Similar to Liquid liquid equilibrium for the ternary system of isopropyl acetate 2 propanol glycerol at different temperatures under atmospheric pressure
Similar to Liquid liquid equilibrium for the ternary system of isopropyl acetate 2 propanol glycerol at different temperatures under atmospheric pressure (20)
2. Additionally, the capacity of glycerol as an extractive solvent was
analyzed by the solute distribution coefficient and the selectivity.
2. Experimental
2.1. Materials
In this work, isopropyl acetate, 2-propanol and glycerol were
used. The source, CASRN, mass fraction purity and analysis method
of all chemicals are listed in Table 1. Purities of the materials were
determined by a gas chromatography (GC) equipped with a flame
ionization detector. In addition, the water contents were measured
by Karl Fischer titration and no appreciable water was detected. All
the materials were used without further purification.
2.2. Apparatus and procedure
The LLE experiment was carried out in a 30 mL glass cell with a
magnetic stirrer in it. The experimental method was described in
literature [13e15]. In this study it was specified as follows: The
temperature of the system was controlled by a refrigerated heating
circulator (Julabo FP45-HF, German, temperature stability ±0.01 K)
and measured by a platinum resistance thermometer Pt-100
(calibrated with an accuracy of 0.01 K). In each measurement of
the LLE data, 10 ml mixture of isopropyl acetate and 2-propanol
plus 10 ml glycerol were added into the glass cell and then stir-
red vigorously by the magnetic stirrer. Through a series of
comparative tests, the stirring time was chosen to be 2 h to get a
sufficient mixing for the extraction equilibrium. The mixture was
settled for 5 h to ensure a complete separation of the two phases.
Then the samples of the upper and lower phase (isopropyl acetate-
rich and glycerol-rich phase) were carefully collected by syringes at
least three times for the composition analysis.
2.3. Sample analysis
The collected samples were analyzed by gas chromatography
(Agilent Technologies 6890N). The gas chromatography was
equipped with a flame ionization detector and a HP-5 capillary
column (30 m  0.32 mm  0.25 mm). The carrier gas was nitrogen
with the purity of 0.99999 provided by Liufang industrial gases co.,
LTD, Tianjin. The operation condition was as follows: The injector
temperature and detector temperature were 573 K and 583 K,
respectively. The column temperature was programmed at 310 K
for 3 min firstly, then increased to 563 K at a rate of 45 K minÀ1
and
held for 1 min. The calibration factor was obtained to correct the
measured values. The accuracy of the analytical method was tested
by known samples of mixtures and the maximum relative error of
the mass fraction did not exceed 0.003.
3. Results and discussion
3.1. Experimental data
The LLE data for isopropyl acetate (1) þ 2-propanol
(2) þ glycerol (3) system at various temperatures T ¼ (298.15,
308.15, and 318.15) K under atmospheric pressure are listed in
Table 2. Triangular phase diagrams with tie-lines are shown in
Fig.1. The experimental data show that the ternary system is a type-
I system. The large two-phase region in Fig. 1 enables a large
operation range for the extraction process. The mutual solubility of
isopropyl acetate and glycerol increases with the addition of 2-
propanol. The increasing temperature from 298.15 K to 318.15 K
does not show obvious effect on the equilibrium of the ternary
system. But it is worthy of mention that increasing temperature will
decrease the viscosity of glycerol significantly. According to the
research of Secur et al. [16], the viscosity of glycerol decreases from
1005 mPa s to 550 mPa s as the temperature increasing from
293.15 K to 323.15 K, which provides convenience for operation.
The consistency of the LLE data was verified by the method
proposed by Marcilla et al. [17]. According to the mass balance
between the initial mixture and the two conjugated phases (extract
phase and raffinate phase), three independent mass balance
equations can be written as follows:
M
0
ðx1Þ
0
¼ MIðx1ÞI þ MIIðx1ÞII (1)
M
0
ðx2Þ
0
¼ MIðx2ÞI þ MIIðx2ÞII (2)
M
0
ðx3Þ
0
¼ MIðx3ÞI þ MIIðx3ÞII (3)
where M0 is the mole of initial mixture, MI and MII are the mole of
the isopropyl acetate-rich phase and the glycerol-rich phase
respectively. (xi)’ is the mole fraction of component i in the initial
mixture, while (xi)I and (xi)II are the mole fraction of component i in
the isopropyl acetate-rich phase and the glycerol-rich phase
respectively, i ¼ 1, 2, 3.
The values of MI and MII were calculated by solving these
overdetermined linear equations with least-squares method. The
relative error RE of the mass balance was determined by the
following equation:
RE ¼
MI þ MII À M
0
M
0 (4)
The maximal RE is less than 1%. From Fig. 1, one can also
conclude that the experimental data is reliable because the points
of the overall compositions agree the tie line with great accuracy.
3.2. Evaluation of the extractive solvent
The distribution coefficient (b) and the selectivity (S) are used to
evaluate the extraction capacity of glycerol. These parameters are
defined as follows:
b ¼
xІІ
2
xІ
2
(5)
Table 1
Experimental chemicals.
Chemical Source CASRN W(Mass fraction) Analysis method
Isopropyl Acetate Yuanli, China 108-21-4 0.990 GCa
, KFb
2-Propanol Yuanli, China 67-63-0 0.999 GCa
, KFb
Glycerol Yuanli, China 56-81-5 0.995 GCa
, KFb
a
Gas chromatography.
b
Karl Fischer titration.
Y.-X. Li et al. / Fluid Phase Equilibria 412 (2016) 199e204200
3. S ¼
xІІ
2 xІ
1
xІ
2xІІ
1
(6)
where x is the mole fraction. The values of b and S are listed in
Table 2, from which one can note a high selectivity.
The selectivity is directly related to the extraction capability of
the solvent. Fig. 2 presents the variations of the selectivity with the
content of the 2-propanol in the isopropyl acetate-rich phase. The
solid lines in Fig. 2 represent the fitting curves of the experimental
data using the following equation:
S ¼ e þ f exp
Àx1
2
.
g
(7)
The equation has been used to correlate the variation of selec-
tivity with a good degree of accuracy in the published studies
[18e20]. The parameters e, f, g in Eq. (7) and the standard de-
viations d are listed in Table 3.
As demonstrated in Fig. 2, the selectivity decreases with the
increase of the 2-propanol content in the isopropyl acetate-rich
phase, and slightly decreases with temperature. It should be
noted in Fig. 2 that the values of S are much higher than the unity,
especially at low content of 2-propanol.
As a potential solvent, glycerol has many attractive features
including good chemical stability, non-toxicity, non-corrosivity,
and relatively low price, besides its high selectivity. Moreover,
compared to isopropyl acetate, its higher density improves the
separation efficiency of the two phases in the extraction process.
(The densities of glycerol and isopropyl acetate are 1.261 g/cm3
,
0.888 g/m3
, respectively [3].) Its boiling point is higher than that of
isopropyl acetate and 2-propanol, which makes it easy to be
recovered by distillation. (The boiling points of glycerol, isopropyl
acetate and 2-propanol are 563.00 K, 362.15 K and 355.60 K,
respectively [3].) Despite the high viscosity of glycerol is unfavor-
able for the extraction process, its viscosity can be decreased effi-
ciently by increasing the operating temperature. Another drawback
is the low distribution coefficient. A low distribution coefficient
suggests that a large amount of extractive solvent is needed to
obtain a satisfactory extraction effect, which means high costs
considering the size of equipment and the energy to posteriorly
separate solvent and solute.
3.3. Correlation of experimental data
Andreatta et al. summarized thermodynamic models describing
the ternary system alkyl ester þ alcohols þ glycerol [21]. Several
models have been previously tested to correlate these kinds of
mixtures: NRTL model, UNIQUAC model, traditional UNIFAC and its
versions, Wilson activity coefficient model, GCÀPPCÀSAFT model
CPA EoS model and GCAÀEoS model.
Except Andreatta, many other researchers also spent much
effort on the LLE of alkyl ester þ alcohols þ glycerol system. For
instance, Basso et al. [22] published the LLE data of
glycerol þ ethanol þ distilled fatty acid ethyl esters from crambe oil
in the range of 298.2Ke338.2 K. The data were correlated with the
NRTL and the UNIFAC models, and the NRTL model gave a better
result. Mesquita et al. [23] measured the LLE data of
glycerol þ ethanol þ coconut biodiesel system. The NRTL and the
UNIQUAC models were used to correlate the LLE data and satis-
factory results were obtained. De Azevedo Rocha et al. [24] studied
Table 2
The experimental LLE data of isopropyl acetate (1) þ 2-propanol (2) þ glycerol (3), together with the distribution coefficient b and selectivity S.a
Overall composition Isopropyl acetate-rich phase (I) Glycerol-rich phase (II) b S
x1 x2 x3 x1 x2 x3 x1 x2 x3
T ¼ 298.15 K
0.388 0.000 0.612 0.995 0.000 0.005 0.010 0.000 0.990
0.342 0.057 0.601 0.850 0.130 0.020 0.012 0.049 0.939 0.373 26.784
0.298 0.113 0.589 0.782 0.198 0.020 0.013 0.071 0.916 0.359 21.650
0.256 0.165 0.579 0.633 0.324 0.043 0.020 0.121 0.859 0.374 11.785
0.216 0.216 0.568 0.545 0.390 0.065 0.021 0.129 0.850 0.332 8.586
0.196 0.241 0.563 0.508 0.418 0.074 0.024 0.153 0.823 0.365 7.649
0.177 0.265 0.558 0.447 0.447 0.106 0.029 0.173 0.798 0.388 6.044
0.157 0.290 0.553 0.372 0.483 0.145 0.037 0.209 0.754 0.434 4.336
0.138 0.313 0.549 0.319 0.493 0.188 0.047 0.225 0.728 0.457 3.116
0.120 0.337 0.543 0.265 0.500 0.235 0.045 0.246 0.709 0.491 2.854
T ¼ 308.15 K
0.388 0.000 0.612 0.994 0.000 0.006 0.011 0.000 0.989
0.342 0.057 0.601 0.857 0.114 0.029 0.013 0.043 0.944 0.378 24.517
0.298 0.113 0.589 0.785 0.192 0.023 0.014 0.063 0.923 0.328 18.111
0.256 0.166 0.578 0.634 0.316 0.050 0.022 0.115 0.863 0.364 10.784
0.216 0.216 0.568 0.564 0.372 0.064 0.024 0.129 0.847 0.348 8.205
0.196 0.241 0.563 0.491 0.414 0.095 0.025 0.155 0.820 0.373 7.265
0.177 0.265 0.558 0.420 0.457 0.123 0.027 0.165 0.808 0.360 5.680
0.157 0.290 0.553 0.361 0.480 0.159 0.036 0.221 0.743 0.459 4.570
0.132 0.320 0.548 0.305 0.490 0.205 0.039 0.249 0.712 0.507 3.928
0.120 0.336 0.544 0.260 0.499 0.241 0.040 0.275 0.685 0.552 3.581
T ¼ 318.15 K
0.388 0.000 0.612 0.989 0.000 0.011 0.012 0.000 0.988
0.342 0.057 0.601 0.840 0.132 0.028 0.013 0.043 0.944 0.327 21.747
0.298 0.113 0.589 0.795 0.180 0.025 0.016 0.065 0.919 0.360 17.515
0.256 0.165 0.579 0.649 0.296 0.055 0.023 0.097 0.880 0.326 9.301
0.216 0.216 0.568 0.566 0.362 0.072 0.026 0.133 0.841 0.367 7.982
0.196 0.241 0.563 0.495 0.415 0.090 0.032 0.158 0.810 0.380 5.824
0.177 0.265 0.558 0.421 0.450 0.129 0.033 0.181 0.786 0.402 5.061
0.157 0.290 0.553 0.358 0.468 0.174 0.045 0.216 0.739 0.462 3.649
0.120 0.336 0.544 0.292 0.483 0.225 0.051 0.259 0.690 0.537 3.089
0.111 0.349 0.540 0.217 0.490 0.293 0.055 0.301 0.644 0.614 2.412
a
All compositions are expressed as mole fraction, the standard uncertainties u are u(T) ¼ 0.01 K, u(x1) ¼ u(x2) ¼ u(x3) ¼ 0.001.
Y.-X. Li et al. / Fluid Phase Equilibria 412 (2016) 199e204 201
4. the LLE for ternary systems containing ethylic palm oil
biodiesel þ ethanol þ glycerol. The experimental data were
correlated by the NRTL model with a global deviation below 1%.
In the present study, both NRTL [25] and UNIQUAC [26] models
were applied to correlate the experimental data. These models
were successfully used in correlating the LLE data of many kinds of
mixtures, including the strongly non-ideal systems, such as the
associated systems which contain carboxylic acids [27e29]. In
terms of the systems of alkyl ester þ alcohols þ glycerol, several
authors correlated the experimental data with the NRTL or the
UNIQUAC model as mentioned above [22e24]. Moreover, Machado
et al. [30] correlated the LLE data for the ternary systems of
biodiesel þ ethanol þ glycerol with the NRTL model and the
calculation results agreed well with the experimental data. Franca
et al. [31] obtained satisfactory results when the authors correlated
the experimental data of castor oil biodiesel þ glycerol þ alcohol
system with the UNIQUAC model.
For the system of isopropyl acetate (1) þ 2-propanol
(2) þ glycerol (3), the non-randomness parameter aij among all
the components is set to 0.3 in the NRTL model, and the UNIQUAC
structural parameters of the pure components are listed in Table 4.
The binary interaction parameters for the two models were ob-
tained by minimizing the objective function OF [32]:
OF ¼
XN
k¼1
X2
j¼1
X3
i¼1
2
4
T
exp
k
À Tcal
k
sT
!2
þ
xexp
ijk
À xcal
ijk
sx
!2
3
5 (8)
where N is the total number of the tie-lines. The subscripts i and j
denote the component and different phase, respectively. The
subscript k represents the tie-line. The superscripts exp and cal
mean experimental value and value calculated by the models. In
the regression, sT and sx are 0.01 K and 0.001, respectively.
The correlation results were ascertained by the corresponding
root-mean-square deviation (RMSD).
RMSD ¼
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
XN
k¼1
X2
j¼1
X3
i¼1
x
exp
ijk
À xcal
ijk
2
6N
v
u
u
u
t (9)
The values of the NRTL and the UNIQUAC model parameters are
shown in Table 5. The calculated data from these parameters are
plotted together with the experimental data in Fig. 1. Through Fig. 1
one can note that both models are in good agreement with the
experimental results, and the NRTL model makes a better correc-
tion. From the correlated results in Table 5, it can also be inferred
that the phase equilibria of the studied system can be accurately
described by the two models, and the NRTL model has a smaller
RMSD than the UNIQUAC model does.
Some authors correlated the LLE data of the system of alkyl
ester þ alcohols þ glycerol with other thermodynamic models.
Oliveira et al. [34] correlated the experimental data of this system
with the CPA-EoS model. The average deviations between the
experimental data and modeling results exceeded 2%. Andreatta
[21] applied the GCA-EoS and the A-UNIFAC model in this kind of
system. The standard deviations in the prediction of methanol
distribution coefficients were 9.5% and 3.93% for the two models,
respectively. Kuramochi et al. [35] applied different versions of the
Fig. 1. Triangular phase diagram for the system isopropyl acetate(1) þ 2-
propanol(2) þ glycerol(3) with tie-lines of the experimental and calculated data at
different temperatures under atmospheric pressure. (a) 298.15 K (b) 308.15 K (c)
318.15 K. (▫) overall composition; (C) experimental tie line data; dash line, data
calculated by the NRTL model; dot line, data calculated by the UNIQUAC model.
Y.-X. Li et al. / Fluid Phase Equilibria 412 (2016) 199e204202
5. UNIFAC models to correlate the methanol þ biodiesel þ glycerol,
and the average relative deviation was more than 10%. The RMSD
values of the NRTL and the UNIQUAC models in the present study
were 0.97% and 1.57% separately, suggesting that these two models
can describe the studied mixtures very well.
4. Conclusions
LLE data for the ternary system of isopropyl acetate þ 2-
propanol þ glycerol were measured at various temperatures
T ¼ (298.15, 308.15, 318.15) K under atmospheric pressure. The
experimental data showed good consistency by checking the mass
balance. The NRTL and the UNIQUAC models were successfully used
to correlate the experimental data and the RMSD values of both
models were reasonable small. The ternary system of isopropyl
acetate þ 2-propanol þ glycerol is a type-I system with a large two-
phase region, which provides a large operation range for the
extraction process. The increasing temperature from 298.15 K to
318.15 K showed no obvious effect on the equilibrium of the ternary
system. The selectivity (S) was much higher than unity. However,
the low distribution coefficient may pose difficulties for its appli-
cation in large-scale industrial production.
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Table 3
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T (K) e f g d
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318.15 À3.821 40.909 0.277 0.486
Table 4
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Component ri qi
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2-Propanol 2.914 2.528
Glycerol 3.386 3.060
a
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Table 5
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i-j NRTL UNIQUAC
aij Dgij (J/mol) Dgji (J/mol) uij (J/mol) uji(J/mol)
1-2 0.3 51.9 1259.2 2039.7 À369.0
1-3 0.3 9862.2 9248.1 3084.7 1519.9
2-3 0.3 2457.2 2395.7 À1130.7 4282.5
RMSD 0.0097 0.0157
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