Modeling of a Biobutanol Adsorption Process for Designing an

Article pubs.acs.org/IECR

Modeling of a Biobutanol Adsorption Process for Designing an Extractive Fermentor Moon-Ho Eom,†,‡ Woohyun Kim,§,† Julia Lee,‡ Jung-Hee Cho,‡ Doyoung Seung,‡ Sunwon Park,*,† and Jay H. Lee*,† †

Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea ‡ Biofuel & Biochemical Team, R&D Center, GS Caltex Corporation, 104-4 Munji-dong, Yusung-gu, Daejeon 305-380, Republic of Korea S Supporting Information *

ABSTRACT: For curbing the severe inhibition and toxicity of 1-butanol in a fermentor, which stand as one of the major hurdles on the way to commercialization of biobutanol production processes, an extractive fermentation process that can remove metabolites during the ferementation can be an effective solution. Among various separation techniques, adsorption using poly(styrene-co-divinylbenzene) adsorbent resin is an effective and energy-efficient technique that holds much promise. In this paper, we have investigated the adsorption-and-desorption characteristics of the fermentation metabolites to aid the design of a new fermentation process equipped with an in situ or ex-situ butanol recovery capability. Specifically, the Langmuir equation and Ideal Adsorption Solution theory (IAST) have been used for developing an adsorption isotherm model, based on which a kinetic model of the adsorption process is developed. For the parameter estimation of the adsorption model, experiments have been carried out with a batch type slurry adsorption process processing a multiple-component mixture containing acetone, ethanol, 1butanol, acetic acid, and butyric acid. It is subsequently confirmed that the adsorption model developed with data from the experiments using the model broth adsorption can accurately predict the adsorption behavior of the actual fermentation broth. To ensure the practical applicability of the adsorption process, desorption experiments of the adsorbent resin have also been performed. It is found that approximately 95% of the adsorbates on the adsorbent can be recovered using 140 °C steam with the steam-to-adsorbent mass ratio of 1. This study on the adsorption-and-desorption characteristics is expected to contribute to designing a large-scale extractive fermentor for biobutanol production.

1. INTRODUCTION Recently, rising oil price and serious concerns over environmental problems, such as the global warming caused by the CO2 emission, have led to a widespread interest in biofuel. In particular, 1-butanol has received much attention, not only as a fuel but also as a chemical feedstock. 1-Butanol is considered a more suitable form of fuel than ethanol for the existing fuel infrastructure because of its superior properties including the higher energy content, lower volatility, and lower water solubility.1 1-Butanol is generally produced by the fermentation of biomass containing carbohydrates, for example, starch, sugar, and cellulosic sources. Acetone-butanol-ethanol (ABE) fermentation by clostridia is one of the oldest industrial fermentation processes. The ABE fermentation process was first developed by Fernbach and Strange in 1911 and quickly spread around the world during World Wars I and II. However, the ABE fermentation process faded out in the mid-20th century as the production cost of the fermentation process was no longer competitive with the ones of petrochemical processes.1−3 Commercial interest in the ABE fermentation process peaked again in the early of 1980s after the oil crisis in the 1970s. Recently, the process has regained its attention with the announcement of DuPont’s biobutanol development plan in 2006.4 Research efforts have intensified, with its scope covering molecular aspects, for example, identification of metabolic reaction pathways and model-based analysis of metabolic © XXXX American Chemical Society

behaviors, as well as macroscopic aspects, for example, new fermentation/separation process development and optimal design for minimizing energy cost in downstream processes.5−9 Although an industrial ABE fermentation process has recently been re-established in China,10 its commercialization is still limited because of several technical challenges such as low volumetric productivity, low product concentration, and high cost for recovery and separation of the solvent.3 In particular, the severe inhibition of the cell growth by the toxicity of 1-butanol is known as a major cause of the low product concentration and productivity. The cell growth and substrate uptake of wild-type clostridium become completely inhibited when the concentration of 1-butanol reaches a level of approximately 13 g/L,11 and despite intensive efforts in the genetic engineering front, the inhibition threshold for genetically modified clostridia has reached merely 17.6 g/L.12 To overcome the toxicity problem by 1-butanol, an in situ or ex-situ auxiliary phase to separate and recover 1-butanol from the fermentation broth can be incorporated into the fermentation process as shown in Figure 1.13 The fermentation process integrated with the 1-butanol separation process can Received: May 14, 2012 Revised: November 23, 2012 Accepted: December 18, 2012

A

dx.doi.org/10.1021/ie301249z | Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

Industrial & Engineering Chemistry Research

Article

(2) The interaction forces between adsorbate molecules are negligible. qi ,eq =

qi , mBi Ci ,eq 1 + Bi Ci ,eq

(1)

Readers are referred to the section Nomenclature at the end of the paper for exact definitions of the various symbols. The parameters for the component i in eq 1, qi,m and Bi, are estimated using respective single-component aqueous solution. The estimated parameters can then be used to predict the amounts of the components adsorbed on the adsorbate in multiple-component aqueous solution. This extension of the single-component model to multiple-component aqueous solution is formulated as eq 2, which is called the extended Langmuir adsorption model.

Figure 1. Schematic diagram of fermentation process with adsorption recovery method: (a) In-Situ recovery, (b) Ex-Situ recovery, white dots are adsorbents.

raise both the yield and the volumetric productivity significantly because the inhibition of the cell growth by 1-butanol is minimized by the simultaneous fermentation/separation of the 1-butanol from the fermentation broth. Reduction in both the downtime and the separation energy is another benefit. A number of 1-butanol recovery techniques, ranging from gas stripping and liquid−liquid extraction to pervaporation, adsorption, and perstraction,14,15 have been investigated for possible incorporation into the ABE fermentation process. Among these techniques, adsorption has been identified as the most energy-efficient process to separate 1-butanol.16,17 Numerous efforts have been made during the past two decades to find appropriate adsorbents with high selectivity and capacity for 1-butanol recovery.18−22 From the literature survey and experiments, we have concluded that the polymeric resin is the best candidate adsorbent in terms of adsorption capacity and 1butanol selectivity for commercial-scale processing. The objective of this study is to investigate the adsorption and desorption characteristics of the ABE fermentation metabolites with the ultimate goal of developing a new fermentation process equipped with an in situ or ex-situ 1butanol recovery function using adsorbent as shown in Figure 1. Thus, several adsorption experiments, where poly(styreneco-divinylbenzene) adsorbent resin is used as adsorbent in a batch-type slurry adsorption process, have been carried out, and appropriate adsorption isotherm models and a kinetic model for the adsorption process have been developed. To ensure the practical feasibility of the adsorption process, we have also conducted desorption experiments to recover the adsorbates and to regenerate the adsorbent resin.

qi ,eq =

qi , mBi Ci ,eq n

1 + ∑i = 1 Bi Ci ,eq

(2)

Because we cannot directly measure the amount of the adsorbed components, qi, in experiment, it is calculated by means of mass conservation as shown in eq 3. Thus, the values calculated from eq 3 are used as the data in estimating the parameters, qi,m and Bi, in eqs 1 and 2. qiexperiment = ,eq

(Ci ,0 − Ci ,eq)Vaq m

(3)

The other adsorption model we examine in this paper is the IAST model. The IAST model was originally developed for modeling adsorption of multiple-component gases, and this method was later extended to ideal liquid solute systems.25 The IAST model provides a thermodynamically consistent and practical method for predicting multiple-component adsorption isotherms using single-component equilibrium data.26,27 The IAST model uses two variables: the spreading pressure, π, defined as the interfacial tension difference in a pure solventsolid interface, and the area of a solute-solid interface, A, for each component. The model equation based on the Gibbs adsorption isotherm is shown in eq 4.26 All the values are calculated on molar basis in the IAST model. Ci,eq qi ,eq RT πi = dCi ,eq A 0 Ci ,eq (4)

∫

Using eq1, the Langmuir isotherm for the adsorption of the component i, the expression for qi,eq/Ci,eq can be derived and substituted into eq 4 to obtain the following expression: Ci,eq qi ,eq πiA = dCi ,eq = qi , m ln(1 + Bi Ci ,eq) RT Ci ,eq 0 (5)

2. THEORY 2.1. Adsorption Equilibrium: the Langmuir Isotherm Model and the Ideal Adsorption Solution Theory (IAST) Model. Among the available adsorption equilibrium isotherm models, we tested the following two: (i) the Langmuir isotherm model and (ii) the ideal adsorption solution theory (IAST) model. The accuracy and fidelity of these models are assessed by comparing their predictions with experimental data in this work. The Langmuir isotherm model is derived from mass-action kinetics; it quantifies the amount of adsorbate adsorbed on adsorbent as a function of concentration at a given temperature.23,24 The Langmuir isotherm model for single-component aqueous solution is shown in eq 1. To use the model, the following assumptions are required:24 (1) The surface of the pores of the adsorbent is homogeneous.

∫

The mass conservation equation for the single component i, shown in eq 3, can be extended to a multiple-component system by using Ci,eq = Coi,eqzi and qi,eq = qTzi where, Coi,eq is the equilibrium concentration of the single component system, zi is the solid-phase mass fraction, and qT is the total amount of the adsorbed components. Equation 6 represents the predicted initial concentration of the component i in the multiplecomponent solution. ⎡ m ⎤⎥ o ⎢ Cipredicted = C + q zi ,0 i ,eq ⎢⎣ Vaq T ⎥⎦ B

(6)



Article 2 ⎡ ⎛ qi , mBi Ci ,eq ⎞ ⎤ ⎢ ⎥ ⎜ ⎟ min f (qm , B) = ⎜qi ,eq,experiment − ⎟⎥ qm , B ⎢ 1 B C + ⎝ ⎠ i i ,eq ⎣ ⎦

n

∑ zi = 1

(7)

i=1

⎛ n ⎞−1 z i qT = ⎜⎜∑ o ⎟⎟ ⎝ i = 1 qi ,eq ⎠

where qm and B are the vector of qi,m and Bi, respectively. For the adsorption equilibrium of the multiple-component solution, the objective function based on the IAST model shown below is used to estimate the model parameters.

(8)

Coi,eq

qoi,eq.

To use eq 6, one needs the expressions for and For this the previous expression of eq 5 can be used. The IAS theory assumes that all the spreading pressures are constant regardless of the component in a given system, so eq 5 reduces to eq 10. π1 = π2 = π3 = ... = πn = π (9) πA = Φ = qi , m ln(1 + Bi Ci ,eq) RT

⎡ ⎢ ⎢ ⎢ ⎢ ⎢ min⎢⎢f (Φ, z) = z ⎢ ⎢ ⎢ ⎢ ⎢ ⎣

(10)

Equation 10 then gives Cio,eq

=

exp(Φ /qio, m) − 1 Bio

(11)

⎤ ⎥ ⎥ ⎥ ⎥ ⎡ ⎥ o n ⎛ Φ − exp( / ) 1 q ⎜ i,m ⎢ ⎥ ∑ ⎜Ci ,0,experiment − ⎢ o ⎥ B ⎜ i i=1 ⎣ ⎥ ⎝ 2⎥ ⎞−1⎤ ⎞ ⎥ ⎛ n zi m⎜ ⎟ ⎥ zi ⎟ ⎥ + ∑ Vaq ⎜⎝ i = 1 qio, m[1 − exp( −Φ/Bio)] ⎟⎠ ⎥ ⎟⎟ ⎥ ⎦ ⎠⎦

Equation 11 can then be substituted into eq 1 to calculate the following expression for qoi,eq: qio,eq = qio, m[1 − exp( −Φ/Bio)]

(12)

Equations 11 and 12 can be used along with eqs 6−8 so that zi and Φ are estimated by minimizing error values between Cpredicted and the experimental data of Ci,0. i,0 2.2. Adsorption Kinetics. The adsorption rate, controlled by external mass transfer, is shown as follows:28 dqi dt

= ki(qi ,eq − qi)

(13)

(17)

Equation 13 can also be represented as the function of the concentration of the component i following mass conservation equation (see eq 14). dqi dt

=−

Vaq dCi m dt

qoi,m

⎛ (Ci ,0 − Ci)Vaq ⎞ Vaq dCi ⎟⎟ = ki⎜⎜qi ,eq − m m dt ⎝ ⎠

o

where and B i are defined using the Langmuir isotherm model for the single-component solution and z is the vector of zi. For the adsorption kinetics of the multiple-component solution, the objective function below is used.

(14)

⎡ ⎢ ⎢ ⎢ ⎢ min⎢f (k) = k ⎢ ⎢ ⎢ ⎢ ⎢⎣

Rearranging eqs 3, 13, and 14, we obtain the following mass balance equation which is the function of the concentration of the component i. Using the efficient optimization method explained in Section 2.3, the rate constant, ki, in eq 15 is estimated with the experimental data. −

(16)

(15)

In eq 15, qi,eq can be calculated by the aforementioned adsorption isotherm model, the extended Langmuir model or the IAST model. 2.3. Optimization Method: Combination of a Genetic Algorithm and the Levenberg−Marquardt Method. For the estimation of the adsorption model parameters, the objective function to be minimized is chosen as the mean square error between the model predictions and the experimental data. For the adsorption equilibrium of the single-component solution, the objective function shown below is used to estimate the maximum adsorption capacity and the Langmuir constant of the Langmuir model.

tf

n

⎛

⎛

⎝

⎝

∑ ∑ ⎜⎜Ci ,experiment(t ) − ⎜⎜Ci ,0 − t=0 i=1

−

(Ci ,0 − Ci)Vaq m

⎞⎞ dt ⎟⎟⎟⎟ ⎠⎠

2

m ki Vaq

⎤ ⎥ ⎥ ⎥ ⎥ t qi ,eq⎥ ⎥ 0 ⎥ ⎥ ⎥ ⎥⎦

∫

(18)

where k is the vector of ki. C



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strongly affected by the choice of the switching point from the GA to the LMA.37 Detailed information on this issue is explained in Supporting Information of the paper. Since the initial point of the LMA, determined by the GA at the switching point, should be near the optimum, the LMA is expected to converge rapidly to the optimal solution. 2.4. Adsorbate Recovery. To develop an energy-efficient 1-butanol separation system, a low-cost regeneration method is needed to recover the adsorbent. Steam is one of the simplest and widely used methods in commercial adsorption processes to regenerate the adsorbents, because steam can raise the temperature quickly and be easily condensed to recover the fermentation products.38−40 The recovery ratio of each component is calculated by using eq 19 with respect to the amount of the steam.

Since the objective functions are complicated, nonlinear functions of the parameters to be estimated, an efficient nonconvex optimization algorithm is needed. To estimate the parameters in eqs 16−18, an optimization technique that combines a genetic algorithm (GA) and the Levenberg− Marquardt algorithm (LMA) is used in this work. A GA, based on the theory of evolution in a natural system, is one of the most popular heuristic search algorithms. The algorithm works with a set of solutions called a population, and each solution is called an individual. After an initial population is created, the objective function value for each individual is computed. Subsequently, individuals with superior objective function values are selected to generate the next generation of the population through the use of certain genetic operators, for example, crossover and mutation of the selected individuals. In general applications of a GA, this regeneration procedure is repeated until the solution satisfies chosen termination criteria.29,30 Even though the GA has been applied to highly nonlinear and multidimensional optimization problems, they suffer from the drawback that the computational load increases quickly with the problem dimension. In other words, a significantly larger population is required in solving multidimensional problems. The overall number of calculation steps grows exponentially with population size. To resolve this issue, a fast deterministic optimization method, the LMA, is integrated with the GA.31,32 The LMA is mathematically derived by a linear approximation, and the search method is based on calculation of a gradient.33,34 The LMA is considered as a combination of the steepest descent method and the Gauss−Newton method to combine the advantages of both algorithms: (i) the speed of the Gauss−Newton method and (ii) the stability of the steepest descent method.35,36 The overall procedure of the combined method is described in Figure 2. A large solution space is searched by a GA without concern over the appropriateness of initial guess. After a given number of generations, the best solution found by the GA up to the current time serves as the initial guess for the ensuing LMA. The effectiveness of the combined optimization algorithm is

Rei =

Ci ,condVcond qi

(19)

3. MATERIALS AND METHODS 3.1. Adsorbent. Poly (styrene-co-DVB) polymer resin used in this research is Dowex optipore L-493 purchased from Dow Korea. This polymer resin has high surface area and porosity. It was evaluated highly in a previous study because it has a high surface area (1,100 m2/g) and high adsorption capacity for 1butanol, about 4.10 mol/kg at a fixed aqueous 1-butanol concentration of 1% (w/v).22 3.2. Model Broth. Acetone (99.9%, Sigma-Aldrich), 1butanol (99.8%, Sigma-Aldrich), ethanol (anhydrous, 99.5%, Sigma-Aldrich), acetic acid (99.7%, Sigma-Aldrich), and butyric acid (99%, Sigma-Aldrich) were used for the fermentation model broth. All chemicals for the fermentation media are purchased from Junsei Chemical, Co. (Tokyo, Japan). 3.3. Fermentation Broth. The actual broth is prepared by a batch fermentation of Clostridium acetobutylicum ATCC824. The batch fermentation is performed in a 7 L Bioflo 310 fermentor (NewBrunswick Scientific Co., Edison, NJ) containing 2 L of Clostridial Growth Media (CGM). The CGM media contained the following components per liter of water: glucose, 80 g; yeast extract, 5 g; KH2PO4, 0.751 g; K2HPO4, 0.754 g; MgSO4·7H2O, 0.710 g; MnSO4·5H2O, 0.014 g; FeSO4·7H2O, 0.010 g; asparagines, 2.3 g; NaCl, 1 g; and (NH4)2SO4, 2 g. The pH is maintained above 5.0 by the addition of NH4OH, and the temperature is controlled at 37 °C. The broth samples for the adsorption tests are taken from the fermentor after 48 h of fermentation. 3.4. Analytical Method. Concentrations of ABE(1butanol, acetone, ethanol) and acids (acetic and butyric acid) in the aqueous solution are measured by gas chromatography (GC) using Agilent 6890N Series/5873 Network (Agilent Technologies, Palo Alto, CA, U.S.A.). A GC is equipped with a flame ionization detector (FID) and a 300 mm × 7.8 m glass 80/120 Carbopack BAW packed column (Supelco Inc., Bellefonte, PA). The flow rate of helium as a carrier gas is 3 mL/min. Inlet heater and FID temperatures are set to be 220 and 280 °C, respectively, and the following conditions are used: oven temperature of 100 °C for 30 s, ramping up to 135 °C at 10 °C/min, ramping up to 170 °C at 30 °C/min, and then programmed at 170 °C for 9 min final hold.

Figure 2. Application of a novel optimization technique combining a genetic algorithm and the Levenberg−Marquardt algorithm: The parameters to be estimated in the figure are from eq 17. D



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4. EXPERIMENTS Experiments performed in this study are categorized into three parts as follows: (i) Adsorption equilibrium isotherm experiments: Experiments for studying the adsorption equilibria of the metabolites are carried out. The adsorption characteristics of singlecomponent and multiple-component solutions are investigated through these experiments. With the experimental equilibrium data, the parameters of the adsorption isotherm models, the Langmuir model, and the IAST model are estimated. (ii) Dynamic adsorption experiments: Using the slurry type adsorption equipment, the dynamic behaviors between adsorbate and adsorbent are analyzed. The experimental data are then used to estimate the parameters of the kinetic model, eq 13. (iii) Regeneration of the adsorbent resin: The steam regeneration method is used to regenerate the adsorbents as well as to recover the adsorbates. To help determine the optimal amount of regeneration steam, the recovery ratios of the adsorbates are calculated with respect to the amount of the steam. 4.1. Adsorption Equilibrium Isotherm. Adsorption equilibrium isotherm experiments for the single-component solutions are performed in sterile, 50 mL flask containing 25 mL of aqueous solution and the polymer resin. The initial total concentration of the ABE and acids in each aqueous solution is about 10 g/L. The amount of the polymer resin varies from 1 to 25 g in the experiment. The flasks are agitated at 150 rpm in a water bath at 37 °C. After 24 h of equilibration, the liquid phase concentrations of 1-butanol and other components are analyzed by GC-FID. The adsorption equilibrium experiments of the multiplecomponent solution are carried out in the same manner as the single-component experiment. Five equilibrium experiments are conducted as shown in Table 1.

butanol, 4.569 g/L of acetone, 4.19 g/L of ethanol, 2.106 g/L of butyric acid, and 2.35 g/L of acetic acid. Samples are taken in the same manner as in the model broth experiment. The concentrations of the components in the 17 samples are analyzed and plotted as concentration versus time. 4.3. Adsorbates Recovery. The desorption experiments of the adsorbents are carried out using 140 °C saturated steam at 3 bar (gauge pressure). The saturated steam is generated from an electric steam generator (Pyeong Hwa Machinery Co. Ltd). A stainless steel column is used for the desorption experiments. The length and the diameter of the column are 25 and 7 cm, respectively, and it is filled with 300 g of the adsorbent. Before the adsorbent regeneration experiment, the adsorbent is submerged in a 500 mL of model broth solution containing 1-butanol, acetone, and ethanol at 37 °C for 24 h and then the solution is removed from the column. The weight of the column and the concentrations of the components in the solution are measured before and after the adsorption to calculate the amount of the components adsorbed onto the adsorbent resin. The 140 °C steam is fed through the column, where the flow rate ranges between 40 and 60 g/min. The effluent is condensed through the condenser to be collected, and the condensate is periodically sampled to measure the amount of the steam and the recovered adsorbates. Subsequently, the amount of the steam used per unit mass of the adsorbent and the recovery ratios of the adsorbates are calculated using eq 19.

5. RESULTS AND DISCUSSION 5.1. Adsorption Equilibrium Isotherm. The adsorption isotherm curves of 1-butanol, acetone, ethanol, butyric acid, and acetic acid with the polymer resin are shown in Figure 3. In case

Table 1. Adsorption Equilibrium Experiments

concentration of multiplecomponent solution solution volume test number adsorbents amount

acetone

ethanol

1butanol

acetic acid

butyric acid

8 g/L

8 g/L

20 g/L

5 g/L

2 g/L

50 mL 1 3g

2 5g

3 7g

4 10g

5 15g

4.2. Adsorption Kinetics. Experiments for studying the adsorption kinetics are also performed in a batch type slurry reactor. About 20 g of the polymer resin is added to a 500 mL flask containing about 250 mL of the model broth solution, which contains 15.297 g/L of 1-butanol, 4.416 g/L of acetone, 4.562 g/L of ethanol, 2.086 g/L of butyric acid, and 2.35 g/L of acetic acid. The flask is agitated at 150 rpm in the water bath, where the temperature is maintained at 37 °C. After adding the polymer resin, 10 samples are taken from the flask at 1 min intervals over the first 10 min and then 7 additional samples are taken with 5 and 10 min intervals over the next 60 min. The concentrations of the components in the samples are analyzed and recorded as concentration-versus-time data. The kinetic experiment using the actual fermentation broth is carried out in the same way as the model broth experiment. The concentrations of the components in the actual broth measured after the 48-h fermentation are 14.868 g/L of 1-

Figure 3. Experimental and best-fit Langmuir isotherm of 1-butanol, ethanol, acetone, butyric acid, and acetic acid with Dowex Optipore L493 resin.

of acid adsorption isotherm, the undissociated form of acids is assumed to be adsorbed preferentially onto the polymer resin as found in a previous study.41 This is because the ionized form has much higher affinity for water, and thus is more likely to remain in the liquid phase. E



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decreased compared to the single component adsorption case. This is clearly caused by the competition with the 1-butanol adsorption. Multiple-component adsorption is predicted by the extended Langmuir model and the IAST model, and the predicted values are compared with the experimental data in Figure 4. The predictions of both models are generally well matched with the experimental data. However, the IAST model’s predictions are more accurate than those by the extended Langmuir model, except for the case of acetone. In particular, the adsorption characteristics are accurately predicted by using the IAST model when the concentration of the 1-butanol is high. Thus, qi,eq for each component is calculated by the IAST model, and these values are used in the kinetic adsorption model. 5.2. Adsorption Kinetics. The kinetic adsorption profile of each component in the model broth experiment is shown in Figure 5. The parameters of the kinetic model, ki, are calculated by fitting the concentration curves shown in Figure 5. The fitted parameter value for each component is shown in Table 3. All the components reach the equilibrium state in about 10 min. 1-Butanol has higher affinity to the adsorbent, and has a lower kinetic parameter value than the other components. The kinetic model for the model broth experiment is verified using the actual fermentation broth. The experimental results and the prediction data of the developed kinetic model are plotted in Figure 6. It is shown that the kinetic model estimated with the experimental data of the model broth effectively predicts the adsorption phenomena in the real broth. This result proves that

The adsorption isotherms of the components show the polymer resin that we use adsorbs highly preferentially 1butanol and butyric acid followed by acetone, acetic acid, and ethanol. This result means that the hydrophobicities of the components have major effects on the adsorption on the polymer resin. The Langmuir equation is fitted to the single-component isotherm data so that the two parameters, qi,m and Bi, of the Langmuir isotherm model are estimated (see Figure 3). The fitted parameter values are given in Table 2. These parameters are then used for the predictions of the multiple-component adsorption isotherm model, the extended Langmuir model and the IAST model. Table 2. Fitted Parameter Values of the Langmuir Isotherm Model Bi qi,m

acetone

ethanol

butanol

acetic acid

butyric acid

0.119 92.79

0.043 97.16

0.359 132.95

0.067 77.65

0.321 123.50

Adsorption equilibrium experiments with the model broth solution, which is the multiple-component aqueous solution containing 1-butanol, acetone, ethanol, butyric acid, and acetic acid, and varying amounts of the adsorbent are performed to observe the competitive adsorption phenomena. In the adsorption of the multiple components, the adsorption amount of acetone, ethanol, and acetic acid adsorption are obviously

Figure 4. Experimental and prediction data of competitive adsorption with multiple-component mixture. F



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model broth experiments is considered to be suitable for predicting the adsorption phenomena in the real fermentation broth system, so the model may be used to determine the optimal design and operating conditions of the extractive fermentor. 5.3. Adsorbates Recovery. The recovery ratio of each component with respect to the amount of the regeneration steam is calculated using eq 19 and is represented in Figures 7

Figure 5. Experimental and fit data of multiple-component adsorption kinetics of model broth.

Table 3. Fitted Parameter Values for the Kinetic Model ki

acetone

ethanol

butanol

acetic acid

butyric acid

3.974

4.619

0.404

4.98

0.553

Figure 7. Recovery ratio of total ABE as a function of the regeneration steam amount.

Figure 8. Recovery ratio of 1-butanol, acetone, ethanol, and total ABE as a function of the regeneration steam amount (20%, 50%, and 80% of adsorbents).

and 8. The amount of the steam used is represented as the ratio of the mass of the steam to the mass of the adsorbent. The line in Figure 7 represents the recovery ratio of the total adsorbed ABE with respect to the amount of the regeneration steam. Figure 8 shows the recovery ratio of acetone, ethanol, 1butanol, and total ABE at steam-to-adsorbent ratios of 20%, 50%, and 80%. Acetone and ethanol have slightly higher desorption ratios than 1-butanol, especially at the low steam amount. This is because these two components vaporize more easily than 1-butanol because of the lower boiling points.

Figure 6. Experimental and Prediction data of multiple-component adsorption kinetics of real fermentation broth.

the cells, the nutrients, and other unknown compounds in the real broth do not disturb the adsorption phenomena of 1butanol. 1-Butanol has a significantly higher affinity to the adsorbents than the nutrients and unknown compounds in broth because of the hydrophobicity of 1-butanol, and hence the adsorption of the 1-butanol is not disturbed by those compounds. In summary, the kinetic model developed from the G



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Notes

With 20% of the steam-to-adsorbent ratio, approximately 20% of the adsorbed ABE is desorbed and then the recovery ratio is sharply increased up to 80% at 50% of the steam-toadsorbent ratio. However, the recovery ratio slows down at 80% of the recovery ratio. To achieve the further 10% recovery, approximately 30% of the additional amount of the steam is required. Though 80% of the recovery ratio can be easily reached with the small amount of the steam, a considerable additional amount of the steam is needed to reach 90% of the recovery ratio. This result means that there is the following trade-off: (i) A high (∼90%) recovery ratio requires a significant additional amount of the steam. (ii) The operating cost and capital cost for the steam generation and the ABE recovery increases as the amount of the steam consumed increases. Thus, in a commercial plant design, the optimal amount of the steam for the regeneration of the adsorbent should be determined by considering the trade-off in terms of economics.

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by the Energy Efficiency & Resources of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Knowledge Economy. (2010201010094C). This work was also supported by the Advanced Biomass R&D Center(ABC) of Global Frontier Project funded by the Ministry of Education, Science and Technology (ABC-20110031354).

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6. CONCLUSIONS Dowex Optipore L-493, poly(styrene-co-divinylbenzene) resin has been evaluated to be an attractive adsorbent for the recovery of 1-butanol from ABE fermentation broth because of its high capacity and selectivity for 1-butanol. Its hydrophobic property enhances the selective adsorption of 1-butanol. The parameters of the Langmuir isotherm model and the kinetic adsorption model have been estimated with the data obtained from single- and multiple-component experiments. These models have been extended to predict the competitive adsorption phenomena in an aqueous mixture containing 1butanol, acetone, ethanol, acetic acid, and butyric acid, and the adsorption kinetics in the actual broth. The model predicted values were found to match the experimental data very well without any modification. Thus, we may conclude that the developed adsorption models are sufficiently accurate representations of the adsorption phenomena of the components in the ABE fermentation broth. The developed kinetic model is expected to contribute significantly to designing a large-scale adsorption process for higher 1-butanol production. Adsorbents regeneration experiments show that steam regeneration method is suitable for adsorbent regeneration and 1-butanol recovery. A high regeneration ratio of the adsorbent and low steam consumption should bode well for developing a costeffective ABE fermentation process.

■

Greek Letter

■

π = spreading pressure component i

REFERENCES

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ASSOCIATED CONTENT

S Supporting Information *

Further details are given in Figures S1−S3. This material is available free of charge via the Internet at http://pubs.acs.org.

■

NOMENCLATURE A = adsorbed surface area per unit mass of adsorbent [m2/ kgadsorbent] Bi = adsorption-equilibrium constant for component i [L/g] Boi = adsorption-equilibrium constant for pure-component adsorption of component i [L/g] Ci,eq = concentration of component i at equilibrium [g/L] Ci,0 = initial concentration of component i [g/L] Coi,eq = equilibrium concentration of the single component adsorption of component i [g/L] Cpredictedi,0 = predicted initial concentration of the purecomponent adsorption of component i [g/L] Ci,cond = concentration of component i in condensate [g/L] ki = adsorption kinetic parameter for component i [/min] m = mass of adsorbent [kg] qi,eq = amount of adsorbed component i per unit mass of adsorbent at equilibrium [g/kgadsorbent] qi,m = maximum adsorption capacity for component i per unit mass of adsorbent [g/kgadsorbent] qT = equilibrium adsorption capacity of component i in a multiple-component adsorption system [g/kgadsorbent] Vcond = volume of condensate [L] R = ideal gas constant T = temperature zi = solid-phase mass fraction of component i

AUTHOR INFORMATION

Corresponding Author

* E-mail: [email protected] (S.P.), [email protected] (J.H.L.). Tel.: 82-42-350-3920 (S.P.), 82-42-350-3926 (J.H.L.). Fax: 82-42-350-3910 (S.P.), 82-42-350-3910 (J.H.L.). Present Address §

Hydrogen & Fuel Cell Department, New & Renewable Energy Research Division, Korea Institute of Energy Research (KIER), 152 Gajeong-ro, Yuseong-gu, Daejeon 305−343, Republic of Korea. H



Article

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