Eniko Haaz1, Daniel Fozer1, Andras Jozsef Toth1. 1. Department of Chemical and Environmental Process Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3, Budapest H-1111, Hungary.
Abstract
Acetaldehyde diethyl acetal (herein called acetal) is an important pollutant of anhydrous ethanol. Isobaric vapor-liquid equilibrium (VLE) of an ethanol-acetal binary system was measured using a vapor condensate and liquid circulation VLE still. The experimental data were correlated with Wilson, nonrandom two-liquid (NRTL), and universal quasichemical (UNIQUAC) activity coefficient models, which were found suitable for representing the VLE data. Proper agreements between experimental and calculated VLE data were obtained, which were then confirmed with consistency tests. The applicability of the novel VLE data was demonstrated during an investigation of an anhydrous ethanol purification column. Reduction of the concentration of acetal and other pollutants was examined and optimized in a flowsheet environment. The modeling results were verified in a laboratory with an experimental distillation column, confirming a correct agreement between the results. It must be highlighted that the developed method is suitable for the production of pharmacopeial quality anhydrous alcohol, based on reliable, verified VLE data. The results show the importance of accurate VLE data in critical compositions (low pollutant content); moreover, aiming at high product purity, experimental validation has paramount importance. The consistency between the three platforms (VLE and distillation experiments and flowsheet simulation) confirms the accuracy of the developed method.
Acetaldehydediethyl acetal (herein called acetal) is an important pollutant of anhydrous ethanol. Isobaric vapor-liquid equilibrium (VLE) of an ethanol-acetal binary system was measured using a vapor condensate and liquid circulation VLE still. The experimental data were correlated with Wilson, nonrandom two-liquid (NRTL), and universal quasichemical (UNIQUAC) activity coefficient models, which were found suitable for representing the VLE data. Proper agreements between experimental and calculated VLE data were obtained, which were then confirmed with consistency tests. The applicability of the novel VLE data was demonstrated during an investigation of an anhydrous ethanol purification column. Reduction of the concentration of acetal and other pollutants was examined and optimized in a flowsheet environment. The modeling results were verified in a laboratory with an experimental distillation column, confirming a correct agreement between the results. It must be highlighted that the developed method is suitable for the production of pharmacopeial quality anhydrous alcohol, based on reliable, verified VLE data. The results show the importance of accurate VLE data in critical compositions (low pollutant content); moreover, aiming at high product purity, experimental validation has paramount importance. The consistency between the three platforms (VLE and distillation experiments and flowsheet simulation) confirms the accuracy of the developed method.
Certain
industries, for example, pharmaceutical and fine chemical sectors,
need high purity chemicals. Such chemicals are frequently produced
by distillation. In the case of pharmacopeial anhydrous alcohol, there
are strict requirements regarding polluting compounds. For the reliable
production of such ethanol, a proper process should be designed. Nowadays,
the process design activities are strongly based on professional flowsheeting
software programs. These software programs must operate on a reliable
database, rigorous modeling tools, and accurate calculation based
on thermodynamic equilibria. The accuracy of these tools is generally
sufficient; however, in a research focused on obtaining high purity
chemicals, special attention must be paid to the evaluation of the
computed results.A typical example for the application of distillation
is the production of ethanol, as a precious chemical in fine chemical
industry.[1] Basically, ethanol production
is performed through a biological process, resulting in bioethanol,
obtained in different qualities/purities depending on its application.[2−5]Anhydrous ethanol has an alcohol content of at least 99.7
v/v % and thus an extremely low water content.[6] The extremely low water content makes it suitable for use by fuel
manufacturers to make mixed fuel.[7] By mixing
with traditional petrol in fuel production, the proportion of biocomponents
has increased, thus reducing traffic emissions of environmentally
harmful greenhouse gases.[8−10] Pharmacopeial anhydrous alcohol
is a premium quality anhydrous alcohol which, besides conforming to
the relevant EU and Hungarian specifications, also meets the strict
requirements of the PHHg VIII, EU Pharma 4 pharmacopeial regulations.[11,12] The major aim of this work is to develop the conversion process from anhydrous
ethanol produced on a biological source to pharmacopeial anhydrous
alcohol using distillation.The required level of purity is
extremely difficult to achieve as raw anhydrous alcohol contains a
wide variety of contaminants, albeit only in small concentrations.
Examples of ethanol contaminants include acetal, acetaldehyde, acetone,
benzene, cyclohexane, methanol, ethyl methyl ketone, isobutyl methyl
ketone, propanol, isopropyl alcohol, butanols, furfural, 2-methylpropan-2-ol,
and 2-methylbutan-2-ol.[13] During the distillation
process, polluting compounds have to be removed to obtain the high
purity bottom product, considered pharmacopeial anhydrous alcohol.One of the most important pollutant compounds is acetal, as it
belongs to the most common contaminants. Acetaldehydediethyl acetal
(1,1-diethoxyethane) is a major flavoring component of distilled beverages,
especially of sherry[14] and malt whisky.[15] In spite of being one of many compounds containing
the acetal functional group, this specific chemical is often simply
referred to as acetal.Acetal is applied in the design of synthetic
perfumes to increase the resistance to oxidation, therefore the lifetime
of perfumes. Acetals have been under consideration as oxygenated additives
to diesel fuel because they drastically decrease the emission of nitrogen
oxides and other particles while retaining or improving the cetane
number and helping in the combustion of the final products, without
decreasing the ignition quality.[16−19]1,1-Diethoxyethane production
involves the reversible reaction of acetaldehyde and ethanol in acid
medium, according to the following: acetaldehyde + 2 ethanol ↔
acetal + water (see Figure ).[20−22] However, acetaldehyde could be replaced by ethylene,
acetylene, or vinyl ether.[23] The advantage
of using acetaldehyde and ethanol as reactants is that ethanol is
produced from renewable sources (mainly from the sugarcane industry)
and acetaldehyde can be produced by dehydrogenation of ethanol or
direct ethylene oxidation.[19,24,25]
Figure 1
Acetalization
of acetaldehyde and ethanol.
Acetalization
of acetaldehyde and ethanol.The reaction shown in Figure is slightly exothermic; at a temperature of 25 °C, a
59% conversion can be achieved with a sulfonic acid catalyst. The
acetal formed can be used as an additive to diesel fuels as it increases
the cetane number and promotes combustion of the mixture.[26]In order to increase the purification
efficiency, it is essential to know the exact vapor–liquid
phase equilibrium data of the mixture. Ionescu et al.[27] have presented the vapor–liquid equilibrium (VLE)
data and nonrandom two-liquid (NRTL), Wilson, and Gothard model parameters
of ethanol–diethyl acetate and i-propanol–diethyl acetate
binary mixtures. In contrast, the VLE data and main thermodynamic
models for other contaminant components of anhydrous ethanol have
already been explored in detail.[28,29] Consequently,
a further goal of this work is to experimentally determine the VLE
data of this binary mixture for universal quasichemical (UNIQUAC)
model parameters too and to verify the VLE data with laboratory distillation
experiments and in a flowsheet environment.The purpose of VLE
analysis is to determine equilibrium-related data and the boiling-dew
point, in addition to thermodynamic data. Today, these can be calculated
with fairly high accuracy using process simulators, various state
equations, and activity coefficient models, but the basis of the calculations
lies in the knowledge of reliable and accurate measurement data and
physicochemical parameters. It is not possible to perform accurate
calculations with thermodynamic relations alone, as it requires knowledge
of appropriate measurement data and parameters derived from them.These can be used to explore the possible azeotropic behavior of
liquid mixtures; furthermore, separation possibilities of liquid mixtures
can also be modeled on the basis of this data. Simulation programs
often determine the state of a multicomponent mixture from the parameters
of the pure components, which can cause discrepancies with their actual
behavior. For example, they show an azeotrope, or a liquid–liquid
distribution, where it does not actually occur, or they do not reveal
it where it is in fact present. However, knowledge of azeotropes is
essential in the design of a separation unit, as they require different
technologies and special design considerations.VLE data and
the resulting pair interaction parameters can be used to model the
separation of different mixtures, as well as for the design of separation
systems. In the context of industrial implementation, the economic
aspects are also taken into account in which case different separation
models can also be used for cost calculation.During the measurements,
it is necessary to examine the equilibrium phases of vapor and liquid
under the same conditions. VLE points can be determined in two ways.
Either the operation is carried out at constant temperature and the
pressure is changed point by point or vice versa. By these means,
it is possible to perform isothermal or isobaric measurements.Since the vast majority of columns in industrial separation units
operate under constant pressure, in the present work, the vapor–liquid
phase equilibrium of the various mixtures is also measured at constant
pressure.However, the measurement data must be examined to
determine whether they are in accordance with the relevant thermodynamic
laws, for which the so-called thermodynamic consistency tests, derived
from thermodynamic relationships, are used.[30] Thermodynamic theorems provide a deeper understanding of different
physical, physicochemical, and thermal processes. The equations derived
from these are still used today to quantitatively describe chemical
systems and phase equilibria. In order to make sure that the measured
data comply with the laws of thermodynamics, consistency tests can
serve as a tool for verification.[31] It
is important to check if the measured equilibria correspond to reality,
that is, whether the measurement points are consistent or inconsistent.[32,33] If they are shown to be consistent, they meet the thermodynamic
theorems and the data set can be considered reliable.
Results and Discussion
First, the modified equipment and
VLE measurement procedure were tested with the acetaldehyde–ethanol
binary mixture as a well-known and studied system. Good reproducibility
and correlation with published results were obtained for the VLE data[29] at 101 kPa (Supporting Information: Table S1, Figures S1 and S2). It can be stated
that the equilibrium still was suitable for measurements.The
refractive indexes were experimentally determined in the whole concentration
range for the ethanol (1)–acetal (2) system at T = 293.2 K. The data are shown in Table . The concentration versus refractive index
plots are shown in Figure .
Table 1
Experimental Refractive Indexes (nD) of the Ethanol (1)–Acetal (2) Mixture
at 293.2 K, p = 101 kPaa
ethanol content
nD [−]
ethanol content
nD [−]
[mol/mol]
[g/g]
(293.15 K)
[mol/mol]
[g/g]
(293.15 K)
0.0000
0.0000
1.3805
0.5527
0.3251
1.3753
0.0180
0.0071
1.3805
0.5964
0.3655
1.3747
0.0485
0.0195
1.3802
0.6461
0.4158
1.3737
0.0976
0.0405
1.3800
0.6867
0.4608
1.3727
0.1521
0.0654
1.3798
0.7509
0.5402
1.3711
0.2104
0.0941
1.3795
0.8014
0.6114
1.3697
0.2477
0.1138
1.3790
0.8437
0.6779
1.3682
0.3092
0.1486
1.3786
0.8995
0.7773
1.3660
0.3510
0.1741
1.3782
0.9520
0.8855
1.3647
0.4009
0.2069
1.3775
0.9898
0.9743
1.3615
0.4598
0.2491
1.3767
1.0000
1.0000
1.3611
0.5044
0.2840
1.3760
Standard uncertainty u is u(nD) = 0.0001, u(p) = 2 kPa, u(T) = 0.1 K; u(x1) = 0.0001.
Figure 2
Experimental refractive indexes
of the system ethanol (1)–acetal (2) at T = 293.2 K (black
solid circle) x1: mole fraction of ethanol
Experimental refractive indexes
of the system ethanol (1)–acetal (2) at T = 293.2 K (black
solid circle) x1: mole fraction of ethanolStandard uncertainty u is u(nD) = 0.0001, u(p) = 2 kPa, u(T) = 0.1 K; u(x1) = 0.0001.The isobaric
VLE of ethanol (1)–acetal (2) was measured at p = 101 kPa. With the experimental data, NRTL, Wilson, and UNIQAC
parameters were regressed. The experimental and calculated data are
presented in Table and Figures and 4. The activity coefficients presented were calculated
by eq .
Table 2
VLE Data (T, Temperature; x, Liquid
Mole Fraction; y, Vapor Mole Fraction) of Ethanol
(1)–Acetal (2) at p = 101 kPaa
calculated data
experimental data
NRTL
Wilson
UNIQUAC
T [K]
x1
y1
γ1
γ2
T [K]
y1
T [K]
y1
T [K]
y1
373.19
0.0258
0.1089
2.0077
1.0421
375.65
0.0000
375.65
0.0000
375.65
0.0000
369.12
0.0738
0.2595
2.0294
1.1005
371.42
0.1720
371.46
0.1706
371.45
0.1712
365.85
0.1356
0.3721
1.8188
1.1438
368.01
0.2986
368.08
0.2966
368.04
0.2977
364.98
0.1552
0.4224
1.8107
1.0804
365.22
0.3957
365.30
0.3932
365.24
0.3948
360.86
0.2718
0.5389
1.5094
1.2832
362.88
0.4726
362.98
0.4696
362.89
0.4715
360.23
0.2836
0.5607
1.6563
1.2109
360.91
0.5350
361.03
0.5315
360.92
0.5336
358.67
0.3291
0.5853
1.5045
1.2831
359.24
0.5866
359.37
0.5828
359.25
0.5850
357.12
0.3746
0.6297
1.4735
1.3282
357.82
0.6301
357.96
0.6261
357.83
0.6282
356.32
0.4201
0.6567
1.4045
1.3640
356.60
0.6673
356.75
0.6633
356.62
0.6652
355.23
0.4563
0.6818
1.3916
1.3393
355.56
0.6995
355.71
0.6957
355.58
0.6973
354.34
0.5273
0.7206
1.3197
1.4058
354.67
0.7278
354.82
0.7245
354.69
0.7257
353.87
0.5719
0.7474
1.2702
1.4908
353.92
0.7531
354.05
0.7505
353.93
0.7512
353.12
0.6382
0.7779
1.2003
1.5846
353.27
0.7762
353.39
0.7743
353.29
0.7745
352.64
0.6796
0.7939
1.1741
1.7034
352.73
0.7978
352.82
0.7968
352.73
0.7964
352.12
0.7076
0.8092
1.1501
1.7394
352.26
0.8185
352.34
0.8184
352.26
0.8175
351.56
0.7367
0.8219
1.1359
1.8367
351.87
0.8392
351.92
0.8399
351.86
0.8386
351.23
0.7702
0.8325
1.1188
1.8934
351.54
0.8610
351.58
0.8622
351.53
0.8606
351.11
0.8309
0.8646
1.0862
2.1243
351.27
0.8850
351.30
0.8865
351.26
0.8849
351.01
0.8517
0.8785
1.0769
2.1912
351.09
0.9136
351.10
0.9148
351.08
0.9135
350.99
0.9410
0.9381
1.0528
2.5918
351.01
0.9499
351.01
0.9504
351.00
0.9498
350.95
0.8976
0.9009
1.0644
2.3976
351.13
1.0000
351.13
1.0000
351.13
1.0000
350.91
0.9620
0.9556
1.0534
2.8931
Standard uncertainties: u(T) = 0.1 K; u(p) = 1 kPa
Figure 3
y–x diagram for the ethanol (1)–acetal (2)
system at p = 101 kPa with experimental data (black
solid circle), Wilson (green line), UNIQUAC (blue line), and NRTL
(red line) activity coefficient models
Figure 4
T–y–x diagram for the ethanol (1)–acetal
(2) system at p = 101 kPa with experimental data
(black solid circle), Wilson (green line), UNIQUAC (blue line), and
NRTL (red line) activity coefficient models
y–x diagram for the ethanol (1)–acetal (2)
system at p = 101 kPa with experimental data (black
solid circle), Wilson (green line), UNIQUAC (blue line), and NRTL
(red line) activity coefficient modelsT–y–x diagram for the ethanol (1)–acetal
(2) system at p = 101 kPa with experimental data
(black solid circle), Wilson (green line), UNIQUAC (blue line), and
NRTL (red line) activity coefficient modelsStandard uncertainties: u(T) = 0.1 K; u(p) = 1 kPaThe minimization
of ChemCAD’s objective function was utilized to obtain model
parameters[34] with eq .The calculated
mean and maximum deviation results can be found in Table .
Table 3
Accuracy
of NRTL, Wilson, and UNIQUAC Models
NRTL
Wilson
UNIQUAC
T [K]
y1
T [K]
y1
T [K]
y1
mean deviation
0.39
0.0099
0.39
0.0102
0.34
0.0103
max. deviation
0.92
0.0209
0.91
0.0189
0.92
0.0221
As it can be seen, the maximum deviation
is lower than 1.00 for NRTL, Wilson, and UNIQUAC models and no significant
difference is revealed in the accuracy of the models.The volume
and area structural parameters applied in UNIQUAC modeling are demonstrated
in Table .
Table 4
Structural Parameters for Pure Components (R: Volume Parameter and Q: Area Parameter)
parameter
acetal
ethanol
R
4.9868
2.1054
Q
4.332
1.972
It can be determined that ethanol forms a minimal
boiling azeotropic mixture with acetal in the investigated concentration
range. The calculated binary parameters are presented in Table .
Table 5
Calculated Binary (Ethanol and Acetal) Interaction Parameters of
Wilson (λ12, λ21, Adjustable Parameters),
NRTL (Bij, Bji, Dimensionless Interaction Parameters; α, Constant Characteristic
of the Nonrandomness of the Mixture), and UNIQUAC (ΔUij, ΔUji,
Binary Interaction Parameter) Models
NRTL
Wilson
UNIQUAC
Bij
Bji
α
λ12
λ21
ΔUij
ΔUji
559.08
–168.65
0.296
525.002
213.742
16.25
269.9
The thermodynamic consistency test
for ethanol–acetal data was performed according to Herrington’s
area test for isobaric data.[30,34]DH and JH values are calculated
according to the following equations.The DH value was 18.3% and the JH value was
found to be 9.5%; therefore, DH – JH is 8.8%. It can be concluded that the measured
data is suitable for application in a flowsheet environment. The elaborated
ethanol–acetal binary model can be used for simulation of the
ethanol purification column.Figure shows the optimization of ethanol purification.
The red line represents the acetal target concentration in the bottom
product, which is 10 ppm. Acetaldehyde did not occur in the bottom
product in any of the cases. The feed was close to the boiling point
in every case. Studying Figure , the following optimized parameters can be determined: 40
theoretical stages, feed into the eighth stage, the reflux ratio is
26, and column pressure must be kept at 10 kPa. The relatively high
values can be considered realistic because extreme purity ethanol
was the goal. It must be mentioned that 10 kPa has to be achieved
in feed and column pressure to reach the corresponding acetal concentration
in the bottom product. Under a pressure value of 10 kPa, it is difficult
to keep up the working pressure in the laboratory column apparatus;
therefore, computer calculations were not performed below this value.
Figure 5
Optimization
process of modeling of anhydrous ethanol purification.
Optimization
process of modeling of anhydrous ethanol purification.The reboiler duty value was 2278 MJ/h in the optimum. Figure shows the influence
of reboiler duties (Q-RD) on the acetal concentration of the bottom
product (W-Acetal).
Figure 6
Influence of the reboiler duties [Q-RD (MJ/h)] and acetal
concentration of the bottom product [W-Acetal (ppm)] on the reflux
ratio [−] (1), feed stage [−] (2), and stages [−]
(3)
Influence of the reboiler duties [Q-RD (MJ/h)] and acetal
concentration of the bottom product [W-Acetal (ppm)] on the reflux
ratio [−] (1), feed stage [−] (2), and stages [−]
(3)The experiments were carried out
according to the optimized results of the simulations. The reflux
ratio was 26 and the distillate/feed ratio was the same as that of
the simulation, 10%. The feed flow rate was 3 kg/h in the case of
laboratory experiments. The trap flow rate was 0.05 kg/h, which was
analyzed together with the distillate product due to its nearly identical
composition. In this evaluation part, the best available results are
presented. Table shows
the optimized simulation results and their control laboratory measurement
results. The simulation verification can be taken with the objective
function (OFDistillation), which presents minimized deviation
of the simulated and the measured values (see eq ).[35]
Table 6
Comparison of Simulated and Measured Data of the Anhydrous Ethanol
Purification Process
modeling results
experimental
results
OF-distillation
feed
distillate
bottom
distillate
bottom
distillate
bottom
ethanol [wt %]
99.79
98.22
99.97
98.21
99.97
3.25 × 10–9
2.50 × 10–11
methanol
[ppm]
63.6
635.9
0.0
623.7
0.0
3.80 × 10–4
0
acetal [ppm]
994.0
9853.7
9.6
9892.4
9.5
1.53 × 10–5
8.40 × 10–5
ethyl acetate [ppm]
41.1
410.5
0.0
402.6
0.0
3.84 × 10–4
0
acetaldehyde [ppm]
278.3
2783.0
0.0
2794.8
0.0
1.80 × 10–5
0
diethyl ether [ppm]
37.8
377.8
0.0
379.0
0.0
9.77 × 10–6
0
isobutanol [ppm]
210.6
0.0
234.0
0.0
235.3
0
2.74 × 10–5
stream [kg/h]
1000 and 3
100
900
0.3
2.7
temperature [°C]
28.5
28.1
29.1
27.9
29.2
5.14 × 10–5
1.17 × 10–5
pressure [kPa]
10
10
10
10
9
The prespecified purification requirements can be
achieved in both laboratory and simulation cases as shown in Table . As it can be seen,
low objective function values can be achieved due to the accurate
assembly of laboratory apparatus. Furthermore, the laboratory experiments
justified the accuracy of VLE data, especially ethanol–acetal
measurements, which also proved to be valid under vacuum conditions.
Conclusions
VLE data for the ethanol–acetal
binary system were measured using a modified Gillespie still. Experimental
data were correlated with Wilson, NRTL, and UNIQUAC models. It was
demonstrated that acetal forms a minimal boiling azeotropic mixture
with ethanol. The data were applied for the design of an ethanol purification
unit. Pharmacopeial quality anhydrous alcohol can be produced with
the vacuum distillation method. The pollutant content of the bottom
product can be reduced below 300 ppm and for the most important compound,
acetal, a value under 10 ppm can be reached. Evaluating the simulated
and the experimentally measured data, it can be stated that almost
perfect isolation can be guaranteed with the application of the best
available laboratory devices. The other conclusion to be drawn is
that close to 0% or to 100% we land in a dangerous region where modeling
becomes more important and special attention needs to be paid to the
experimental work and analytics. It must be mentioned that there is
consistency between the results of flowsheet simulations, distillation
and VLE experiments, respectively.
Materials
and Methods
Before the examination of anhydrous ethanol purification,
vapor–liquid measurements were performed. The VLE data of acetaldehyde–ethanol
is already well known in the literature.[29] Therefore, this mixture was examined for the correct operation of
the VLE still.The properties of the commercially available
chemicals used in VLE examination are introduced in Table . Ethanol was applied without
further purification. Acetal and acetaldehyde were purified by vacuum
distillation at a pressure of 27 kPa.
Table 7
Description
of Chemicals Applied in This Work (MW: Molecular Weight)
chemical name
formula
MW [g/mol]
source
initial mole fraction purity
purification method
final
mole fraction purity
analysis method
ethanol (1)
C2H6O
46.07
molar chemicals
0.9999
GC–MS
acetal (2)
C6H14O2
118.17
sigma-aldrich
0.9800
distillation
0.9995
GC–MS
acetaldehyde
C2H4O
44.05
sigma-aldrich
0.9950
distillation
0.9999
GC–MS
The VLE still is a modified Gillespie apparatus. An amount of about
100 mL of the appropriate mixture was added to the liquid container
at the site of the top valve. For the heating of the mixture, an electric
resistance wire was used, folded around the boiler tube. Through the
Cottrell-pump, the vapor–liquid mixture was lifted into the
thermometer well. Subsequently, the phases were directed into the
equilibrium chamber, where their separation could occur, at an equilibrium
state. The condensation of the vapor phase took place on the surface of the chamber and in
the condenser, then the resulting condensate was transferred to the
vapor sampler. The sample originating from the liquid phase was obtained
at the site of the liquid sampler. For temperature measurement, a
VWR Traceable Digital Thermometer (China) was used (223–573
K), presenting an uncertainty of 0.1 K. As for atmospheric pressure,
the accuracy of the measurement was 1 kPa.[36] The atmospheric pressure was measured by a VACUUBRAND PC2003 VARIO
(China) vacuum pump.Refractive indexes were determined for
the analysis of the equilibrium samples, three replications were applied.
In addition, gas chromatography analysis was performed for certain
equilibrium and calibration samples as a validation for the refractometric
method.[36] A Carl Zeiss Abbe Refractometer
(Type G) was applied for the analysis of refractive indexes. The accuracy
of the refractometer was 0.0001 at 293.2 K, according to the manufacturer.
Literature and experimental refractive indexes and Antoine constants
of the used chemicals are listed in Table . As it can be seen, the experimental refractive
indexes show good agreement with the literature data.
Table 8
Experimental and Literature Refractive Indexes (nD) at 293.2 K of Pure Compounds Used and Antoine Constants
property
ethanol
acetal
acetaldehyde
nD present
work
1.3611
1.3805
1.3308
nD literature
1.3613
1.3819
1.3316
nD reference
(37)
(38)
(39)
Antoine constantsa
A
5.24677
4.7498
3.68639
B
1598.673
1573.964
822.894
C
–46.424
–43.681
–69.899
T-min [K]
292.77
250
293.4
T-max [K]
366.63
375.3
377.5
reference
(40)
(41)
(42,43)
Antoine constants (bar, K) of ethanol, acetal,
and acetaldehyde were calculated by NIST from literature data.
Antoine constants (bar, K) of ethanol, acetal,
and acetaldehyde were calculated by NIST from literature data.Table contains the main compounds of the raw anhydrous
ethanol sample.
Table 9
Components of the Anhydrous Ethanol
Sample with the Boiling Point of Pure Component at 101 kPa
substance
ppm-v/v
wt %
pure component boiling point [°C]
ethanol
-
99.79
78.4
methanol
64
8.05 × 10–3
64.7
acetal
994
1.26 × 10–1
102.5
ethyl
acetate
41
5.20 × 10–3
77.1
acetaldehyde
278
3.53 × 10–2
20.2
diethyl ether
38
4.79 × 10–3
34.6
isobutanol
211
2.67 × 10–2
108.0
The main purification requirements for the
composition of pharmacopeial quality anhydrous alcohol are the following:
200 ppm in methanol, 10 ppm in acetaldehyde + acetal, 2 ppm in benzene,
and 300 ppm in all pollutants.[13] It can
be seen that more types of substances are above the prescribed composition.Distillation can be performed in discontinuous (batch) and continuous
mode.[44−46] In the present study, the amount to be processed
was relatively large (1000 kg/h) so continuous operation was recommended.
The actual task was to remove polluting compounds and therefore to
achieve a high-quality product. According to basic unit operation
knowledge, a distillation column with a stripping section should be
applied.[47] Therefore, considering the data
in Table , it can
be estimated in advance that the polluting compounds’ removal
results mainly in the distillate product and the bottom product contains
the pharmacopeial anhydrous alcohol.At first, flowsheeting
simulations were carried out with the ChemCAD 7.1.5 program to get
a comprehensive overview about the system and find promising alternatives.
The optimal reflux ratio (thereby the distillate and bottom flow rates),
column pressure, number of theoretical stages, feed stage, and heating
and cooling requirements were also determined with the dynamic programming
optimization method.[48−50] The investigated ethanol sample is considered highly
nonideal, because it has more azeotropic binary pairs. As an equilibrium
model for the calculation of highly nonideal vapor–liquid equilibria,
the UNIQUAC method was applied.[51−54] Considering the vapor–liquid equilibria, that
is, our modeling results obtained with ChemCAD, the separation of
the ethanol sample can be performed significantly better if vacuum
distillation is applied. Figure shows the flowsheet used for modeling the distillation.
Figure 7
Flowsheet
of anhydrous alcohol purification.
Flowsheet
of anhydrous alcohol purification.Figure summarizes
the optimization process of anhydrous alcohol purification.
Figure 8
Flowchart of
the optimization process of anhydrous alcohol purification.
Flowchart of
the optimization process of anhydrous alcohol purification.The modeling results were tested in a laboratory,
under experimental conditions. The main parameters of the experimental
column were the following: 1.5 m high and internal diameters of 25
mm (rectifying section) and 20 mm (stripping section) with Sulzer
EX structured packing (see Figure ). The column had 40 theoretical stages, according
to the measurement carried out with an ethanol–water binary
mixture. The feed was preheated and it was pumped into the eighth
stage of the column. The column heating was controlled with a heating
basket (300 W). The vacuum was maintained with a VACUUBRAND PC2003
VARIO vacuum pump and kept at 10 kPa. Another vacuum pump was also
used for bottom product removal and kept at 9 kPa. The distillation
apparatus was collected in three traps connected in series and cooled
with liquidnitrogen to prevent the evaporation and loss of the distillate
product. The reflux ratio was maintained with a Bertolt reflux controller.
Figure 9
Laboratory
demonstrative column for alcohol purification.
Laboratory
demonstrative column for alcohol purification.As a startup procedure of the experiments, batch distillation was
first carried out to obtain a relatively pure liquid satisfying the
purity prescriptions in the reboiler.[13] Afterward, continuous mode was used until a steady-state (constant
output flows and temperatures) operation was achieved.The content
of the feed (F), distillate(D),
bottom product (W), and traps were measured with
a Shimadzu GC2010Plus + AOC-20 autosampler gas chromatograph with
a ID-BP1 (60 m × 0.32 mm, 1.0 μm) column using helium as
the carrier gas. The column temperature was kept at constant 60 °C
while the injector was thermostated to 250 °C and MS ion source
temperature was set to 250 °C. Pressure of the helium carrier
gas (with 5.0 purity) was kept at 90 kPa. The results were the average
of three analyses in the analytical method.[55]