Liquid Liquid equilibria

1. (Liquid + liquid) equilibrium of systems involved in the stepwise
ethanolysis of vegetable oils
Larissa C.B.A. Bessa, Marcela C. Ferreira, Simone Shiozawa, Eduardo A.C. Batista, Antonio J.A. Meirelles ⇑
Laboratory of Extraction, Applied Thermodynamics and Equilibrium, Department of Food Engineering, Faculty of Food Engineering, University of Campinas, Campinas, São
Paulo 13083-862, Brazil
a r t i c l e i n f o
Article history:
Received 10 February 2015
Received in revised form 29 April 2015
Accepted 30 April 2015
Available online 21 May 2015
Keywords:
(Liquid + liquid) equilibrium
Monoacylglycerol
Diacylglycerol
Biodiesel
Ethanol
Modelling
a b s t r a c t
Current concerns about adverse impacts to the environment and human health have encouraged the
research and development of renewable fuels, such as biodiesel. The transesterification reaction is a
three-stage reaction, which produces two intermediate products (diacylglycerols and monoacylglyc-
erols). Accurate and proper knowledge of the phase equilibrium behaviour during the transesterification
process is crucial for a better understanding of the reaction pathway, for the optimisation of reactors and
the separation of the products. Thus, in order to thoroughly understand the entire transesterification sys-
tem for biodiesel production, which consists of six different kinds of components, this study reports
experimental results and the thermodynamic modelling of the (liquid + liquid) equilibrium (LLE) of
two systems composed by {vegetable oils (sunflower or high oleic sunflower oils) + monoacylglyc-
erols + diacylglycerols (+ethyl esters + fatty acids) + ethanol} at T = (303.15 and 318.15) K, at atmospheric
pressure. The LLE experimental values were used to estimate NRTL parameters and to evaluate the
UNIFAC model, using its original version with two different set of parameters. Results showed that,
due to differences in the number of polar groups, mono- and diacylglycerols behave in opposite ways
regarding phase distribution. Experimental data were well correlated using NRTL, in which the maximum
deviation value was 0.434%. As for UNIFAC, the model predicted the experimental data with deviations
varying within the range of (1.80 to 9.24)%.
Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction
Due to environmental adversities and the global concern about
the conservation of non-renewable natural resources, combined
with the growing sensitivity to the global warming, a search for
environmentally friendly renewable energy sources, such as bio-
diesel, has gained recent significant attention [1]. Biodiesel, defined
as mono-alkyl esters of fatty acids from vegetable oils or animal
fats, is an environmentally attractive alternative to conventional
petroleum diesel fuel. It presents many important technical advan-
tages over petroleum diesel, including low toxicity, derivation from
renewable feedstock, superior biodegradability, negligible sulfur
content, higher flash point and lower exhaust emissions [2].
The process used most often for the biodiesel production is the
transesterification (alcoholysis), a reaction between triacylglyc-
erols (TAG) found in oils and fats and an alcohol in the presence
of a catalyst (such as a base, an acid or an enzyme). Methanol is
the most often used alcohol in biodiesel synthesis because of its
suitable physical and chemical properties and low cost [3].
However, the advantages of using ethanol in biodiesel production
include higher miscibility with vegetable oils that allows better
contact in the reaction step and lower toxicity [4].
Transesterification produces methyl or ethyl esters, according to
the selected alcohol.
The reaction typically follows three steps, as shown in figure 1,
where each fatty acid is sequentially taken out and converted to a
molecule of fatty acid alkyl ester (biodiesel). The reaction (1) con-
verts triacylglycerol (TAG) plus alcohol into diacylglycerol (DAG)
plus a fatty acid alkyl ester. Subsequently, the reaction (2) gener-
ates monoacylglycerol (MAG) and another fatty acid alkyl ester.
Finally, reaction (3) generates glycerol and a third fatty acid alkyl
ester. Thus, complete conversion of one mole of TAG generates
three moles of biodiesel [5]. This reaction is essentially biphasic
from the beginning to the end under the reaction conditions usu-
ally employed in the industrial process [6].
Unconverted triacylglycerols, diacylglycerols, monoacylglyc-
erols, glycerol, water and other undesirable components could
http://dx.doi.org/10.1016/j.jct.2015.04.036
0021-9614/Ó 2015 Elsevier Ltd. All rights reserved.
⇑ Corresponding author. Tel.: +55 19 3521 4037; fax: +55 19 3521 4027.
E-mail addresses: larissacbabessa@gmail.com (L.C.B.A. Bessa), marcela.cravo@
gmail.com (M.C. Ferreira), sshiozawa@gmail.com (S. Shiozawa), eacbat@fea.
unicamp.br (E.A.C. Batista), tomze@fea.unicamp.br (A.J.A. Meirelles).
J. Chem. Thermodynamics 89 (2015) 148–158
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journal homepage: www.elsevier.com/locate/jct

2. cause significant engine damages and their loss of power.
Therefore, high conversion and purification steps are of utmost
importance for biodiesel production [7]. Some of the drawbacks
of the industrial ethylic biodiesel production are associated with
the lack of knowledge of the phase compositions during the reac-
tion process. Thus, the measurement and modelling of equilibrium
data, including the equilibrium involved in the steps of oil extrac-
tion, de-acidification, transesterification reaction and purification
of the biodiesel, should be carried out in order to properly optimise
operating conditions for economical and efficient ethylic biodiesel
purification and alcohol recuperation processes.
(Liquid + liquid) equilibrium involving alkyl esters, methanol,
ethanol and glycerol systems, which correspond to the end of the
transesterification reaction, have been extensively published in
the literature in recent years [8–14], as well as the equilibrium
involving vegetable oils, fatty acid and ethanol, which represents
the initial stage of the reaction. [15–18]. However, phase equilib-
rium data taking into account the presence of partial acylglycerols
are limited. Voll et al. [19] determined (liquid + liquid) equilibrium
of hydrolysed palm oil, containing tri-, di- and monoacylglycerols
and free fatty acids in its composition, with water and ethanol, in
order to enrich the palm oil diacylglycerol content by (liquid + liq-
uid) extraction. Oh et al. [20] and Casas et al. [6] discussed the (liq-
uid + liquid) equilibrium results for the system triacylglycerol,
fatty acid methyl esters, methanol, glycerol, diacylglycerol and
monoacylglycerol involved in the methanolysis of crude palm oil
and soybean oil, respectively. Even though, phase equilibrium data
involving both partial acylglycerols and ethyl esters, required for
some of the reactive and purification steps of the ethylic biodiesel
production, are still scarce.
In this context, the main objective of this study was to enhance
the experimental data bank by providing information on the (liq-
uid + liquid) equilibrium (LLE) related to systems that could be
involved in biodiesel production and its purification processes,
with special emphasis on phase equilibrium associated with the
transesterification and esterification reactions. Thus, LLE values
were determined using two different vegetable oils (sunflower
and high oleic sunflower oils), two kinds of commercial mixtures
of mono- and diacylglycerols from different sources (soybean and
cottonseed oils) and two different ethyl esters (oleate and linole-
ate), so that each system consists of derivatives of different major
fatty acid (oleic or linoleic). High oleic sunflower oil is derived from
a high-oleic variety of the sunflower plant. It has an exceptional
oxidative stability due to the reduction in linoleic acid content
[21].
The experimental results include the following kinds of
systems: (vegetable oil + diacylglycerols + monoacylglycerols +
ethanol), (vegetable oil + diacylglycerols + monoacylglyc-
erols + ethyl ester + ethanol) and (vegetable oil + diacylglyc-
erols + monoacylglycerols + fatty acid + ethyl ester + ethanol), so
that the LLE was measured for multicomponent systems. In addi-
tion, these experimental values were used to adjust all binary
interaction parameters of the NRTL model and to evaluate two dif-
ferent sets of parameters of the UNIFAC original model.
2. Experimental
2.1. Material
The suppliers and the mass fraction purity of the solvents and
fatty compounds used in this work are listed in table 1; none of
them was subjected to further purification.
CH2
CH O
O
CH2 O
C
C R2
C R3
O
O
O
R1
OHR
TAG Alcohol Ester
CH2
CH O
O
CH2 OH
C
C R2
O
O
R1
O C R3
O
R
DAG
(1)
OHR
Alcohol Ester MAG
O C
O
R1R
CH2
CH O
OH
CH2 OH
C R2
O
(2)
CH2
CH O
O
CH2 OH
C
C R2
O
O
R1
DAG
OHR
CH2
CH OH
OH
CH2 OH
MAG Alcohol Ester Glycerol
CH2
CH O
OH
CH2 OH
C R2
O
O C R2
O
R
(3)
FIGURE 1. Generalized scheme of the transesterification steps for the production of biodiesel from triacylglycerols.
TABLE 1
Reagents and fatty compounds used in this work, its suppliers and mass fraction
purity.
Component Supplier Mass fraction
puritya
Ethanol Merck >0.995
Toluene HPLC grade Sigma Aldrich >0.999
Acetic acid Merck >0.998
Sunflower oil Cargill >0.999e
HOSOb
Cargill >0.999e
Mixture Ac
SGS Agriculture and Industry
Ltd.
>0.52f
Mixture Bd
SGS Agriculture and Industry
Ltd.
>0.52f
Commercial ethyl oleate Tecnosyn >0.75
Commercial ethyl linoleate Sigma Aldrich >0.65
a
As reported by the supplier.
b
High oleic sunflower oil.
c
Commercial mixtures of mono- and diacylglycerols from cottonseed oil.
d
Commercial mixtures of mono- and diacylglycerols from soybean oil.
e
Of fatty compounds.
f
Of monoacylglycerols.
L.C.B.A. Bessa et al. / J. Chem. Thermodynamics 89 (2015) 148–158 149

3. 2.2. Experimental procedure
All fatty compounds used were converted to fatty acid methyl
esters as reported by Hartman and Lago [22], and analysed by
gas chromatography in order to determine the fatty acid composi-
tion according to the official method Ce 1f-96 of the American Oil
Chemists’ Society (AOCS) [23]. The compositions of the commercial
ethyl oleate and ethyl linoleate were also determined by gas
chromatography.
The analysis of fatty acid composition using the aforementioned
method is a simple way to characterise oils and fats because it
reduces the number of their constituents to no more than 18 to
20 fatty acids. On the other hand, their TAG composition includes
much more than 100 components, if it is taken into account triacyl-
glycerols with different fatty acid connected to the glycerol residue
and the corresponding different types of isomerism. A detailed
experimental analysis of oils and fats, in terms of TAGs, can be car-
ried out by liquid or gas chromatography, but the identification of
the chromatographic peaks, sometimes even for major compo-
nents, requires a lot of knowledge and parallel information, since
the required set of pure standards is often not available, attributing
a relatively high uncertainty to these analyses.
Owing to this difficulty in analysing these components experi-
mentally, the probable triacylglycerol composition of the vegetable
oils was calculated using the statistical algorithm suggested by
Antoniosi Filho et al. [24]. These authors compared results acquired
by the proposed method with those obtained by gas chromatogra-
phy for several vegetable oils and observed high correlation
between the gas chromatographic data and the statistical ones.
The statistical method results in a very large number of TAGs
and in order to reduce the number of components, all structural
isomers were added up in a set of components with x carbons
and y double bonds and named according to the major TAG in this
isomer set. The groups with a total TAG concentration less than
0.5 wt.% were ignored.
(Liquid + liquid) equilibrium results for the systems containing
{sunflower oil + mixture A (+ethyl linoleate) + ethanol} and
{HOSO + mixture B (+ethyl oleate + oleic acid) + ethanol} were
determined at T = (303.15 and 318.15) K, at atmospheric pressure.
These values were determined using a sealed headspace glass
tubes (10 mL) (Perkin Elmer). Components were weighted on an
analytical balance (Precisa, model XT220A, Sweden, ±0.0001 g).
The tubes were vigorously stirred using a vortex (IKA, model
Genius3) for 30 min. All systems were left to rest for at least 36 h
with temperature controlled in a thermostatic bath Cole Parmer,
model Polystat (T/K ± 0.01). Two clear layers and a well-defined
interface were formed when the systems reached the equilibrium
state, the upper layer being the alcoholic phase (AP), and the lower
layer the oil-rich phase (OP). At the end of the experiment, samples
of both phases were carefully collected using syringes and diluted
directly with toluene to guarantee an immediate dilution of the
samples and avoid further separation into two liquid phases at
ambient temperature. The compounds of each phase were identi-
fied and quantified.
The quantification of ethyl esters, acylglycerols and ethanol was
conducted in a HPLC (High-Performance Liquid Chromatography)
Shimadzu, model 20AT, equipped with a single 10.0 nm Phenogel
size exclusion column (300 Á 7.8 mm ID, 5 lm) (Phenomenex,
Torrance, CA, USA), a RI detector (RID-10A), a model CTO-10AS
VP column oven set at 40 °C, a model CBM-20A system controller
and a LC-Solution 2.1 software for data acquisition. Elution was
carried out in isocratic mode using 0.25% (v/v) acetic acid in
toluene at a flow rate of 1.0 mL Á minÀ1
. An auto sampler and injec-
tor were used to inject 20 lL of the sample into the HPLC system
[25,26]. This methodology was also used to qualitatively analyse
all fatty reagents used in this study.
The quantitative determination was carried out using calibra-
tion curves (external calibration) obtained by using solutions made
with the same reagents used in the equilibrium systems. The com-
pounds were diluted with toluene in the concentration range from
(0.18 to 52) mg Á mLÀ1
. The values obtained were fitted by linear
TABLE 2
Fatty acid composition of fatty reagents (% mass).a
Fatty acid/ethyl ester Symbol Cx:yb
Sunflower oil HOSO Mixture A Mixture B Ethyl oleate Ethyl linoleate
Dodecanoic L C12:0 0.02 0.04 2.54
Tetradecanoic M C14:0 0.07 0.05 0.72 0.09 0.29 0.11
Hexadecanoic P C16:0 6.15 3.86 22.08 11.38 4.62 7.98
9-Hexadecenoic Po C16:1 0.09 0.09 0.47 0.08 0.10
Octadecanoic S C18:0 3.38 2.90 2.33 5.52 1.84 2.27
cis-9-Octadecenoic O C18:1 31.68 80.94 16.45 23.38 78.08 12.61
cis-9,cis-12-Octadecadienoic Li C18:2 57.32 10.44 57.02 52.21 11.93 76.38
trans-9,trans-12-Octadecadienoic Li Tc
C18:2 Tc
2.57
All-cis-9,12,15-octadecatrienoic Le C18:3 0.16 0.31 0.24 3.53 0.20
All-trans-9,12,15-octadecatrienoic Le Tc
C18:3 Tc
0.28 0.20
Icosanoic A C20:0 0.28 0.29 0.21 0.41 0.08 0.07
cis-9-Icosenoic Ga C20:1 0.16 0.25 0.05 0.14 0.08 0.19
Docosanoic B C22:0 0.71 0.87 0.13 0.45 0.13 0.09
13-Docosenoic E C22:1 0.41
a
Standard uncertainties u are u(w/%) = 0.02.
b
Cx:y: x is the number of carbons and y is the number of double bonds.
c
Trans isomers.
TABLE 3
Probable triacylglycerol compositions of the vegetable oils.a
Group
x:yb
Main
TAG
M/g Á molÀ1
Sunflower oil HOSO
% molar % mass % molar % mass
50:2 PPLi 831.35 0.84 0.80
52:2 OOP 859.41 2.85 2.79 8.95 8.70
52:3 POLi 857.39 7.54 7.36 2.51 2.44
52:4 LiLiP 855.38 6.96 6.78
54:2 OOS 887.46 1.29 1.31 6.09 6.12
54:3 OOO 885.45 6.95 7.01 55.27 55.42
54:4 OOLi 883.43 20.87 21.00 21.09 21.10
54:5 LiLiO 881.41 31.93 32.04 3.36 3.35
54:6 LiLiLi 879.40 19.53 19.57
56:2 OOA 915.51 0.61 0.63
56:3 OOGa 913.50 0.60 0.62
58:2 OOBe 943.57 1.52 1.62
58:3 OLiBe 941.55 0.65 0.70
58:4 LiLiBe 939.54 0.59 0.64
a
Standard uncertainties u are u(x/%) = 0.5.
b
x:y, x = number of carbons (except carbons of glycerol) and y = number of double
bonds.
150 L.C.B.A. Bessa et al. / J. Chem. Thermodynamics 89 (2015) 148–158

4. regression and the corresponding equations were generated for
quantification.
To verify the quality of the results, the procedure developed by
Marcilla et al. [27] and previously applied to fatty systems by
Rodrigues et al. [28] was utilised. According to Marcilla et al.
[27], values of global mass balance deviation less than 0.5% ensure
the good quality of the experimental data. The global mass balance
deviation corresponds to the difference between the sums of the
calculated mass in both liquid phases and the actual value for total
mass used in the experiment, divided by the total mass.
2.3. Thermodynamic modelling
2.3.1. NRTL modelling approach
The experimental values determined were used to adjust all
binary interaction parameters of the NRTL model. Parameters
adjustments were made by considering the systems as if they were
composed by a single triacylglycerol, representatives of diacylglyc-
erol and monoacylglycerol, ethyl linoleate or ethyl oleate, ethanol
and oleic acid, when applied, so that the systems studied are com-
posed by up to 6 components. The molar masses Mi of the repre-
sentative tri-, di- and monoacylglycerol and ethyl esters were,
respectively, determined from the molar composition of the veg-
etable oils, commercial mixtures of mono- and diacylglycerols
and the commercial ethyl esters.
The binary parameters were obtained according to the proce-
dure developed by Stragevitch and d’Ávila [29], using the modified
simplex method by the minimisation of the composition objective
function defined as:
S ¼
XD
m¼1
XN
n¼1
XPÀ1
i¼1
wFI;exp
inm À wFI;calc
inm
rwFI
inm
!2
þ
wFII;exp
inm À wFII;calc
inm
rwFII
inm
!2
2
4
3
5; ð1Þ
TABLE 4
Probable tri-, di- and monoacylglycerol compositions of the commercial mixture A.a
Main TAG M/g Á molÀ1
% molar DAG M/g Á molÀ1
% molar MAG M/g Á molÀ1
% molar
MLiP 803.30 0.71 MP 540.85 0.24 M 302.43 0.85
PPP 807.33 1.39 MO 566.89 0.33 P 330.48 16.19
PPO 833.37 2.80 MLi 564.88 1.13 Po 328.47 7.72
PPLi 831.35 9.89 PP 568.91 5.62 S 358.54 0.18
MLiO 829.34 0.98 PoLi 590.91 15.44 O 356.52 19.53
LiLiM 827.32 0.84 PS 596.96 0.18 Li 354.51 55.54
POS 861.42 0.54 PO 594.95 8.90
OOP 859.41 3.71 PLi 592.93 11.82
POLi 857.39 13.13 SO 623.00 0.18
LiLiP 855.38 23.16 OO 620.98 5.13
LiLiPo 853.36 0.91 OLi 618.97 19.40
OOO 885.45 1.70 LiLi 616.95 31.65
OOLi 883.43 6.58
LiLiO 881.41 15.46
LiLiLi 879.40 18.19
a
Standard uncertainties u are u(x/%) = 0.5.
TABLE 5
Probable tri-, di- and monoacylglycerol compositions of the commercial mixture B.a
Main TAG M/g Á molÀ1
% molar DAG M/g Á molÀ1
% molar MAG M/g Á molÀ1
% molar
PPO 833.37 1.03 PP 568.91 1.16 P 330.48 12.49
PPLi 831.35 2.46 OS 596.96 0.30 S 358.54 2.78
LiLiP 855.38 13.01 PO 594.95 7.36 O 356.52 26.87
PLeLi 853.36 1.76 PLi 592.93 14.41 Li 354.51 56.13
POS 861.42 0.90 PLe 590.91 0.59 Le 352.49 1.72
OOP 859.41 4.30 SO 623.00 3.31
POLi 857.39 10.54 SLi 620.98 1.95
OOS 887.46 1.59 OO 620.98 6.74
SOLi 885.45 5.86 OLi 618.97 29.59
OOLi 883.43 14.35 LiLi 616.95 31.73
LiLiO 881.41 21.84 LiLe 614.94 2.86
LiLiLi 879.40 18.97
LiLiLe 877.38 3.41
a
Standard uncertainties u are u(x/%) = 0.5.
TABLE 6
Composition of the vegetable oils and commercial mixtures A and B (% mass).a
Mass fraction
Sunflower oil HOSO Mixture A Mixture B
TAG 99.33 99.00 6.49 5.26
DAG 0.67 1.00 32.35 34.86
MAG 61.16 59.89
a
Standard uncertainties u are u(w/%) = 0.46.
TABLE 7
Probable diacylglycerol compositions of the vegetable oils.a
Mole per cent
DAG M/g Á molÀ1
Sunflower oil HOSO
PP 568.91 0.28
PO 594.95 4.41 6.80
PLi 592.93 7.72 0.84
SO 623.00 0.86 4.06
OO 620.98 15.29 68.22
OLi 618.97 37.92 17.14
LiLi 616.95 32.69 1.12
AO 651.05 0.41
OGa 649.04 0.40
OBe 679.11 0.22 1.01
LiBe 677.09 0.61
a
Standard uncertainties u are u(x/%) = 0.5.
L.C.B.A. Bessa et al. / J. Chem. Thermodynamics 89 (2015) 148–158 151

5. where D is the total number of data sets, N is the total number of tie
lines, P is the total number of components in each data set; i, n, and
m stand for component, tie line and data group, respectively; FI and
FII refer to phases I and II, respectively; exp and calc stand for exper-
imental and calculated mass fractions (w), respectively, rwOP
inm
and
rwAP
inm
are the standard deviations observed in the composition of
the two liquid phases.
The deviations between experimental and calculated composi-
tions in both phases were calculated using the root mean square
deviation (Dw/%), which is given by the following equation:
Dw ¼ 100
XN
n¼1
XP
i¼1
wFI;exp
i;n À wFI;calc
i;n
2
þ wFII;exp
i;n À wFII;calc
i;n
2
2NP
0
B
B
B
B
@
1
C
C
C
C
A
1=2
:
ð2Þ
2.3.2. UNIFAC modelling approach
The UNIFAC thermodynamic model was used to predict the LLE
of the system. Structural groups selected to represent the studied
systems were ‘‘CH3’’, ‘‘CH2’’, ‘‘CH’’, ‘‘CH = CH’’, ‘‘CH2COO’’,
‘‘COOH’’ and ‘‘OH’’.
Two sets of interaction parameters were used to test the predic-
tion capability of LLE data. In both cases, the model used was that
presented by Fredenslund et al. [30], and the set of binary interac-
tion parameters denoted as UNIFAC-LLE is that updated by
Magnussen et al. [31]. The set of parameters here referred to as
UNIFAC-HIR was presented by Hirata et al. [32], wherein the
authors used several data for real multicomponent oil
de-acidification systems to readjust group interaction parameters.
Those systems were composed by several triacylglycerols and fatty
acids, ethanol and water. All individual components – tri-, di- and
monoacylglycerols, and ethyl esters – were considered for UNIFAC
modelling calculations.
3. Results
Through the size exclusion chromatography (HPSEC) it was pos-
sible to identify the classes of compounds present in each fatty
reagent used in this study. Thus, it was observed that the commer-
cial mixtures of mono- and diacylglycerols, besides these compo-
nents, also contain a small amount of triacylglycerols. In
addition, it was identified the presence of a very small amount of
diacylglycerols in the vegetable oils and the presence of fatty acids
in the commercial ethyl oleate. The quantification of these com-
pounds will be discussed later.
The fatty acid composition of the vegetable oils and the com-
mercial mixtures of mono- and diacylglycerols are presented in
table 2, as well as the ethyl ester composition of the commercial
ethyl oleate and ethyl linoleate.
Table 3 shows the probable TAG compositions of the sunflower
and high oleic sunflower oils. The names given to the main TAG in
table 3 are related to the symbols used for each fatty acid in table 2,
i.e., the TAG named POLi, for instance, is a triacylglycerol composed
by palmitic acid (P), oleic acid (O) and linoleic acid (Li). The same
applies to all the other TAGs.
TABLE 8
Average molar masses of each pseudocomponent.
Pseudocomponent M/g Á molÀ1
TAG_sunflower oil 877.86
TAG_HOSO 883.21
DAG_mixture A 605.08
DAG_mixture B 612.19
MAG_mixture A 348.57
MAG_mixture B 352.12
Ethyl oleate 306.33
Ethyl linoleate 306.79
Oleic acid 282.46
Ethanol 46.07
TABLE 9
(Liquid + liquid) equilibrium values for the system {sunflower oil (1)a
+ DAG1 (3) + MAG1 (5) (+ethyl linoleate (7)) + ethanol (10)} at T = (303.15 and 318.15) K, and P = 93.8 kPa.b
T/K Overall Composition Alcoholic phase Oil phase d/%c
w1 w3 w5 w7 w10 w1 w3 w5 w7 w10 w1 w3 w5 w7 w10
303.15 0.4969 0.0034 0.0000 0.0000 0.4997 0.0578 0.0026 0.0000 0.0000 0.9396 0.8630 0.0048 0.0000 0.0000 0.1322 0.05
0.4415 0.0223 0.0367 0.0000 0.4995 0.0997 0.0187 0.0550 0.0000 0.8266 0.7762 0.0265 0.0194 0.0000 0.1779 0.07
0.4041 0.0346 0.0603 0.0000 0.5010 0.1340 0.0293 0.0825 0.0000 0.7542 0.7095 0.0397 0.0373 0.0000 0.2135 0.06
0.3863 0.0413 0.0732 0.0000 0.4992 0.1643 0.0364 0.0960 0.0000 0.7033 0.6641 0.0468 0.0467 0.0000 0.2424 0.06
0.3658 0.0480 0.0862 0.0000 0.5000 0.2081 0.0439 0.1038 0.0000 0.6442 0.6142 0.0532 0.0598 0.0000 0.2728 0.01
0.3516 0.0524 0.0947 0.0000 0.5013 0.2498 0.0490 0.1070 0.0000 0.5942 0.5648 0.0573 0.0702 0.0000 0.3077 0.02
0.4740 0.0111 0.0150 0.0000 0.4999 0.0810 0.0092 0.0234 0.0000 0.8864 0.8123 0.0137 0.0073 0.0000 0.1667 0.02
0.4518 0.0114 0.0157 0.0208 0.5003 0.0873 0.0094 0.0235 0.0149 0.8649 0.7806 0.0136 0.0080 0.0247 0.1731 0.08
0.4332 0.0113 0.0159 0.0406 0.4990 0.0952 0.0092 0.0229 0.0294 0.8433 0.7391 0.0129 0.0087 0.0483 0.1910 0.18
0.4040 0.0105 0.0148 0.0703 0.5004 0.1094 0.0086 0.0205 0.0523 0.8092 0.6796 0.0118 0.0088 0.0832 0.2166 0.25
0.3849 0.0108 0.0156 0.0887 0.5000 0.1355 0.0095 0.0210 0.0731 0.7609 0.6453 0.0122 0.0089 0.1064 0.2272 0.01
0.3632 0.0109 0.0159 0.1096 0.5004 0.1429 0.0093 0.0199 0.0900 0.7379 0.5947 0.0118 0.0107 0.1271 0.2557 0.21
318.15 0.4970 0.0034 0.0000 0.0000 0.4996 0.0774 0.0025 0.0000 0.0000 0.9201 0.8557 0.0044 0.0000 0.0000 0.1399 0.02
0.4738 0.0113 0.0153 0.0000 0.4996 0.0908 0.0084 0.0233 0.0000 0.8775 0.8234 0.0143 0.0076 0.0000 0.1547 0.00
0.4599 0.0160 0.0244 0.0000 0.4997 0.1007 0.0122 0.0368 0.0000 0.8503 0.8001 0.0189 0.0129 0.0000 0.1681 0.02
0.4410 0.0225 0.0369 0.0000 0.4996 0.1140 0.0176 0.0528 0.0000 0.8156 0.7656 0.0259 0.0202 0.0000 0.1883 0.12
0.4133 0.0321 0.0555 0.0000 0.4991 0.1385 0.0268 0.0764 0.0000 0.7583 0.7190 0.0363 0.0322 0.0000 0.2125 0.09
0.3858 0.0411 0.0730 0.0000 0.5001 0.1754 0.0367 0.0935 0.0000 0.6944 0.6455 0.0450 0.0481 0.0000 0.2614 0.05
0.4636 0.0116 0.0160 0.0096 0.4992 0.0979 0.0099 0.0213 0.0074 0.8635 0.7885 0.0132 0.0089 0.0108 0.1786 0.16
0.4429 0.0113 0.0157 0.0306 0.4995 0.1054 0.0089 0.0238 0.0227 0.8392 0.7451 0.0125 0.0091 0.0349 0.1984 0.17
0.4243 0.0111 0.0155 0.0497 0.4994 0.1184 0.0090 0.0230 0.0386 0.8110 0.7001 0.0122 0.0094 0.0573 0.2210 0.12
0.3945 0.0107 0.0151 0.0796 0.5001 0.1392 0.0095 0.0222 0.0669 0.7622 0.6371 0.0115 0.0099 0.0907 0.2508 0.02
0.3730 0.0106 0.0154 0.1015 0.4995 0.1445 0.0085 0.0203 0.0844 0.7423 0.5869 0.0112 0.0108 0.1150 0.2761 0.18
a
Includes only TAG.
b
Standard uncertainties u are u(T/K) = 0.1, u(P/kPa) = 0.3, u(w) = 0.0022.
c
Overall mass balance deviation [27].
152 L.C.B.A. Bessa et al. / J. Chem. Thermodynamics 89 (2015) 148–158

6. TABLE 10
(Liquid + liquid) equilibrium values for the system {HOSO (2)a
+ DAG2 (4) + MAG2 (6) (+ethyl oleate (8) + oleic acid (9)) + ethanol (10)} at T = (303.15 and 318.15) K, and P = 94.1 kPa.b
T/K Overall Composition Alcoholic phase Oil phase d/%c
w2 w4 w6 w8 w9 w10 w2 w4 w6 w8 w9 w10 w2 w4 w6 w8 w9 w10
303.15 0.4947 0.0050 0.0000 0.0000 0.0000 0.5003 0.0541 0.0046 0.0000 0.0000 0.0000 0.9413 0.8544 0.0068 0.0000 0.0000 0.0000 0.1388 0.09
0.4388 0.0251 0.0355 0.0000 0.0000 0.5006 0.0858 0.0207 0.0537 0.0000 0.0000 0.8398 0.7813 0.0294 0.0177 0.0000 0.0000 0.1716 0.01
0.4003 0.0392 0.0605 0.0000 0.0000 0.5000 0.1301 0.0346 0.0834 0.0000 0.0000 0.7519 0.7173 0.0435 0.0343 0.0000 0.0000 0.2049 0.02
0.3818 0.0455 0.0716 0.0000 0.0000 0.5011 0.1353 0.0406 0.0948 0.0000 0.0000 0.7293 0.6844 0.0507 0.0445 0.0000 0.0000 0.2204 0.04
0.3637 0.0520 0.0831 0.0000 0.0000 0.5012 0.1682 0.0469 0.1044 0.0000 0.0000 0.6805 0.6376 0.0573 0.0560 0.0000 0.0000 0.2491 0.03
0.3443 0.0590 0.0955 0.0000 0.0000 0.5012 0.2089 0.0552 0.1105 0.0000 0.0000 0.6254 0.5912 0.0653 0.0672 0.0000 0.0000 0.2763 0.04
0.4701 0.0144 0.0165 0.0000 0.0000 0.4990 0.0645 0.0117 0.0263 0.0000 0.0000 0.8975 0.8380 0.0179 0.0069 0.0000 0.0000 0.1372 0.01
0.4504 0.0141 0.0164 0.0184 0.0017 0.4990 0.0709 0.0117 0.0261 0.0128 0.0020 0.8765 0.8030 0.0169 0.0081 0.0236 0.0014 0.1470 0.08
0.4304 0.0136 0.0159 0.0379 0.0035 0.4987 0.0755 0.0112 0.0241 0.0264 0.0041 0.8587 0.7544 0.0165 0.0081 0.0483 0.0028 0.1699 0.01
0.4025 0.0135 0.0162 0.0651 0.0060 0.4967 0.0882 0.0116 0.0232 0.0479 0.0070 0.8221 0.7006 0.0158 0.0083 0.0806 0.0050 0.1897 0.09
0.3821 0.0133 0.0163 0.0819 0.0075 0.4989 0.0956 0.0117 0.0225 0.0619 0.0086 0.7997 0.6635 0.0159 0.0101 0.1008 0.0065 0.2032 0.01
0.3603 0.0131 0.0163 0.1032 0.0095 0.4976 0.1103 0.0117 0.0221 0.0811 0.0107 0.7641 0.6186 0.0152 0.0095 0.1252 0.0083 0.2232 0.05
318.15 0.4958 0.0050 0.0000 0.0000 0.0000 0.4992 0.0749 0.0046 0.0000 0.0000 0.0000 0.9205 0.8418 0.0065 0.0000 0.0000 0.0000 0.1517 0.06
0.4723 0.0136 0.0152 0.0000 0.0000 0.4989 0.0853 0.0116 0.0247 0.0000 0.0000 0.8784 0.8184 0.0158 0.0073 0.0000 0.0000 0.1585 0.05
0.4571 0.0190 0.0247 0.0000 0.0000 0.4992 0.0904 0.0155 0.0376 0.0000 0.0000 0.8565 0.7936 0.0218 0.0128 0.0000 0.0000 0.1718 0.03
0.4395 0.0256 0.0364 0.0000 0.0000 0.4985 0.1006 0.0212 0.0545 0.0000 0.0000 0.8237 0.7638 0.0297 0.0197 0.0000 0.0000 0.1868 0.03
0.4146 0.0354 0.0537 0.0000 0.0000 0.4963 0.1202 0.0307 0.0738 0.0000 0.0000 0.7753 0.7096 0.0394 0.0338 0.0000 0.0000 0.2172 0.01
0.3828 0.0458 0.0722 0.0000 0.0000 0.4992 0.1574 0.0412 0.0941 0.0000 0.0000 0.7073 0.6737 0.0507 0.0430 0.0000 0.0000 0.2326 0.08
0.4615 0.0138 0.0157 0.0090 0.0008 0.4992 0.0846 0.0119 0.0251 0.0066 0.0010 0.8708 0.8032 0.0149 0.0082 0.0109 0.0007 0.1621 0.01
0.4399 0.0137 0.0159 0.0291 0.0027 0.4987 0.0976 0.0122 0.0249 0.0225 0.0033 0.8395 0.7609 0.0152 0.0081 0.0358 0.0021 0.1779 0.07
0.4225 0.0123 0.0138 0.0450 0.0041 0.5023 0.1025 0.0115 0.0217 0.0362 0.0051 0.8230 0.7241 0.0139 0.0078 0.0548 0.0033 0.1961 0.20
0.3935 0.0124 0.0144 0.0728 0.0067 0.5002 0.1240 0.0114 0.0200 0.0595 0.0078 0.7773 0.6593 0.0134 0.0091 0.0871 0.0056 0.2255 0.08
0.3665 0.0121 0.0144 0.0905 0.0083 0.5082 0.1214 0.0110 0.0194 0.0758 0.0097 0.7627 0.6230 0.0139 0.0086 0.1085 0.0072 0.2388 0.13
a
Includes only TAG.
b
Standard uncertainties u are u(T/K) = 0.1, u(P/kPa) = 0.5, u(w) = 0.0014.
c
Overall mass balance deviation [27].
L.C.B.A.Bessaetal./J.Chem.Thermodynamics89(2015)148–158153

7. For the commercial mixtures of mono- and diacylglycerols, the
probable TAG compositions were determined using the same pro-
cedure and, from these compositions, the compositions in mono-
and diacylglycerols were estimated considering the probability of
the partial rupture of the triacylglycerols without preference for
specific ester bonds. Tables 4 and 5 present the probable TAG,
DAG and MAG compositions of the commercial mixtures A and B,
respectively, where the symbols given to DAGs follow the same
reasoning aforementioned for the TAGs. Note that the composi-
tions of each class of components, viz. TAG, DAG and MAG, pre-
sented in tables 4 and 5, sum to 100%.
The concentration of fatty acids in the commercial ethyl oleate
was determined by titration according to the official method 2201
of the IUPAC [33] with an automatic buret (Metrohm, Model
Dosimat 715). The analysis was replicated three times and the
average value is 8.43 wt.%, expressed in oleic acid.
As for the commercial mixtures A and B, the quantification of
mono-, di- and triacylglycerols was performed by gas chromatog-
raphy with flame ionisation detector, according to the official
method ASTM D 6585 [34]. This analysis was carried out at the
Analytical Center of the Institute of Chemistry at the University
of Campinas (IQ/UNICAMP), and the results are presented in table
6. Having these compositions, calibration curves were made with
the commercial mixtures A and B and the angular coefficients
obtained for the diacylglycerols were used to determine the DAG
compositions in the vegetable oils, which are also presented in
table 6. The correct and detailed characterisation of input materials
allowed the construction of calibration curves in order to thor-
oughly describe the equilibrium phases obtained in the experi-
ments in terms of their various classes of components.
Despite being very small, the composition of DAG in the veg-
etable oils was taken into account in both the experimental data
and in the thermodynamic calculations. However, in the case of
the NRTL model, the molar masses Mi of the representative DAG
were calculated considering only the molar composition of the
commercial mixtures of mono- and diacylglycerols. The average
molar masses of diacylglycerols from mixture A and mixture B
were calculated according to tables 4 and 5, and the values
obtained were M = (605.08 and 612.19) g Á molÀ1
for DAGs from
mixtures A and B, respectively. It is worth mentioning that the
error introduced by considering only the compositions of the com-
mercial mixtures in the DAGs molar masses calculation is fairly
small, since the amount of DAGs in the vegetable oils are quite
low, as already mentioned, and because the average molar masses
of DAGs from vegetable oils (M = (615.93 and 614.10) g Á molÀ1
for
DAGs from sunflower oil and HOSO, respectively) do not differ sig-
nificantly from those calculated for the commercial mixtures.
These average molar masses were calculated according to the dia-
cylglycerols compositions of the vegetable oils, presented in table
7, which were estimated in the same way as for the mixtures A
and B.
Similarly, the TAG content in the commercial mixtures of mono-
and diacylglycerols was also taken into account, but, due to the
same reasons presented above, the average molar masses were cal-
culated considering only the molar composition of the vegetable
oils. According to table 3, the obtained values were M = (877.86
and 883.21) g Á molÀ1
for sunflower and high oleic sunflower oils,
respectively.
The average molar masses of monoacylglycerols from mixtures
A and B were calculated according to tables 4 and 5, obtaining the
values of M = (348.57 and 352.12) g Á molÀ1
for MAGs from mixture
A and B, respectively. Average molar masses of the commercial
ethyl oleate and ethyl linoleate were determined from their ethyl
ester composition presented in table 2. The obtained values were
M = (306.33 and 306.79) g Á molÀ1
, respectively. The average molar
masses of each pseudo component considered in the NRTL mod-
elling is summarised in table 8.
Regarding the UNIFAC model, all different components were
considered in the calculation, i.e., all tri- and diacylglycerols from
vegetable oils, all tri-, di- and monoacylglycerols from mixtures A
and B, and all ethyl esters from commercial oleate and linoleate,
so that the compositions of the input materials were employed
as precisely as possible. This means that, in total, 62 different com-
ponents were considered.
TABLE 11
Deviations for the global mass balance of the phase compositions.
System d/%a
Sunflower oil/DAG1/MAG1/ethyl linoleate/ethanol, T = 303.15 K 0.085
Sunflower oil/DAG1/MAG1/ethyl linoleate/ethanol, T = 318.15 K 0.087
HOSO/DAG2/MAG2/ethyl oleate/oleic acid/ethanol, T = 303.15 K 0.039
HOSO/DAG2/MAG2/ethyl oleate/oleic acid/ethanol, T = 318.15 K 0.068
a
Overall mass balance deviation according to Marcilla et al. [27].
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
Ki
Temperature/K
303.15 318.15
FIGURE 2. Average distribution coefficient of: e, DAG1; h, MAG1; s, ethyl linoleate; D, DAG2; Â, MAG2; +, ethyl oleate; d, oleic acid.
154 L.C.B.A. Bessa et al. / J. Chem. Thermodynamics 89 (2015) 148–158

8. In the present study, the following notations were given to the
components: DAG1 for the DAGs of (sunflower oil + mixture A),
DAG2 for the DAGs of (HOSO + mixture B), and MAG1 and MAG2
for the MAGs of mixtures A and B, respectively. Tables 9 and 10
contain the values of the overall composition and the correspond-
ing tie lines for the systems composed by {sunflower oil (1) + DAG1
(3) + MAG1 (5) (+ethyl linoleate (7)) + ethanol (10)} and {HOSO
(2) + DAG2 (4) + MAG2 (6) (+ethyl oleate (8) + oleic acid
(9)) + ethanol (10)} at T = (303.15 and 318.15) K. All concentrations
are expressed in mass fraction.
The mass balances were checked and the average results
obtained for each set of experimental values are shown in table
11. In all cases, the average values were lower than 0.09%, which
indicates the good quality of the experimental data. Note that
the mass balance deviations for every tie line are also given in
tables 9 and 10 and that the highest value obtained (0.25%) is still
much lower than the maximum deviation suggested by Marcilla
et al. [27] for checking the quality of the experimental data.
The ratio between the content of the component i in the alco-
holic phase and the content of this component in the oil phase in
each tie line is called distribution coefficient. The average distribu-
tion coefficients of the components, with the corresponding error
bars, are shown in figure 2. It can be observed that for all systems
studied, the distribution coefficients of DAGs and esters were smal-
ler than unity, indicating their preference for the oil phase. On the
other hand, for MAGs and fatty acids, the distribution coefficients
were greater than unity, showing a clear preference for the alco-
holic phase.
The miscibility of a vegetable oil in ethanol is affected mainly by
the unsaturation and chain length of its fatty acids constituents
[35]. Figure 3 presents the experimental ELL values for both sys-
tems studied at T = 303.15 K. It can be observed that the
two-phase region for the system {HOSO (2) + DAG2 (4) + MAG2
(6) + ethanol (10)} is larger than the biphasic region of the system
{sunflower oil (1) + DAG1 (3) + MAG1 (5) + ethanol (10)}, indicat-
ing a greater miscibility in the case of the last system. In fact, sun-
flower oil is rich in linoleic acid, a fatty acid more unsaturated than
oleic acid, which is the major fatty acid present in HOSO. For any
given temperature, the more unsaturated the vegetable oil, the
greater is its miscibility in ethanol and, consequently, the smaller
the two-phase region.
Tables 12 and 13 contain values of the parameters of the NRTL
model adjusted to the experimental values for the two systems
studied. The deviations between the experimental and calculated
values are shown in table 14.
Figures 4 and 5 present the experimental and calculated tie
lines for the system (sunflower oil + mixture A + ethanol) at
T = 303.15 K, indicating the DAG1 and MAG1 distribution, respec-
tively. These figures confirm that those components show opposite
behaviour. This occurs because monoacylglycerols contain higher
number of polar groups (hydroxyl groups) than diacylglycerols,
increasing their solubility in ethanol. The same behaviour is
observed for DAG2 and MAG2, at both temperatures. Figure 6
shows experimental and calculated tie lines for the system (sun-
flower oil + mixture A + ethyl linoleate + ethanol) at T = (303.15
and 318.15) K. In order to have a better interpretation of the
five-component phase equilibrium, the experimental and calcu-
lated results are represented in a simplified form, showing only
the ethyl ester (w7) and ethanol (w10) compositions in a explicit
way and grouping the acylglycerols as a third pseudo component,
which consists of TAG-DAG-MAG. From that figure, it is noted that
an increase in temperature from T = (303.15 to 318.15) K causes a
small decrease in the two-phase region, indicating an improve-
ment in the mutual solubility of acylglycerols (TAG, DAG and
MAG) and ethanol. This behaviour is observed for both systems
studied and has already been reported in literature [10,12,36,37].
From figures 4–6 and table 14, it can be seen that the NRTL
model accurately described the LLE behaviour of the systems. Tie
lines calculated by the NRTL model and the experimental data
almost overlap, indicating an accurate description of the LLE and
confirming the low deviations between experimental values and
calculated compositions.
Concerning the UNIFAC, this model did not provide the same
precision, as indicated in table 14. According to figure 7, which
FIGURE 3. (Liquid + liquid) equilibrium for the systems: d, sunflower oil
(1) + DAG1 (3) + MAG1 (5) + ethanol (10), and Â, HOSO (2) + DAG2 (4) + MAG2
(6) + ethanol (10) at T = 303.15 K.
TABLE 12
NRTL parameters for the system {sunflower oil (1) + DAG1 (3) + MAG1 (5) (+ethyl linoleate (7)) + ethanol (10)}.
T = 303.15 K T = 318.15 K
Pair i-j Aij/K Aji/K aij Aij/K Aji/K aij
1-3 À992.88 À434.45 0.56984 À731.47 À447.06 0.46997
1-5 118.46 À347.69 0.10296 142.52 À321.03 0.12137
1-7 533.19 19.786 0.5319 793.26 21.109 0.57
1-10 70.866 1444.7 0.49292 54.153 1464.7 0.50555
3-5 40.941 À29.715 0.37757 90.781 À28.25 0.31806
3-7 À56.945 À306.98 0.56977 À47.73 À298.3 0.37065
3-10 140.8 À2056 0.1 118.31 À1652.9 0.10777
5-7 3247.3 À656.37 0.13493 2938.2 À1033.4 0.14639
5-10 À121.58 671.29 0.37836 À135.01 686.43 0.49335
7-10 À15.523 166.97 0.57 À45.658 201.97 0.56979
L.C.B.A. Bessa et al. / J. Chem. Thermodynamics 89 (2015) 148–158 155

9. contain experimental and calculated tie lines for the system
(HOSO + mixture B + ethanol) at T = 303.15 K, using both sets of
parameters, the ethanol mass fraction was underestimated in the
oil phase and overestimated in the alcoholic phase, particularly
in the case of UNIFAC-LLE parameters. In both cases, the slope of
the calculated tie lines was more accentuated than the slope of
the experimental ones. This effect was greater when using the
UNIFAC-LLE parameters, resulting in higher deviations values.
However, using the UNIFAC-HIR set of parameters, the model pre-
dicted a different behaviour for diacylglycerols, indicating a prefer-
ence for the alcoholic phase, which is not consistent with
experimental results. These deviations can be somehow justified
by the fact that neither Magnussen et al. [31] nor Hirata et al.
[32] used experimental values involving partial acylglycerols in
their data set when adjusting the parameters. Similar improperly
description in LLE modelling of systems containing vegetable oils,
TABLE 13
NRTL Parameters for the system {HOSO (2) + DAG2 (4) + MAG2 (6) (+ethyl oleate (8) + oleic acid (9)) + ethanol (10)}.
T = 303.15 K T = 318.15 K
Pair i-j Aij/K Aji/K aij Aij/K Aji/K aij
2-4 355.85 À237.48 0.56925 428.74 À239.34 0.55624
2-6 À89.708 À63.743 0.21735 À94.895 À49.48 0.21395
2-8 À433.71 175.41 0.14045 À464.9 190.16 0.12222
2-9 7206.5 À546.15 0.10614 7621.4 À246.39 0.12729
2-10 À253.21 1757.2 0.36497 À268.53 1739.3 0.38638
4-6 1407.8 À256.19 0.1 1262.7 À343.43 0.10001
4-8 À110.07 À3165.9 0.20321 À102.26 À2775.4 0.1978
4-9 3741.4 39.494 0.14479 3112.2 42.715 0.22118
4-10 2759.3 À38.441 0.4131 2425 À37.322 0.56989
6-8 À160.15 À13.354 0.13943 À132.18 À13.578 0.15407
6-9 1855.5 631.23 0.10585 2142.3 793.5 0.10002
6-10 À327.15 940.35 0.44749 À334.06 955.19 0.45553
8-9 À59.733 À803.63 0.44596 À92.819 À782.9 0.34846
8-10 À35.525 À83.099 0.13313 À44.798 À84.608 0.11002
9-10 À474.94 339.78 0.48174 À223.97 437.6 0.41941
TABLE 14
Average deviations in phase composition.
System Dw/%
NRTL UNIFAC-LLEa
UNIFAC-HIRb
Sunflower oil/DAG1/MAG1/ethyl linoleate/ethanol, T = 303.15 K 0.434 9.237 5.070
Sunflower oil/DAG1/MAG1/ethyl linoleate/ethanol, T = 318.15 K 0.388 7.844 2.511
HOSO/DAG2/MAG2/ethyl oleate/oleic acid/ethanol, T = 303.15 K 0.348 6.305 2.781
HOSO/DAG2/MAG2/ethyl oleate/oleic acid/ethanol, T = 318.15 K 0.332 5.690 1.804
a
Original parameters [31].
b
Parameters from Hirata et al. [32].
FIGURE 4. (Liquid + liquid) equilibrium for the system {sunflower oil (1) + DAG1
(3) + MAG1 (5) + ethanol (10)} at T = 303.15 K, DAG1 distribution: d, experimental
data; - -, calculated values using NRTL.
FIGURE 5. (Liquid + liquid) equilibrium for the system {sunflower oil (1) + DAG1
(3) + MAG1 (5) + ethanol (10)} at T = 303.15 K, MAG1 distribution: d, experimental
data; - -, calculated values using NRTL.
156 L.C.B.A. Bessa et al. / J. Chem. Thermodynamics 89 (2015) 148–158

10. partial acylglycerols, free fatty acids, ethanol and/or biodiesel,
using UNIFAC, has already been reported in the literature
[4,19,38,39].
On the other hand, according to values in table 14, using the
UNIFAC-HIR set of parameters, it can be observed there is an
improvement in the LLE description, and this is especially signifi-
cant taking into account the ethyl esters behaviour. Figure 8 shows
the tie lines for the system (HOSO + mixture B + ethyl oleate + oleic
acid + ethanol) at T = 303.15 K, in which similar components were
grouped up into the x-axis. The improvement in the description
using the UNIFAC-HIR set of parameters is fairly evident.
Although Hirata et al. [32] have advanced significantly in the LLE
description of systems containing vegetable oils, it can be observed
that further enhancement is still needed. The results presented in
figures 7 and 8 show that despite the availability of group interac-
tion parameters and their practical use, UNIFAC models must be
used cautiously in design analysis and process simulation of
biodiesel production due to the deviations in the prediction of
LLE for this type of system.
4. Conclusions
The results presented in this study confirm that it is indeed
important to consider the partial acylglycerols when studying the
phase equilibrium in biodiesel systems, mainly in the transesterifi-
cation step. In addition, the information acquired in this study may
also be useful for the downstream processes in cases of incomplete
conversion. It was observed that monoacylglycerols, which has a
higher number of polar groups (hydroxyl groups), have a higher
affinity with the alcoholic phase when compared to diacylglyc-
erols. The NRTL model was applied to the equilibrium results and
the binary interaction parameters were optimised for each system.
Good agreement was observed between experimental values and
the correlations, indicating the applicability of this model for such
systems. In contrast, the UNIFAC model, using two sets of parame-
ters from the literature, yielded higher deviations values, which
motivates future work to improve further the model by adjusting
a specific set of parameters. The results obtained in the present
study may allow a more accurate description of the real behaviour
of the transesterification system involved in biodiesel production
process and, consequently, its optimization.
Acknowledgements
The authors wish to acknowledge CAPES for the scholarship and
FAPESP (08/56258-8 and 09/54137-1) and CNPq (304495/2010-7
and 406856/2013-3) for the financial support.
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JCT 15-86
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