An experimental study of bioethanol adsorption on natural Iranian clinoptilolite was carried out. Dynamic breakthrough curves were used to investigate the best adsorption conditions in bioethanol liquid phase. A laboratory setup was designed and fabricated for this purpose. In order to find the best operating conditions, the effect of liquid pressure, temperature and flow rate on breakthrough curves and consequently, maximum ethanol uptake by adsorbent were studied. The effects of different variables on final bioethanol concentration were investigated using Response Surface Methodology (RSM). The results showed that by working at optimum condition, feed with 96% (v/v) initial ethanol concentration could be purified up to 99.9% (v/v). In addition, the process was modeled using Box–Behnken model and optimum operational conditions to reach 99.9% for final ethanol concentration were found equal to 10.7 C, 4.9 bar and 8 mL/min for liquid temperature, pressure and flow rate, respectively. Therefore, the selected natural Iranian clinoptilolite was found to be a promising adsorbent material for bioethanol dehydration process.
Trang 1ORIGINAL ARTICLE
Experimental investigation of bioethanol liquid
phase dehydration using natural clinoptilolite
a
Biosystem Engineering Department, Tarbiat Modares University, Tehran 14115-336, Iran
bChemical Engineering Department, Tarbiat Modares University, Tehran 14115-143, Iran
c
Department of Chemical and Biomolecular Engineering, National University of Singapore (NUS), Singapore 117585, Singapore1
d
Department of Chemical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran 15875-4413, Iran
G R A P H I C A L A B S T R A C T
A R T I C L E I N F O
Article history:
Received 18 January 2016
Received in revised form 25 February
2016
A B S T R A C T
An experimental study of bioethanol adsorption on natural Iranian clinoptilolite was carried out Dynamic breakthrough curves were used to investigate the best adsorption conditions in bioethanol liquid phase A laboratory setup was designed and fabricated for this purpose In order to find the best operating conditions, the effect of liquid pressure, temperature and flow
* Corresponding author Tel.: +98 2148292308.
E-mail address: ghobadib@modares.ac.ir (B Ghobadian).
1 Current affiliation.
Peer review under responsibility of Cairo University.
Production and hosting by Elsevier
Cairo University Journal of Advanced Research
http://dx.doi.org/10.1016/j.jare.2016.02.009
2090-1232 Ó 2016 Production and hosting by Elsevier B.V on behalf of Cairo University.
Trang 2Accepted 29 February 2016
Available online 5 March 2016
Keywords:
Adsorption
Clinoptilolite
Dehydration
Bioethanol
Isotherm
Box–Behnken model
rate on breakthrough curves and consequently, maximum ethanol uptake by adsorbent were studied The effects of different variables on final bioethanol concentration were investigated using Response Surface Methodology (RSM) The results showed that by working at optimum condition, feed with 96% (v/v) initial ethanol concentration could be purified up to 99.9% (v/v).
In addition, the process was modeled using Box–Behnken model and optimum operational con-ditions to reach 99.9% for final ethanol concentration were found equal to 10.7 °C, 4.9 bar and
8 mL/min for liquid temperature, pressure and flow rate, respectively Therefore, the selected natural Iranian clinoptilolite was found to be a promising adsorbent material for bioethanol dehydration process.
Ó 2016 Production and hosting by Elsevier B.V on behalf of Cairo University.
Introduction
Fuel grade bioethanol is one of the widely used alternative for
fossil fuels or gasoline additive [1,2] In bioethanol–gasoline
mixture, the presence of even a very small amount of water
in bioethanol is unfavorable and leads to a two phase mixture
[3–5] The bioethanol dehydration is a process to eliminate
water from bioethanol–water mixture up to 99.6% (V/V)
There are several methods including azeotropic distillation
[6–8], extractive distillation [9,10], pervaporation with
mem-branes [11–13] and adsorption using adsorbents [3,5,14–18],
that are being used for water elimination to overcome the
ethanol–gasoline mixing problem The azeotropic distillation and extractive distillation are too expensive process[9,19] Lit-eratures show that extractive distillation is more complex due
to the design and process application and articles on energy consumption and cost, during recent years confirm that this method has high performance but needs further studies on energy consumption [20] Conventional extractive distillation
is energy consumption process because of using reboilers and condensors Different refine processes were used to improve conventional extractive distillation such as heat-pump-assisted extractive distillation for bioethanol purification[21], Ethanol dehydration via azeotropic distillation with gasoline fraction mixtures as entrainers [20]and Control comparison
of conventional and thermally coupled ternary extractive dis-tillation processes [22] In addition, although the pervapora-tion is a new generapervapora-tion in separapervapora-tion technology, it has industrial installation limitations The adsorption by selective porous adsorbents is a common high performance method in bioethanol dehydration Many studies have focused on differ-ent types of water adsorbdiffer-ents including biobased adsorbdiffer-ents namely natural corncobs, natural and activated palm stone and oak [3,23,24], Calcium Carbide [25], calcium chloride and lime[26], silica gel[27], cellulose and lignocellulose based (bleached wood pulp, oak sawdust and kenaf core) [14,28], Aluminas and c-alumina [29], Starch-Based Adsorbents [5,24,30]and different types of molecular sieves especially the zeolites [16,31–34] Finding appropriate, effective and cheap adsorbent material is a way to reduce the final bioethanol pro-duction costs The zeolites with porous structures and selectiv-ity properties can let water molecules to penetrate inside pore volumes of hydrophilic adsorbents and separate ethanol–water mixture The natural zeolites and clays such as clinoptilolite [17,35–37], chabazite and phillipsite[38]are plentiful material
in nature with hydrophilic properties suitable for ethanol–wa-ter separation For instance, it has been shown that the clinop-tilolite water adsorption capacity is more than 50% of water adsorption capacity of 3A zeolite [39] In various previous studies, the parameters influencing ethanol–water separation such as temperature[39], system pressure[40], adsorption heat [41]and particle size [39]have been investigated As a lot of industrial separation processes based on adsorption mecha-nism are carried out in liquid phase [42], using mesoporous adsorbents such as clinoptilolite is highly recommended to adsorb the big molecules in liquid phase[43] Although there are some studies on using clinoptilolite as a adsorbent for purification of ethanol in liquid phase [35,37], the effect of operational conditions has not well understood So, we aim
to use of Iranian clinoptilolite in both batch and continuous
Clinop-tilolite sample at T = 77 K (b) Pore size distribution based on
BJH method
Trang 3adsorption processes to separate the water contents from
water/ethanol mixture which is usual product of biofuel
pro-duction In this research work, the Iranian natural
clinoptilo-lite is presented as a cheap water adsorbent media to
separate the water from hydrous bioethanol in a fixed bed
setup Furthermore, the optimum operational conditions have
been found both experimentally and theoretically
Material and methods
The deionised water and ethanol were purchased from
Bide-stan Co (Qazvin-Iran) The natural clinoptilolite used in this
research work was purchased from Afrazand Co (East
Semnan–Iran) The chemical analysis showed the high content
of K+and Na+ The zeolite was approximately 65 wt.% pure
in clinoptilolite The composition of the material based on
X-ray fluorescence (XRF) (Model: Philips PW 2404) analysis
was 71.159 wt.% SiO2, 11.335 wt.% Al2O3, 0.936 wt.% Fe2O3,
0.807 wt.% CaO, 0.478 wt.% MgO, 3.064 wt.% Na2O,
4.48 wt.% K2O, 0.164 wt.% TiO2 and 0.847 wt.% SO3 Loss
of ignition (LOI) is 6.23 The bulk density was calculated and
it was found 820 kg m3(1–2 mm particle size) The silica
mod-ulus (molar ratio) of the sample wasg = SiO2/Al2O3= 6.26
The pore structure and surface area of Iranian clinoptilolite
were characterized by N2adsorption–desorption isotherm at
77 K which has been illustrated in Fig 1a Nitrogen
adsorp-tion was carried out using Belsorp mini II (Bel Japan) Before
the experiments, the sample was dried to be degassed at 25°C for 5 h and vacuum The adsorption isotherm has hysteresis loop along with a relative pressure from 0.4 to 0.99 This iso-therm is type I, which is typical property for mesoporous mate-rials[44] As it has been presented inTable 1, the BET surface area (aBET), total pore volume (Vt), (from the last point of iso-therm at a relative pressure of 0.99), micropore volume (Vm) and mean pore size have been calculated using Brunauer– Emmett–Teller (BET) method The Barrett–Joyner–Halenda (BJH) pore size distribution of the Iranian clinoptilolite sample was calculated based on the adsorption data As it can be seen
inFig 1b, the majority of pores have the radius size of less than 10 nm with mean pore diameter of 26.47 nm based on BJH method which has good agreement with what has been calculated from BET method[45](SeeTable 1)
A stainless steel column with 4 cm diameter and 55 cm height was designed and fabricated to regenerate samples using high temperature and vacuum pressure Regeneration column consists of three heating elements with a heating rate of approximately 20°C/min and indicators Three thermocouples provide the required feedback for an on/off temperature con-trolling system Vacuum gage is used for indicating the column vacuum pressure A cooling setup – condensers and cooling water circulator – collects regeneration liquid Afterward, regenerated zeolite is cooled to ambient temperature in desic-cator Regeneration operation is completed in 0.6 bar vacuum pressure and 300°C for 50 min
Static adsorption isotherms (batch)
Water removal from water/ethanol mixture by natural clinop-tilolite in batch condition was examined for different initial concentrations of water The experiments were carried out at ambient temperature (20°C) and static conditions in a thermo-stated laboratory scale adsorption vessel, with an
a BET (m 2 /g) V m (cm 3 /g) V t (cm 3 /g) D mean (nm) a BET (m 2 /g) V m (cm 3 /g) D mean (nm) 14.394 3.3071 0.094766 26.334 15.4 0.094327 26.334
bioethanol dehydration (1 Initial Container, 2 Liquid Pump, 3
Adsorption Column, 4 Cooling Circulator, 5 Temperature
Sensor, 6 Pressure Sensor, 7 Flowmeter and 8 Final Container.)
water adsorption
Trang 4initial liquid weight of 100 g The ethanol–water mixture at
dif-ferent concentrations was applied as adsorptive and 60 g
zeo-lite and the contact time of 24 h was selected for
experiments The water concentration in feed was varied
between 50 and 363 kg m3(kg of water in feed to feed
vol-ume) The Langmuir and Freundlich isotherm models were
used for description of the adsorption process (Eqs.(1) and
(2)):
qe¼kl Ce qm
where qe is the amount of solute adsorbed per unit weight of
solid (kmol/kg), Ce is equilibrium concentration of water
remaining in solution (kg/m3), qm is maximum adsorption
capacity (kmol/kg) and kfand klare Freundlich and Langmuir
constants (m3/kg), respectively 1/n is a measure of intensity of
adsorption The higher the 1/n value, the more favorable is the
adsorption qeis calculated from equation as follows (Eq.(3)):
qeðkmol=kgÞ¼C0Ce
Czeo
ð3Þ Because of using Temperature Swing Adsorption process
(TSA) for adsorbents regeneration (high temperature and
low pressure), it was necessary to find temperature dependent
isotherm An Extended Langmuir isotherm was used to find
adsorption dependence with temperature For this, qeand Ce
values in different temperature between 10 and 70°C were
found and temperature dependent equation was expressed as
follows:
qe¼ k1k2exp k3
T
Ce
1þ k2exp k3
T
Ce
ð4Þ
where k1is qm(kmol/kg), k2is kel(m3/kg) and k3isDH/R (°K)
DH and R are enthalpy changes and gas constant, respectively Dynamic adsorption (continuous)
An apparatus with packed bed adsorption column was designed for dynamic standard experiments The schematic
of the designed apparatus is shown inScheme 1 The column was designed based on the Yamamoto’s set-up dimensions for liquid phase adsorption [16] The retention time in the
Temperature (K) Uptake (kmol/kg) Langmuir Freundlich
k l (m 3 /kg) q m (kmol/kg) R 2 k f (kmol/kg) 1/n R 2
283 0.00746 0.0179 0.00746 0.986 0.00066 0.412 0.973
298 0.00701 0.0156 0.00701 0.986 0.00051 0.442 0.984
313 0.00689 0.0125 0.00689 0.991 0.00041 0.47 0.987
328 0.00662 0.0113 0.00662 0.971 0.00033 0.498 0.979
343 0.00628 0.0106 0.00629 0.974 0.000264 0.529 0.992
temperatures
(b) in different temperatures
Trang 5set-up was determined to be 21.2 min and for this research
work this value was assumed as 25 min According to the
max-imum flow rate of 14 mL/min, a stainless steel column with
4 cm diameter and 40 cm height was designed and fabricated
Its dimension ensured good flow distribution since the bed
internal diameter was at least 10 times as much as the particle
size and its length was at least 100 times as much as the particle size[40] A jacket of cooling water with 4 cm thickness was connected to circulator and surrounded the main column to fulfill the isotherm conditions Two pressure and temperature sensors were located on both inlet and outlet of the column for monitoring pressure drop and changes in system tempera-ture A copper coil was used in initial bioethanol container to control the initial bioethanol temperature.Scheme 1illustrates the experimental setup
Two pressure sensors in bottom and top of the column show the pressure and pressure drop Using circulator and temperature sensors, initial and final bioethanol temperatures were controlled The bioethanol concentration in initial tainer was constant and it was 96% The final bioethanol con-centration leaves the top valve and is shown by the Portable Density Meter of Anton DMA 35 A water flow meter (cali-brated for ethanol v/v concentration) was used for adjustment
of bioethanol flow rate and it is one of the main experimental parameters Before carrying out the experiments, the adsor-bent samples were treated by thermal regeneration for elimina-tion of water from the adsorbent pores The procedure was completed by putting samples in furnace for 2 h at 300°C and then it was cooled to ambient temperature in desiccator Natural zeolites with the HEU (Heulandite) framework are divided into two distinct classes based on Si/Al ratio Those with Si/Al of less than 4 are known as heulandite and those with Si/Al greater than 4 are known as clinoptilolite or silica-rich heulandite The key difference in these materials is those with Si/Al of less than 4 are not thermally stable to cal-cination above 350°C [46] and High silica Clinoptilolite is thermally stable to temperatures in excess of 500°C[47] The initial tank was filled with 96% (v/v) ethanol–water mixture The bioethanol entered from the bottom of the col-umn which was packed with a mass of natural zeolite When the mixture leaved the column, the pressure, temperature and flow rate were controlled The data collected and concentra-tion were obtained every minute by Density Meter All of the experiments were organized by RSM to find the optimal operational conditions This was done by Design-Expert 7 software
Results and discussion Static isotherm models
To determine the model to be used to describe the adsorption for an adsorbent–adsorbate isotherm experiments were carried out Initial concentration was varied from 50 to 363 kg m3for all the experiments at different temperature Raman spec-troscopy test was used to determine water–ethanol adsorption
constant T = 288 K and P = 3 bar, (b) different pressures and
constant F = 14 mL/min T = 293 K, and (c) different
tempera-tures and constant F = 10 mL/min and P = 1 bar
Coded factors Corresponding parameters Coded levels
Corresponding values
Trang 6on natural clinoptilolite The Raman spectra were collected at
the Spectroscopy Laboratory, Atomic and Molecular Group,
Physics Department, Tarbiat Modares University by using a
Thermo Nicolet Almega dispersive micro-Raman scattering
spectrometer Results showed that the main peak in water
Raman spectrum is for stretching O–H bond around 3000–
3400 cm1and it is obvious inFig 2that there is a strong peak
in this area after the treatment of zeolite by mixture of water and ethanol; hence, it could be concluded that only water is adsorbed and the amount of adsorbed ethanol is negligible
Pattern A (pressure) B (flow) C (temperature) Final concentration
response, and (c) effects of B and A on response
Trang 7By applying the linearization of both Langmuir and
Fre-undlich models, it has been indicated that data could be well
described by both models (Figs S1–S5 in Supplementary
infor-mation data) Linear form of experimental data for Langmuir
and Freundlich isotherms at different temperatures was shown
in Supplementary details (Figs S6–S15).Table 2shows
Lang-muir and Freundlich isotherm parameters in different
temper-atures varied between 283 and 343 K It is obvious that
Langmuir isotherm has a better correlation than Freundlich
at low temperatures near ambient Fortunately, working at
low temperature is desirable for industrial adsorption process
and based on data presented in Table 2, it is obvious that
decreasing in temperature causes increase in final uptake
Hence, Extended Langmuir isotherm was selected as a temper-ature dependent isotherm equation to describe the tempertemper-ature behavior in adsorption process that could also be used for any future process simulation or scale-up and design the industrial plant Eq (5) shows the Extended Langmuir model that describes the static data.Fig 3shows the experimental data and Extended Langmuir model at different temperatures Fur-thermore,Fig 4a and b shows the amount of uptake as a func-tion of temperature and initial concentrafunc-tion for both experimental data and Extended Langmuir model, respectively that are well matched together
qe¼0:0076 0:0001244exp 1386:5T
Ce
1þ 0:0001244exp 1386:5
T
Breakthrough curves based on dynamic study (Continuous)
In order to understand the effect of parameters including flow rate, pressure and temperature on the breakthrough curves and finding the optimum operating condition, the variation
of each parameter was studied The breakthrough curves in Fig 5show the effects of pressure, temperature and flow rate
on breakthrough point.Fig 5a shows that most of the mass transfer and adsorption takes place at the moment that the fluid first comes in contact with the inlet of the bed and by increasing the flow rate, there is a decrease in time required for saturation of adsorbent and breakthrough point shifts to the right side by increasing the flow rate Increasing pressure from 1 to 5 bar sat defined temperature (T = 293 K) also enhances the saturation time of adsorbent while there is a slight increase in adsorption capacity (Fig 5b) Reducing the temperature changes breakthrough point and increases
Source Sum of squares df Mean square F value P-value Prob > F
A-pressure 1.45 1 1.45 85.50 <0.0001
B-flow rate 0.080 1 0.080 4.73 0.0486
C-temperature 0.32 1 0.32 18.93 0.0008
Residual 0.22 13 0.017
Lack of fit 0.20 9 0.022 4.44 0.0826
Source Sum of squares df Mean square F value P-value Prob > F
A-pressure 1.45 1 1.45 119.00 <0.0001
B-flow rate 0.080 1 0.080 6.59 0.0372
C-temperature 0.32 1 0.32 26.35 0.0013
B2 2.632E 3 1 2.632E 3 0.22 0.6557
C2 2.632E 3 1 2.632E 3 0.22 0.6557
Residual 0.085 7 0.012
Lack of fit 0.065 3 0.022 4.33 0.0953
Trang 8adsorption, the breakthrough point shifts to the right side and
the maximum adsorption is obtained
To find the total adsorption capacity (q) from
break-through curve, the area above the curve divided into the total
area (above and under the curve) results in adsorption
percent-age[16] Hence, according to Eq.(6), total adsorption capacity
could be calculated from feed loading and adsorption
percentage
q¼Fqf
w C0
Z tb
0
1Ct
C0
The total adsorption capacity q inFig 5a for flow rates 6,
10 and 14 mL/min (in 3 bar pressure and 288 K) was obtained
1.75, 1.52 and 1.26 mol/kgzeo, respectively Also inFig 5b, for
column pressures 1, 3 and 5 bar (14 mL/min and 293 K), q
val-ues were calculated 1.5, 1.74 and 1.97 mol/kgzeo respectively
According to Fig 5c, for temperatures 283, 288 and 293 K
and 10 mL/min flow rate and 1 bar pressure, q values obtained
were 1.13, 1.31 and 1.44 mol/kgzeo, respectively
The response surface methodology
The response surface methodology (RSM) is a collection of
statistical and mathematical techniques for obtaining empirical
models Understanding the effect of parameters and
optimiza-tion is the common advantage of the RSM applicaoptimiza-tion.Table 3
shows the coded level for each parameter For the three parameters, the Box–Behnken Method was used In this method, each factor or independent variable is placed at one
of the three equally spaced values, usually coded as 1, 0 and +1 In this research work, the temperature, pressure and flow rate are independent variables and the final bioetha-nol concentration is the responses.Table 4shows the experi-mental design used in this study
The two linear and Quadratic models were used for the con-centration modeling in Box–Behnken method.Fig 6illustrates the different variables to response diagrams in linear model for concentration response An analysis of variance for linear model is shown inTable 5 The Model F-value of 36.39 implies the model significant The values of Prob > F less than 0.05 indicate that the model terms are significant and the parameter has a significant effect on the response In this case, A (pres-sure), B (flowrate) and C (temperature) are significant model terms The values greater than 0.10 indicate that the model terms are not significant The prediction expression is given
as follows:
Concentration¼ 99:43 þ 0:2125 P 0:025 F 0:04 T
ð7Þ According to Fig 6 increasing the pressure causes an increase in maximum final bioethanol concentration For the low temperatures, the effect of pressure on maximum
response and (c) effects of B and A on response
Trang 9bioethanol final concentration was intensified It can be seen
that there is a positive relation between the pressure and
max-imum bioethanol final concentration for a given temperature
Decreasing the temperature causes the maximum bioethanol
concentration to increase Reducing the temperature in liquid
affects the adsorbent surface and makes water molecules enter
the adsorbent pores The temperature control in liquid phase
adsorption process is more effective and it is simpler than
the other two operational parameters and the obtained results
show that the temperature has more influence on bioethanol
final concentration The flow rate decrease causes an increase
in maximum bioethanol concentration Reducing the flow rate
makes more retention time and hence creates a better contact
between the adsorbent and solute
Fig 7 shows the relationship between the predicted and
actual data line The R2value of 0.89 indicated that the actual
and the predicted data had a relatively good correlation in
lin-ear model
Analysis of variance for quadratic model is shown in
Table 6 The Model F-value of 18.11 implies that the model
is significant The values of Prob > F less than 0.05 indicate
that the model terms are significant and have a significant
effect on the response In this case, A (temperature), B
(flow-rate) and C (Temperature) are significant model terms The
values greater than 0.1 indicate that the model terms are not
significant The prediction expression in quadratic model is
given as follows (Eq.(8)):
Conc¼ 99:637 þ 0:3875 P 0:050 F 0:0750 T
0:00625 PF þ 0:005 PT þ 0:005 FT
0:03125P2 0:00015F2 0:001T2 ð8Þ
Fig 8 shows the independent variables to response
dia-grams in quadratic model Fig S16 illustrates the relationship
between the predicted and actual data line The R2 value of
0.92 shows a relatively good correlation between predicted
and actual data The optimization as a point of view of
con-centration shows that at 10.7°C liquid temperature, 4.9 bar
pressure and 8 mL/min liquid flow rate, the best response
was 99.9% bioethanol final concentrations
Conclusions
In this research work, Iranian natural clinoptilolite was used to
dehydrate hydrous ethanol Results showed that in optimum
operating conditions, bioethanol final concentration can reach
to 99.9% and above Static and dynamic studies were done and
adsorption isotherms were obtained and experimental data
were well described by Extended-Langmuir isotherm The
effects of operating parameters such as temperature, pressure
and flow rate were investigated on final ethanol concentration
and the adsorption process was optimized In Box–Behnken
analysis, the linear and quadratic models could be successfully
applied for description of dynamic process Results showed
that the selected natural clinoptilolite could be used as a
favor-able adsorbent in bioethanol drying without any pretreatment
processes
Conflict of Interests
The authors have declared no conflict of interests
Compliance with Ethics Requirements This article does not contain any studies with human or animal subjects
Acknowledgment The authors express their sincere thanks to Iranian Fuel Con-servation Company (IFCO) for the support during the course
of this research work
Appendix A Supplementary material
Supplementary data associated with this article can be found,
in the online version, athttp://dx.doi.org/10.1016/j.jare.2016 02.009
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