) and correlated the experimental data using the nonrandom two-liquid (NRTL) model. Machado et al.19 investigated the influence of temperature and catalyst on a ternary LLE system of castor oil biodiesel, ethanol, and glycerol, as well as a quaternary LLE system that consisted of castor oil biodiesel,

1. INTRODUCTION Crude oil is the biggest source of energy in today’s world whose galloping declining rate is everyone’s concern. The consumption of fossil fuels not only has increased greenhouse gases but has decreased its resources as well.1 Consequently, in recent years, the attention of many researchers has been drawn to biodiesel as a replacing source of energy. Biodiesel has quite a few advantages over petroleum-based fuels, of which the most important ones are lower production of greenhouse gases,2 a more favorable combustion profile,3 easier storage as well as transportation,4 biodegradability, and nontoxicity.5 There are several different ways to produce biodiesel, among which the transesterification reaction is the industrially used approach and the most preferable one. Through this process, vegetable oil or animal fat reacts with alcohol at an evaluated temperature, producing alkyl esters of fatty acids and glycerol. Due to the slow rate of the transesterification reaction, catalysts such as alkaline catalysts are used to increase the rate and yield.6,7 The unsaturated fatty acid esters content of produced biodiesel changes depending on the raw materials. For instance, methyl oleate and methyl linoleate are the main products of soybean oil.8 Experiments have shown that oleaginous seeds, soybean, sunflower, canola, and rapeseed seeds, have high oil content. Accordingly, they have gained much attention recently.9,10 The production of high quality biodiesel depends on the purification process of transesterification products. The separation of these products is facilitated by the formation of two immiscible liquid phases. The heavier phase almost contains glycerol; on the other hand, the lighter phase almost contains biodiesel. The excess alcohol is distributed between the two phases.11 As a consequence, many researchers have studied different ternary systems (fatty acid methyl esters + glycerol + methanol) to understand the liquid−liquid © 2013 American Chemical Society

Received: Revised: Accepted: Published: 855

September 25, 2013 November 22, 2013 November 26, 2013 November 26, 2013 dx.doi.org/10.1021/ie4031902 | Ind. Eng. Chem. Res. 2014, 53, 855−864

Industrial & Engineering Chemistry Research

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Table 1. Canola and Sunflower Oil Fatty Acid Methyl Esters Composition canola biodiesel

sunflower biodiesel

trivial name

fatty acids

composition (% mass)

trivial name

fatty acids

composition (% mass)

myristic acid palmitic acid palmitoleic acid stearic acid oleic acid linoleic acid linolenic acid arachidic acid

C14 C16 C16:1 C18 C18:1 C18:2 C18:3 C20 Others

0.00 4.27 0.00 1.92 68.43 24.08 0.90 0.00 0.40

myristic acid palmitic acid palmitoleic acid stearic acid oleic acid linoleic acid linolenic acid arachidic acid

C14 C16 C16:1 C18 C18:1 C18:2 C18:3 C20 Others

0.00 12.72 0.40 2.77 29.69 53.05 1.14 0.00 0.23

Figure 1. Phase diagram and liquid−liquid results for system containing canola oil biodiesel (containing 1 wt % KOH) + methanol + glycerol at 303.15 K. Experimental (• and ), NRTL (▲ and •••), and Wilson−NRF (■ and ---) results.

under this circumstance. Furthermore, a modified version of the Wilson model proposed by Pazuki et al.,20 so-called the Wilson−NRF, and the NRTL models were used to correlate these systems.

ethanol, glycerol, and NaOH. Nevertheless, in all these works, pure components were mixed to evaluate the phase equilibrium, making the situations different from real industrial conditions. In the present study, liquid−liquid phase equilibrium of two pseudoquaternary systems of canola biodiesel (containing 1 wt % KOH) + glycerol + methanol and sunflower biodiesel (containing 1 wt % KOH) + glycerol + methanol are studied experimentally at 303.15, 313.15, and 323.15 K. Data are obtained by experiments directly done on the two phase, resulting from the transesterification reaction, to simulate conditions closer to industrial production of biodiesel. Accordingly, in this study, the effect of the presence of KOH in both phases is not neglected, and the experimental LLE data are obtained

2. EXPERIMENTAL SECTION Materials. The chemicals used in this work included glycerol (mass purity > 99% GC, Merck), methanol (mass purity > 99.5%, Merck), distilled water, canola refined oil (Mohsen Oil Company), sunflower refined oil (Mohsen Oil Company), and H3PO4 (99%, Merck). Biodiesel samples used in the present study were produced in the laboratory via the transesterification reaction of both oils, and KOH (99%, Merck) was used as the catalyst. To produce the samples, the 856

dx.doi.org/10.1021/ie4031902 | Ind. Eng. Chem. Res. 2014, 53, 855−864


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international standard method of ISO 5501978 (E) for biodiesel preparation was used.21 After production, The methyl ester content of produced biodiesels was analyzed by gas chromatography (GC) using a Varian gas chromatograph system equipped with a flam ionization detector (Tdetector = 523.15 K), automated split injector (Tinjector = 513.15 K), and the split ratio considered as 100:1. The temperature program applied to the column was the following: an initial temperature of 323.15 K was held for 1 min and then raised to 453 K at 15 K/min, 503.15 K at 7 K/min, and finally to 613.15 K at 30 K/min with a total analytical run time equal to 20 min. The profiles of studied biodiesels are reported in Table 1. A 50 mg sample of biodiesel was mixed with 1 mL of a standard solution of methyl heptadecanoate and n-hexane (5 mg/1 mL). The yield of biodiesel was determined by analyzing 1 μL of the mixture by a GC test. Methods. 1. Saturation Curve of the Pseudoquaternary System of Biodiesel (Containing 1 wt % KOH) + Methanol + Glycerol. The determination of phase boundaries for each pseudoquaternary system was carried out at three different temperatures of 303.2, 313.2, and 323.2 K by a titration method under isothermal conditions. In this method, so-called “turbidimetric analysis”, for the biodiesel-rich phase, a mixture of a certain amount of biodiesel containing 1 wt % KOH and methanol was added to a flask that was immersed in a constanttemperature water bath with a temperature uncertainty of ±0.2 K. The mixture was titrated by glycerol, while stirring with

a magnetic stirrer, until the mixture changed from transparent to turbid. This is, in fact, a transition point from a one-phase region into a two-phase region, which is considered the saturation point of glycerol in a biodiesel + methanol mixture. Similarly, in the case of the glycerol-rich phase, a mixture of glycerol and methanol was titrated with biodiesel, containing 1 wt % KOH, until the mixture turned cloudy. The corresponding solubility curve was calculated on the basis of the amount of each component added. Uncertainties in the mass fraction of each component were calculated to be less than 10−3. 2. Tie-Line Determination of the Transesterification Reaction Products. For tie-line determination, a new procedure was devised and applied to create conditions more similar to industrial ones. First, methyl ester biodiesel was prepared by transesterification of canola and sunflower oil with methanol in the presence of KOH as a catalyst. Through this step, oil and methanol reacted with a mole ratio of 1:6 at 333.15 K for 60 min. A sample of the produced biodiesel was washed three times with deionized water containing 1 wt % H3PO4. The biodiesel phase was collected and mixed with Na2SO4 to remove the remaining water. The mixture was centrifuged, and the liquid phase was collected. The treated biodiesel sample was analyzed by gas chromatography (GC), and the results proved the nearly complete conversion of oil to methyl esters (>99%) by the use of this molar ratio. The obtained mixture of transesterification products was kept in an isothermal incubator at constant temperature for 24 h to 857



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provide an adequate time for complete separation into two phases. Samples were carefully taken from the biodiesel-rich phase and the glycerol-rich phase using syringes. The samples were weighed and then kept in an oven at 348.15 K for 3 h to evaporate the whole methanol. According to the phase rule, at a fixed temperature and pressure, only one component can independently change. Thus, the points, which represent the composition of each phase, were determined by measuring the amount of removed methanol with uncertainties less than 10−3 g and using the binodal curves obtained in the previous section. Later, since the higher content of methanol was proved by GC analysis to result in the complete conversion of oil, the procedure was repeated for a higher amount of methanol to obtain other tie-lines. Thermodynamic Section. In this study, to model the experimental data of both canola and sunflower biodiesel systems, two Gibbs free energy-based models are selected. First, the NRTL model22 was used due to its high accuracy and applicability to strongly nonideal mixtures. The NRTL activity coefficient is as follows: ln γi =

3 ∑ j = 1 τjiGjixj 3 ∑l = 1 Glixl

3

+

∑ j=1

3 ∑ xτG ⎞ xjGij ⎛ ⎜τ − r = 1 r rj rj ⎟ ij 3 3 ∑l = 1 Gljxl ⎜⎝ ∑l = 1 Gljxl ⎟⎠

τij =

(3)

RT

In above equations, Δgij is a Gibbs energy parameter characteristic of the i−j interaction, and αji is related to the nonrandomness in the mixture, which is arbitrarily set to 0.3. Second, the Wilson−NRF model20 was used due to its simplicity and high accuracy in correlating LLE systems. It is pointed out that the Wilson model cannot be used for liquid− liquid calculations, whereas the Wilson−NRF model has solved this problem. The Wilson−NRF model has been previously used for the correlation and prediction of amino acids and simple peptides in aqueous solutions,20 polymer solutions,23 aqueous electrolyte solutions,24 and physical properties of several biodiesels.25 The Wilson−NRF activity coefficient is defined as follows: 3 ⎡ ln γi = −C ⎢ln(∑ xjHji) − 1 + ⎢⎣ j = 1

(1)

−

where γi and xi are the activity coefficient and molar fraction of component i. Gij and τij are calculated by eqs 2 and 3: Gij = exp( −αjiτij)

Δgij

3

xjHij 3 j = 1 ∑k = 1 xkHki

∑

3

3

⎤

j=1

j=1

⎦

∑ xj(∑ xk ln Hkj − ln HijHji)⎥⎥

(4)

where C is the coordinate number, which is set to be 10, and Hij is calculated by following equation:

(2) 858



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Figure 4. Phase diagram and liquid−liquid results for system containing sunflower oil biodiesel (containing 1 wt % KOH) + methanol + glycerol at 303.15 K. Experimental (• and ), NRTL (▲ and •••), and Wilson−NRF (■ and ---) results.

⎛ Δhij ⎞ Hij = exp⎜ − ⎟ ⎝ CRT ⎠

where xI1, xI2, and xI3 are mole fractions of biodiesel, methanol, and glycerol in biodiesel-rich phase (I), respectively, and xII1 , xII2 , and xII3 are mole fractions of biodiesel, methanol, and glycerol in glycerol-rich phase (II), respectively. γIi and γIIi are the activity coefficients of component i in the biodiesel-rich and glycerol-rich phases. Z1 is the biodiesel mass fraction in the feed, and B is the biodiesel-rich phase mass ratio to total mass. Second, a genetic algorithm (GA) was applied to minimize the objective function and converge at the optimized energy interaction parameters of both models. In our study, the parameter Δgi,j/R, which represents the energy parameter characteristic of the interaction between components i and j, was considered as the adjustable parameter for the NRTL model due to its independency on temperature. Similarly, the parameter Δhi,j/R, which represents the enthalpy characteristic between components i and j, was considered as the adjustable parameter for the Wilson−NRF model.

(5)

where Δhij is the enthalpy energy parameter characteristic of the i−j interaction. The objective function described below was minimized to obtain the energy interaction parameters of both models N

OF =

3

2 II,calc − XiI,exp − XiII,exp )2 ] ∑ ∑ [(XiI,calc ,j , j ) + (X i , j ,j i=1 j=1

(6)

where Xi,j is the mass fraction of component j in each phase, N is the number of experimental tie-lines, superscripts “I” and “II” stand for biodiesel-rich phase and glycerol-rich phase, and superscripts “calc” and “exp” stand for calculated and experimental results. The optimization procedure for each model consisted of two different iterating steps. First, the Newton−Raphson method was applied to obtain the values of XI,calc and XII,calc by the i,j i,j simultaneous solution of eqs 7−11: x1Iγ1I(x1I , x 2I , x3I) = x1IIγ1II(x1II , x 2II , x3II)

(7)

x 2Iγ2I(x1I , x 2I , x3I) = x 2IIγ2II(x1II , x 2II , x3II)

(8)

x3Iγ3I(x1I , x 2I , x3I) = x3IIγ3II(x1II , x 2II , x3II)

(9)

Z1 = X1IB + (1 − B)X1II

(10)

Z 2 = X 2IB + (1 − B)X 2II

(11)

3. RESULT AND DISCUSSION LLE data at T = (303.2, 313.2, and 323.2) K for system of canola oil biodiesel (containing 1 wt % KOH) + methanol + glycerol are shown in Figures 1−3, and for the sunflower oil biodiesel (containing 1 wt % KOH) + methanol + glycerol data are presented in Figures 4−6. These diagrams include biodiesel curves and experimental tie-lines as well as calculated tie-lines by the Wilson−NRF and the NRTL models. Experimental LLE results for canola oil biodiesel and sunflower oil biodiesel are respectively presented in Tables 2 and 3. In Figures 1−6 as well 859



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As it is shown, two main methyl esters of sunflower and canola oil biodiesels were oleic and linoleic acid. Additionally, Linoleic acid contains two unsaturated bonds, whereas oleic acid contains one that makes linoleic acid more polar than oleic acid. Consequently, due to the linoleic acid having a higher content of sunflower oil biodiesel, methanol solubility in the biodiesel-rich phase in the sunflower oil biodiesel system is slightly higher than that for the canola oil biodiesel system at a fixed temperature. The quality of LLE data was proved by two factors. First, the agreement of tie-lines with feed composition indicated slight mass loss and low experimental error. Second, LLE data was tested by the Othmer−Tobias26 equation, which is described as eq 13:

as Tables 2 and 3, quaternary LLE data are represented as pseudoternary systems by calculating the weight fraction of each component without considering 1 wt % KOH. The experimental results showed good agreement with previously published data on similar systems of methyl oleate + glycerol + methanol,12 as well as canola and sunflower oil biodiesel + glycerol + methanol.14 As it is observed, biodiesel and glycerol are both completely soluble in methanol; on the other hand, biodiesel and glycerol are partially miscible in one another. As the slope of tie-lines can present, the solubility of methanol in glycerol is higher than methanol solubility in biodiesel, which is due to the higher similarity between methanol and glycerol than that of methanol and biodiesel. The methanol distribution was also studied by a calculation of the solute distribution coefficient (K) given by eq 12. K=

⎛ 1 − X II ⎞ ⎛ 1 − XI ⎞ 3 1 ⎜ ⎟ + bOT ⎟ a log⎜ log = OT II I ⎝ X1 ⎠ ⎝ X3 ⎠

X 2I X 2II

(13)

where aOT and bOT are angular and linear coefficients, respectively, XI1 is the mass fraction of biodiesel in biodiesel-rich phase, and XII3 is the mass fraction of glycerol is glycerol-rich phase. An example of the Othmer−Tobias plot of sunflower oil biodiesel at 303.15 K is presented in Figure 7. The experimental LLE data of both biodiesels show a good linear fit with the Othmer−Tobias equation, which indicates the consistency of experimental tie-lines and binodal. Moreover, the quality of data is also shown by R2 > 0.92 achieved for both biodiesels at all temperatures, as presented in Table 5.

(12)

The resulted solute distributions for each biodiesel at all studied temperatures are presented in Table 4. As it can be observed, increasing the temperature leads to a small decrease in the K value. This behavior can be explained by an increase of methanol solubility in the glycerol-rich phase due to the temperature increase. K values data also show that the methanol partitioning is different for canola and sunflower oil biodiesel systems. K values for the sunflower oil biodiesel system is slightly higher than those for the canola oil biodiesel system. 860



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Table 2. LLE Experimental Data for Canola Oil Biodiesel (1) + Methanol (2) + Glycerol (3) Obtained by New Experimental Method LLE data feed

biodiesel-rich phase

glycerol-rich phase

temperature (K)

Z1

Z2

Z3

X1

X2

X3

X1

X2

X3

303.15

0.8459 0.7843 0.7229 0.6554 0.8039 0.7552 0.6909 0.6015 0.7979 0.7528 0.6841 0.6284

0.0662 0.1342 0.2020 0.2765 0.1126 0.1663 0.2373 0.3360 0.1192 0.1690 0.2448 0.3063

0.0879 0.0815 0.0751 0.0681 0.0835 0.0785 0.0718 0.0625 0.0829 0.0782 0.0711 0.0653

0.9624 0.9272 0.9022 0.8797 0.9417 0.9272 0.8940 0.8495 0.9394 0.9222 0.9006 0.8860

0.0376 0.0728 0.0978 0.1203 0.0583 0.0728 0.1060 0.1505 0.0606 0.0778 0.0994 0.1140

0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

0.0100 0.0000 0.0027 0.0150 0.0000 0.0000 0.0000 0.0315 0.0000 0.0000 0.0010 0.0265

0.2890 0.4587 0.6055 0.7319 0.4158 0.5692 0.6718 0.7667 0.4713 0.5771 0.6799 0.7595

0.7010 0.5413 0.3918 0.2531 0.5842 0.4308 0.3282 0.2018 0.5287 0.4229 0.3191 0.2140

313.15

323.15

The NRTL and the Wilson−NRF models were used to correlate LLE data of both canola oil biodiesel and sunflower oil biodiesel systems. As previously described, due to the negligible amount of catalyst, both systems were considered as pseudoternary systems consisting of biodiesel + methanol + glycerol. Figures 1−6 also include the results of both models for each studied system. The NRTL model correlations are shown by blue dashed lines, and the Wilson−NRF modeling results are shown by red dotted lines. The obtained energy interaction parameters of the NRTL model and the Wilson−NRF model are presented in Table 6.

The average absolute deviation (AAD%) of tie-lines was calculated in accordance with eq 14 for both studied systems. 1 AAD = 6N

⎛ X I,exp − X I,calc ∑ ∑ ⎜⎜ ij I,exp ij Xij i=1 j=1 ⎝ N

3

XijI I,exp − XijII,calc ⎞ ⎟ + ⎟ XijII,exp ⎠ 861

(14)



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Table 3. LLE experimental data for sunflower oil biodiesel (1) + methanol (2) + glycerol (3) obtained by new experimental method LLE data feed

biodiesel-rich phase

glycerol-rich phase

temperature (K)

Z1

Z2

Z3

X1

X2

X3

X1

X2

X3

303.15

0.8155 0.7778 0.7529 0.6035 0.8230 0.7750 0.6963 0.5981 0.7811 0.7083 0.6735 0.5820

0.0998 0.1414 0.1689 0.3338 0.0915 0.1445 0.2313 0.3397 0.1377 0.2181 0.2565 0.3575

0.0847 0.0808 0.0782 0.0627 0.0855 0.0805 0.0724 0.0622 0.0812 0.0736 0.0700 0.0605

0.9404 0.9265 0.9115 0.8447 0.9385 0.9243 0.9057 0.8519 0.9302 0.9049 0.8884 0.8493

0.0596 0.0735 0.0885 0.1553 0.0615 0.0757 0.0943 0.1481 0.0698 0.0951 0.1116 0.1507

0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

0.0000 0.0000 0.0000 0.0184 0.0000 0.0000 0.0000 0.0303 0.0000 0.0000 0.0128 0.0484

0.3760 0.4838 0.5400 0.7432 0.3200 0.4953 0.6838 0.7649 0.4952 0.6654 0.7039 0.7616

0.6240 0.5162 0.4600 0.2384 0.6800 0.5047 0.3162 0.2048 0.5048 0.3346 0.2833 0.1900

313.15

323.15

Table 4. Solute Distribution Coefficient of Canola and Sunflower Oil Biodiesel distribution coefficient K temperature (K)

canola oil biodiesel

sunflower oil biodiesel

303.15

0.1301 0.1587 0.1615 0.1694 0.1402 0.1279 0.1578 0.1913 0.1286 0.1348 0.1462 0.1501

0.1585 0.1519 0.1639 0.2090 0.1922 0.1528 0.1379 0.1936 0.1409 0.1429 0.1585 0.1979

313.15

323.15

The calculated AAD% for each model is presented in Table 7. The Wilson−NRF model with AAD% inferior to 8.78% and 10.80% correlated canola and sunflower biodiesel LLE systems well. Nevertheless, the NRTL model presented a more accurate correlation of LLE behavior of both studied systems with AAD% inferior to 6.26% and 7.43% for canola and sunflower biodiesel systems, respectively.

Figure 7. Othmer−Tobias plot of sunflower oil biodiesel at 303.15 K.

4. CONCLUSION Novel experimental measurements were carried out for the LLE behavior of two systems consisting of canola oil methyl ester

Table 5. Othmer−Tobias Correlated Constants for Canola Oil Biodiesel and Sunflower Oil Biodiesel Systems canola oil biodiesel

sunflower oil biodiesel 2

temperature (K)

aOT

bOT

R

303.15 313.15 323.15

0.6398 0.6340 0.4933

−1.1206 −1.1375 −1.1487

0.9438 0.9775 0.9688

aOT

bOT

R2

0.0648 0.4376 0.5849

−1.0646 −1.0675 −1.1323

0.9963 0.9268 0.9894

Table 6. Obtained Energy Interaction Parameters of NRTL and Wilson−NRF Models Wilson−NRF model

NRTL model

parameters



parameters



Δh12/R Δh13/R Δh21/R Δh23/R Δh31/R Δh32/R

1944.293 3390.798 1737.542 4891.088 1391.600 −480.242

3802.296 4851.177 1823.828 5887.057 3938.215 −70.218

Δg12/R Δg13/R Δg21/R Δg23/R Δg31/R Δg32/R

−795.708 1884.381 2277.450 1219.732 2596.237 −879.097

−798.833 2483.285 2345.375 1569.897 2456.78 −901.118

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Subscripts

Table 7. Average Absolute Deviation of Calculated Data by NRTL and Wilson−NRF Models

i = tie-line j = component OT = Othmer−Tobias

calculated AAD% canola biodiesel phase

temperature (K)

biodiesel-rich

glycerol-rich

303.15 313.15 323.15 303.15 313.15 323.15

average

sunflower biodiesel

NRTL

Wilson− NRF

NRTL

Wilson− NRF

4.626 6.601 9.105 6.837 4.240 6.110 6.253

6.372 14.105 14.313 4.326 6.952 6.558 8.771

3.676 11.966 6.925 7.172 9.110 6.670 7.425

3.957 15.687 15.316 7.275 11.609 10.955 10.800

Superscripts

■

REFERENCES

(1) Subramaniam, R.; Dufreche, S.; Zappi, M.; Bajpai, R. Microbial lipids from renewable resources: production and characterization. J. Ind. Microbiol. Biotechnol. 2010, 37, 1271−1287. (2) Monyem, A. H.; van Gerpen, J. The effect of biodiesel oxidation on engine performance and emissions. Biomass Bioenergy 2001, 20, 317−325. (3) Demirbas, A. Political, economic and environmental impacts of biofuels: A review. Appl. Energy 2009, 86, 108−117. (4) Kralova, I.; Sjöblom, J. Biofuels−Renewable Energy Sources: A Review. J. Dispersion Sci. Technol. 2010, 31, 409−425. (5) Gerpen, J. V. Biodiesel processing and production. Fuel Process. Technol. 2005, 86, 1097−1107. (6) Ma, F.; Hanna, M. A. Biodiesel production: a review. Bioresour. Technol. 1999, 70, 1−15. (7) Meher, L. C.; Vidya Sagar, D.; Naik, S. N. Technical aspects of biodiesel production by transesterificationa review. Renewable Sustainable Energy Rev. 2006, 10, 248−268. (8) Abo El-Enin, S. A.; Attia, N. K.; El-Ibiari, N. N.; El-Diwani, G. I.; El-Khatib, K. M. In-situ transesterification of rapeseed and cost indicators for biodiesel production. Renewable Sustainable Energy Rev. 2013, 18, 471−477. (9) Basiron, Y. Palm oil production through sustainable plantations. Eur. J. Lipid Sci. Technol. 2007, 109, 289−295. (10) Barnwal, B. K.; Sharma, M. P. Prospects of biodiesel production from vegetable oils in India. Renewable Sustainable Energy Rev. 2005, 9, 363−378. (11) van Gerpen, J.; Shanks, B.; Pruszko, R.; Clements, D.; Knothe, G. Biodiesel production technology; Report NREL/SR-510-36244; National Renewable Energy Laboratory: Golden, CO, 2004. (12) Negi, D. S.; Sobotka, F.; Kimmel, T.; Wozny, G.; Schomäcker, R. Liquid−Liquid Phase Equilibrium in Glycerol−Methanol−Methyl Oleate and Glycerol−Monoolein−Methyl Oleate Ternary Systems. Ind. Eng. Chem. Res. 2006, 45, 3693−3696. (13) Rostami, M.; Raeissi, S.; Mahmoudi, M.; Nowroozi, M. Liquid− Liquid Phase Equilibria of Systems of Palm and Soya Biodiesels: Experimental and Modeling. Ind. Eng. Chem. Res. 2012, 51, 8302− 8307. (14) Rostami, M.; Raeissi, S.; Mahmoodi, M.; Nowroozi, M. Liquid− Liquid Equilibria in Biodiesel Production. J. Am. Oil Chem. Soc. 2013, 90, 147−154. (15) Di Felice, R.; De Faveri, D.; De Andreis, P.; Ottonello, P. Component Distribution between Light and Heavy Phases in Biodiesel Processes. Ind. Eng. Chem. Res. 2008, 47, 7862−7867. (16) Oliveira, M. B.; Barbedo, S.; Soletti, J. I.; Carvalho, S. H. V.; Queimada, A. J.; Coutinho, J. A. P. Liquid−liquid equilibria for the canola oil biodiesel + ethanol + glycerol system. Fuel 2011, 90, 2738− 2745. (17) Oliveira, M. B.; Ribeiro, V. t.; Queimada, A. n. J.; Coutinho, J. o. A. P. Modeling Phase Equilibria Relevant to Biodiesel Production: A Comparison of gE Models, Cubic EoS, EoS−gE and Association EoS. Ind. Eng. Chem. Res. 2011, 50, 2348−2358. (18) Mesquita, F. M. R.; Feitosa, F. X.; Sombra, N. E.; de SantiagoAguiar, R. S.; de Sant’Ana, H. B. Liquid−Liquid Equilibrium for Ternary Mixtures of Biodiesel (Soybean or Sunflower) + Glycerol + Ethanol at Different Temperatures. J. Chem. Eng. Data 2011, 56, 4061−4067.

biodiesel (containing 1 wt % KOH) + methanol + glycerol + KOH and sunflower oil methyl ester biodiesel (containing 1 wt % KOH) + methanol + glycerol + KOH at 303.2, 313.2, and 323.2 K. Moreover, experimental tie-lines were determined through a new experimental approach. The agreement of tie-lines with feed composition and linearity of Othmer−Tobias plots proved the reliability of experimental tie-lines obtained in this study. The experimental data was correlated using the NRTL and the Wilson−NRF models. The energy interaction parameters of both models were obtained for each studied system. Despite the fact that the corrolated results of both models proved suitable for modeling such systems with AAD% inferior to 10.80%, the NRTL model provided a more precise correlation with AAD% inferior to 7.43%.

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calc = calculated exp = experimental I = biodiesel-rich phase II = glycerol-rich phase

AUTHOR INFORMATION

Corresponding Author

*M. Vossoughi. Tel: +98-021-66164104. E-mail: vosoughi@ sharif.edu. Notes

The authors declare no competing financial interest.

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NOMENCLATURE a = angular coefficient in Othmer−Tobias equation AAD = average absolute deviation B = biodiesel-rich phase mass ratio to total mass b = linear coefficient in Othmer−Tobias equation C = coordinate number Gij = parameter of the NRTL model Hij = parameter of the Wilson−NRF model K = solute distribution coefficient N = number of experimental tie-lines OF = objective function R = universal gas constant T = temperature (K) X = mass fraction x = mole fraction Z = mass fraction in feed

Greek Letters

γ = activity coefficient Δgij = interaction energy between i−j pair in the NRTL model Δhij = interaction energy between i−j pair in the Wilson− NRF model τij = parameter of the NRTL model αij = nonrandomness parameter in the NRTL model 863



Article

(19) Machado, A. B.; Ardila, Y. C.; de Oliveira, L. H.; Aznar, M. n.; Wolf Maciel, M. R. Liquid−Liquid Equilibrium Study in Ternary Castor Oil Biodiesel + Ethanol + Glycerol and Quaternary Castor Oil Biodiesel + Ethanol + Glycerol + NaOH Systems at (298.2 and 333.2) K. J. Chem. Eng. Data 2011, 56, 2196−2201. (20) Pazuki, G. R.; Taghikhani, V.; Vossoughi, M. Correlation and prediction the activity coefficients and solubility of amino acids and simple peptide in aqueous solution using the modified local composition model. Fluid Phase Equilib. 2007, 255, 160−166. (21) Rostami, M.; Raeissi, S.; Ranjbaran, M.; Mahmoodi, M.; Nowroozi, M. Experimental investigation and modeling of liquid− liquid equilibria in two systems of concern in biodiesel production. Fluid Phase Equilib. 2013, 353, 31−37. (22) Smith, J. M.; van Ness, H.; Abbott, M. Introduction to Chemical Engineering Thermodynamics. McGraw-Hill Education: New York, 2004. (23) Pazuki, G. R.; Taghikhani, V.; Vossoughi, M. Study of VLE phase behavior and correlating the thermophysical properties of polymer solutions using a local composition-based model. J. Appl. Polym. Sci. 2009, 112, 1356−1364. (24) Khaderlo, K.; Pazuki, G. R.; Taghikhani, V.; Vossoughi, M.; Ghotbi, C. A new Gibbs energy model in obtaining thermophysical properties of aqueous electrolyte solutions. J. Solution Chem. 2009, 38, 171−186. (25) Abedini Najafabadi, H.; Pazuki, G.; Vossoughi, M. Estimation of Biodiesel Physical Properties Using Local Composition Based Models. Ind. Eng. Chem. Res. 2012, 51, 13518−13526. (26) Othmer, D.; Tobias, P. Liquid-Liquid Extraction Data - The Line Correlation. Ind. Eng. Chem. 1942, 34, 693−696.

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+ Glycerol + Methanol - American Chemical Society

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