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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.
Journal of Advanced Research (2016) 7, 435–444 Cairo University Journal of Advanced Research ORIGINAL ARTICLE Experimental investigation of bioethanol liquid phase dehydration using natural clinoptilolite Samira Karimi a, Barat Ghobadian a,*, Mohammad-Reza Omidkhah b, Jafar Towfighi b, Mohammad Tavakkoli Yaraki c,d a Biosystem Engineering Department, Tarbiat Modares University, Tehran 14115-336, Iran Chemical 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 b 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) Current affiliation Peer review under responsibility of Cairo University Production and hosting by Elsevier 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 436 Accepted 29 February 2016 Available online March 2016 Keywords: Adsorption Clinoptilolite Dehydration Bioethanol Isotherm Box–Behnken model S Karimi et al 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 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 membranes [11–13] and adsorption using adsorbents [3,5,14–18], that are being used for water elimination to overcome the Fig (a) Adsorption/desorption of N2 gas on Iranian Clinoptilolite sample at T = 77 K (b) Pore size distribution based on BJH method ethanol–gasoline mixing problem The azeotropic distillation and extractive distillation are too expensive process [9,19] Literatures 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-pumpassisted 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 distillation processes [22] In addition, although the pervaporation is a new generation in separation 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 different types of water adsorbents including biobased adsorbents 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 production costs The zeolites with porous structures and selectivity 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–water separation For instance, it has been shown that the clinoptilolite 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 mechanism 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 Investigation of bioethanol dehydration using clinoptilolite Table 437 Porosity characterization of Iranian clinoptilolite BET method BJH method aBET (m2/g) Vm (cm3/g) Vt (cm3/g) Dmean (nm) aBET (m2/g) Vm (cm3/g) Dmean (nm) 14.394 3.3071 0.094766 26.334 15.4 0.094327 26.334 adsorption processes to separate the water contents from water/ethanol mixture which is usual product of biofuel production In this research work, the Iranian natural clinoptilolite 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 Bidestan 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 mÀ3 (1–2 mm particle size) The silica modulus (molar ratio) of the sample was g = SiO2/Al2O3 = 6.26 The pore structure and surface area of Iranian clinoptilolite were characterized by N2 adsorption–desorption isotherm at 77 K which has been illustrated in Fig 1a Nitrogen adsorption was carried out using Belsorp mini II (Bel Japan) Before the experiments, the sample was dried to be degassed at 25 °C for h and vacuum The adsorption isotherm has hysteresis loop along with a relative pressure from 0.4 to 0.99 This isotherm is type I, which is typical property for mesoporous materials [44] As it has been presented in Table 1, the BET surface area (aBET), total pore volume (Vt), (from the last point of isotherm 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 in Fig 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] (See Table 1) A stainless steel column with 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 controlling 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 desiccator Regeneration operation is completed in 0.6 bar vacuum pressure and 300 °C for 50 Static adsorption isotherms (batch) Water removal from water/ethanol mixture by natural clinoptilolite 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 Scheme Schematic of experimental apparatus used for bioethanol dehydration (1 Initial Container, Liquid Pump, Adsorption Column, Cooling Circulator, Temperature Sensor, Pressure Sensor, Flowmeter and Final Container.) Fig Raman spectrum of natural clinoptilolite before and after water adsorption 438 S Karimi et al Table Langmuir and Freundlich parameters in different temperatures Temperature (K) 283 298 313 328 343 Uptake (kmol/kg) 0.00746 0.00701 0.00689 0.00662 0.00628 Fig The temperatures Extended Langmuir Langmuir Freundlich kl (m3/kg) qm (kmol/kg) R2 kf (kmol/kg) 1/n R2 0.0179 0.0156 0.0125 0.0113 0.0106 0.00746 0.00701 0.00689 0.00662 0.00629 0.986 0.986 0.991 0.971 0.974 0.00066 0.00051 0.00041 0.00033 0.000264 0.412 0.442 0.47 0.498 0.529 0.973 0.984 0.987 0.979 0.992 isotherms in different initial liquid weight of 100 g The ethanol–water mixture at different concentrations was applied as adsorptive and 60 g zeolite and the contact time of 24 h was selected for experiments The water concentration in feed was varied between 50 and 363 kg mÀ3 (kg of water in feed to feed volume) The Langmuir and Freundlich isotherm models were used for description of the adsorption process (Eqs (1) and (2)): qe ẳ kl Ce qm ỵ kl Ce qe ẳ kf C1=n e 1ị 2ị 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 kf and kl are 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 qe is calculated from equation as follows (Eq (3)): qekmol=kgị ẳ C0À Ce 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, qe and Ce values in different temperature between 10 and 70 °C were found and temperature dependent equation was expressed as follows: Fig Experimental data (a) and Extended Langmuir isotherms (b) in different temperatures qe ¼ Àk3 Ce T ỵ k2 exp kT3 Ce k1 k2 exp ð4Þ where k1 is qm (kmol/kg), k2 is kel (m3/kg) and k3 is DH/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 in Scheme The column was designed based on the Yamamoto’s set-up dimensions for liquid phase adsorption [16] The retention time in the Investigation of bioethanol dehydration using clinoptilolite Fig Breakthrough curves at (a) different flow rates and constant T = 288 K and P = bar, (b) different pressures and constant F = 14 mL/min T = 293 K, and (c) different temperatures and constant F = 10 mL/min and P = bar 439 size and its length was at least 100 times as much as the particle size [40] A jacket of cooling water with 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 temperature A copper coil was used in initial bioethanol container to control the initial bioethanol temperature Scheme illustrates 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 container was constant and it was 96% The final bioethanol concentration leaves the top valve and is shown by the Portable Density Meter of Anton DMA 35 A water flow meter (calibrated 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 adsorbent samples were treated by thermal regeneration for elimination of water from the adsorbent pores The procedure was completed by putting samples in furnace for 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 are known as heulandite and those with Si/Al greater than are known as clinoptilolite or silica-rich heulandite The key difference in these materials is those with Si/Al of less than are not thermally stable to calcination 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 column 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 concentration 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 software Results and discussion Static isotherm models set-up was determined to be 21.2 and for this research work this value was assumed as 25 According to the maximum flow rate of 14 mL/min, a stainless steel column with 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 Table The three level factors used in the Box–Behnken design Coded factors A B C 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 mÀ3 for all the experiments at different temperature Raman spectroscopy test was used to determine water–ethanol adsorption Corresponding parameters Pressure (bar) Flow rate (mL/min) Temperature (°C) Coded levels À1 Corresponding values 1 10 10 15 14 20 440 S Karimi et al Table The experimental design used in this research work Pattern A (pressure) B (flow) C (temperature) Final concentration 000 000 000 ++0 +À0 À0+ À+0 0++ 000 ÀÀ0 +0À 0ÀÀ À0À 0À+ 000 +0+ 0+À 3 5 1 3 3 10 10 10 14 10 14 14 10 10 10 10 10 14 15 15 15 15 15 20 15 20 15 15 10 10 10 20 15 20 10 99.3 99.2 99.3 99.3 99.7 98.4 98.7 99.1 99.4 98.9 99.9 99.6 98.9 99.0 99.3 99.5 99.3 Fig The different variables to response diagrams in linear model, (a) effects of A and C on response, (b) effects of B and C on response, and (c) effects of B and A on response on 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 cmÀ1 and it is obvious in Fig that 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 Investigation of bioethanol dehydration using clinoptilolite Table 441 Analysis of concentration variance for ANOVA table by linear model Source Sum of squares df Mean square F value P-value Prob > F Model A-pressure B-flow rate C-temperature Residual Lack of fit Error 1.84 1.45 0.080 0.32 0.22 0.20 0.020 1 13 0.61 1.45 0.080 0.32 0.017 0.022 5.0EÀ3 36.39 85.50 4.73 18.93 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 (flowrate) 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)): Conc ẳ 99:637 ỵ 0:3875 P 0:050 Â F À 0:0750 Â T À 0:00625 Â PF ỵ 0:005 PT ỵ 0:005 FT 0:03125P2 À 0:00015F2 À 0:001T2 ð8Þ Fig shows the independent variables to response diagrams 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 concentration shows that at 10.7 °C liquid temperature, 4.9 bar pressure and 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 favorable adsorbent in bioethanol drying without any pretreatment processes Conflict of Interests The authors have declared no conflict of interests 443 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 Conservation 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, at http://dx.doi.org/10.1016/j.jare.2016 02.009 References [1] Costa RC, Sodre´ JR Hydrous ethanol vs gasoline–ethanol blend: engine performance and emissions Fuel 2010;89 (2):287–93 [2] Yuăksel F, Yuăksel B The use of ethanolgasoline blend as a fuel in an SI engine Renewable Energy 2004;29(7):1181–91 [3] 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