Process Biochemistry

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1 Process Biochemistry 47 (22) Contents lists available at SciVerse ScienceDirect Process Biochemistry jo u rn al hom epa ge: Continuous separation of succinic acid and lactic acid by using a three-zone simulated moving bed process packed with Amberchrom-CG3C Hee-Geun Nam, Chanhun Park, Se-Hee Jo, Young-Woong Suh, Sungyong Mun Department of Chemical Engineering, Hanyang University, Seoul 33-79, South Korea a r t i c l e i n f o Article history: Received 9 July 22 Received in revised form 24 September 22 Accepted 28 September 22 Available online 6 October 22 Keywords: Amberchrom-CG3C Simulated moving bed Continuous separation Model-based design approach Process experiment a b s t r a c t The issue of separating succinic acid and lactic acid in a continuous mode has been a major concern in the biotechnological process for production of succinic acid. To address this issue, both the optimal design and the experimental validation of a three-zone simulated moving bed (SMB) process for such separation were attempted in this article using the Amberchrom-CG3C resin and a self-assembled SMB unit with three zones. First, the intrinsic parameters of the two organic acids on the Amberchrom-CG3 resin were estimated at 4 C from a series of multiple frontal experiments. The resulting intrinsic parameters were then used in optimizing the experimental setting points for pump flow rates and switching time of the three-zone SMB equipment, which was assisted by an up-to-date genetic algorithm. Based on the optimized conditions, the relevant SMB experiment was conducted at 4 C and all the resultant samples from the product ports and column outlets of the SMB unit were assayed. It was confirmed from the assay results that the continuous separation of succinic acid and lactic acid was performed successfully. The experimental data for the product concentration profiles and the internal concentration profiles were also in reasonable agreement with the model predictions. 22 Elsevier Ltd. All rights reserved.. Introduction has been recognized as a highly useful chemical with a wide range of industrial applications [ 4]. Its noteworthy applications include surfactants, detergents, forming agents, ion chelators, cosmetics, pharmaceuticals, and antibiotics [,2,4]. Such a high value and a wide usefulness of succinic acid are mainly due to its own inherent multiple functional groups, which has led succinic acid to be called building-block chemicals in the literature [ 3]. In regard to the production of succinic acid, two different pathways have been established previously [,4]. One was based on a chemical pathway, in which succinic acid was produced from petroleum through chemical processing. The other was based on a biotechnological pathway, in which succinic acid was obtained from biomass through fermentation. Between these two, the biotechnological pathway has recently attracted more attention because its advantages in both economical and environmental aspects are becoming increasingly important [,4]. To ensure the economic feasibility of the aforementioned biotechnological pathway, it is essential to develop an efficient Corresponding author at: Department of Chemical Engineering, Hanyang University, Haengdang-dong, Seongdong-gu, Seoul 33-79, South Korea. Tel.: ; fax: address: munsy@hanyang.ac.kr (S. Mun). separation process for recovery of pure succinic acid because some impurities or by-products are generated during the fermentation procedure. Such a separation task has recently been handled by a nanofiltration process [4], which turned out to be effective in separating succinic acid from other by-product components on the whole. It was, however, reported to have some limitations in the removal of lactic acid, which was also one of the by-product components, due to the similarity between the rejection ratios of lactic acid and succinic acid during the nanofiltration processing [4]. As a means of addressing the aforementioned needs for separation of succinic acid and lactic acid, the application of a chromatographic column packed with Amberchom-CG3C resin has been proposed in the latest studies [5,6], where the relevant chromatographic separation process has also been designed in a continuous mode by using multiple chromatographic columns connected in series and multiple ports switched periodically. A chromatographic process with such pattern of structure and operation mode has been called a simulated moving bed (SMB), which is known to surpass conventional batch chromatographic processes in every respect [7 ]. However, the aforementioned Amberchrom-CG3C SMB process for continuous separation of the two organic acids has not yet been validated experimentally. The goal of this study is to experimentally verify the feasibility of continuous separation between succinic acid and lactic acid using a well-designed Amberchrom-CG3C SMB process. For this /$ see front matter 22 Elsevier Ltd. All rights reserved.

2 H.-G. Nam et al. / Process Biochemistry 47 (22) Fig.. Schematic diagram of a three-zone SMB process. (A) Lowest-affinity solute and (B) high-affinity solute. N: positive integer; t: time; t sw: switching time. task, a laboratory-scale SMB equipment that was configured to have three zones (Fig. ) was self-assembled by our research group and the adsorption isotherm and mass-transfer parameters of the two organic acids were estimated at the temperature of 4 C. The estimated parameters were then applied to optimal determination of the experimental setting points for pump flow rates and switching time, which corresponded to the operating conditions of the threezone SMB equipment. Based on the optimized operating conditions, the experiment of separating succinic acid and lactic acid in a continuous mode was conducted at 4 C and all the resultant samples were assayed by an HPLC system. Finally, the experimental evidences of verifying the Amberchrom-CG3C SMB performance in continuous separation of the two organic acids were provided. 2. Theory 2.. Systematic approach to the development of a continuous chromatographic separation process When a continuous chromatographic separation process like the three-zone SMB of our interest (Fig. ) is to be developed, it is of the utmost importance that a systematic method is used in order to reduce trial and error in process design and the number of experiments required for process development. One of wellsystematized methods for such purpose is a model-based design approach (Fig. 2), which is widely adopted in the area of a multicolumn chromatographic process development [7,8,2,3]. As illustrated in Fig. 2, the first step of this approach is to obtain intrinsic parameters from a series of single column experiments. The intrinsic parameters to be obtained include the Henry constants and mass-transfer parameters of feed components, which are independent of the scale or the operating condition of the system. The validity of these parameters is checked by comparison of the singecolumn experimental data and the relevant simulation based on a detailed chromatographic model. The validated parameters are then utilized in the optimal process design, which is to determine the operating parameters that can ensure high product purities and high productivity. This task requires the preparation of a highly efficient optimization tool, in which the intrinsic parameters of the feed components serve as input data and the operating parameters of a targeted process correspond to output results. After the optimal operating parameters are determined from the aforementioned optimization tool, their effectiveness are validated first by the process simulation based on a detailed model, and then by the process experiment based on a laboratory-scale equipment. Once the simulation and the experimental results for the process operation agree well with each other and both results ensure the attainment of a targeted separation goal, the validated process can be scaled-up to a large-scale process. In general, such a scale-up task can be accomplished by increasing the column diameter while keeping the interstitial velocities constant Detailed chromatographic model for simulation of a multi-column chromatographic process There are several kinds of chromatographic models available in the open literature. Among them, the lumped mass-transfer model was employed in this study because its effectiveness in predicting the separation behavior of a multi-column chromatographic process has been verified in many of previous studies [6 9,3 5]. In this model, convection, axial dispersion, and mass-transfer between mobile phase and solid phase (or adsorbent phase) are taken into account in the prediction of transport phenomena occurring in a chromatographic bed. The corresponding model equations for each chromatographic column are presented below [6,3 5]: ε b C b,i t + ( ε b )K f,i (C b,i C i ) + u ε b C b,i z 2 C b,i ε b E b,i z 2 = (a) C i ε p + ( ε p ) q i t t = K f,i (C b,i C i ) (b) where the subscript i stand for different solutes; C b,i is the mobile-phase concentration (g/l); C is the average pore-phase i concentration (g/l); q i is the solid-phase concentration (g/l S.V.), which is in equilibrium with C i ; ε b is the bed voidage; u is the liquid interstitial velocity; ε p is the particle porosity; and E b is the axial dispersion coefficient. In addition, K f is the lumped mass-transfer coefficient, which can be estimated from the following equation [6,3 5]: K f = (d p/2) 2 5ε p D p + (d p/2) 3k f (2)

3 242 H.-G. Nam et al. / Process Biochemistry 47 (22) Fig. 2. The outline of a model-based design approach for the development of an SMB chromatographic process for continuous separation. where d p is the diameter of adsorbent particle; D p is the intraparticle diffusivity; and k f is the film mass-transfer coefficient. The equilibrium relationship between q i and C in the above i model equation is usually expressed by an adsorption isotherm, which is given below in the case of a linear adsorption relationship: q i = H i C i (3) where H i is the Henry constant of component i. To solve the aforementioned model equations, a biased upwind differencing scheme (BUDS) was employed in conjunction with Gear integration having a step size of. The number of nodes in each column was set at 4. All of these numerical computations were carried out in Aspen Chromatography simulator Optimization tool for the optimal design of a multi-column chromatographic process One of the key steps in the model-based design approach is to utilize a proper optimization tool for the optimal design of a given process. In general, such a process optimization tool is prepared by combining a well-established optimization algorithm with a given process model. In this study, the electronic program of SMB optimization tool was prepared by linking NSGA-II-JG algorithm (elitist nondominated sorting genetic algorithm with jumping genes) [9,3,6 8] with the Aspen Chromatography simulator based on the lumped mass-transfer model. For this preparation, the relevant computerprogram codes for the NSGA-II-JG were prepared using Visual Basic Application (VBA) in Excel software. Since the NSGA-II-JG optimization requires repetitive numerical simulations, the VBA codes were prepared to include the function of calling Aspen Chromatography simulator as well as of implementing the NSGA algorithm. The prepared optimization tool begins with the specification of several NSGA-II-JG parameters, which includes the number of decision variables, the length of chromosome, population size, crossover probability, mutation probability, and jumping gene probability. Table lists such NSGA-II-JG parameters, which were used in the optimal design of the three-zone SMB of interest in this work. 3. Experimental 3.. Materials and lactic acid were purchased from Sigma Aldrich Co. (St. Louis, MO) and used for the preparation of a feed mixture to be separated in this work. Table NSGA-II-JG parameters used in the optimization of the three-zone SMB process for separation of succinic acid and lactic acid at 4 C. Parameter Value Number of decision variables 3 Population size 5 Length of chromosome 39 bits Crossover probability.9 Jumping gene probability.7 Mutation probability /(length of chromosome) Distilled deionized water (DDW) was obtained from a Milli-Q system by Millipore (Bedford, MA) and utilized as a desorbent in the SMB experiment performed. Sodium sulfate and methanesulfonic acid were purchased from Sigma Aldrich Co. (St. Louis, MO) and used in the preparation of a mobile-phase solution for HPLC assay. The Amberchrom-CG3C resin with an average diameter of 2 m was purchased from Rohm and Hass Co. (Philadelphia, PA) and utilized as the adsorbent (solid phase). This adsorbent was packed into an omnifit chromatographic column from Bio-Chem Fluidics Co. (Boonton, NJ). The diameter and length of this column are.5 cm and.6 cm, respectively. The bed voidage and particle porosity of the packed column were.376 and.723, respectively, which were obtained from a series of tracer-molecule pulse tests [5]. A column jacket supplied from Bio-Chem Fluidics Co. (Boonton, NJ) was used to control the column temperature Apparatus A Young-Lin HPLC system (Anyang, South Korea) was used in the single-column experiments. This system consisted of two HPLC pumps (Young-Lin SP-93D), a refractive index detector (Young-Lin 75F), an HPLC mixer from Analytical Scientific Instruments Co. (El Sobrante, CA), an HST-25WL circulator from Hanbaek Co. (Bucheon, South Korea), and a BW-2G water bath from Jeio Tech Co. (Daejon, South Korea). The entire operation of this HPLC system was controlled by Young-Lin Autochro-3 software. A Waters HPLC system (Milford, MA), which was employed for the assay of succinic acid and lactic acid, consisted of two HPLC pumps (Waters 55), a PDA detector (Waters 996), and an injector (Rheodyne 9725i). The control of this system was performed by Waters Millennium software. For the experimental testing of continuous separation between succinic acid and lactic acid, a laboratory-scale SMB unit based on a three-zone configuration was assembled by our research group in a similar manner to that in the literature [3,9]. This unit consisted of three rotary valves and three columns as shown in Fig. 3. For control of the flow rates, three pumps were employed in this equipment. An Ismatec REGLO-CPF Digital pump (Glattbrugg, Switzerland) was used to control the extract flow rate. A Series 2 PerkinElmer pump (Norwalk, CT) and a Young-Lin SP-93D pump (Anyang, South Korea) were used to control the flow rates of feed and desorbent respectively. The other details of this unit were described elsewhere [3] Assay An Acclaim Organic Acid analytical column (5 m, 4 mm 25 mm), which was purchased from Dionex Corporation (Sunnyvale, CA), was used in the abovementioned Waters HPLC system for the assay of each organic acid in the collected fractions from the single-column experiment and the SMB experiment. The mobile

4 H.-G. Nam et al. / Process Biochemistry 47 (22) Fig. 3. Picture of the laboratory-scale three-zone SMB equipment with three packed columns, three rotary valves, and three pumps. (a) Top part, (b) middle part and (c) lower part. phase was the aqueous solution of sodium sulfate with a concentration of mm and its ph was adjusted at 2.6 using methanesulfonic acid. The mobile-phase flow rate was ml/min and the sample injection volume was 5 L. The column temperature was maintained at 3 C using a Mistral Column Thermostat 88 (Plainsboro, NJ). The detector wavelength was 2 nm Procedures Single-column experiments In this study, two kinds of single-column experiments were carried out at the temperature of 4 C using the aforementioned Young-Lin HPLC system. First, a single-component multiple frontal experiment was carried out for each organic acid by using the two pumps in the Young-Lin HPLC system simultaneously. One pump delivered DDW and the other pump the feed solution containing either succinic acid or lactic acid. The concentration of each organic acid in the feed solution was kept constant at g/l throughout the experiment. The two streams were mixed before being loaded into the column packed with the Amberchrom-CG3C resin. Such a mixing process was facilitated by the HPLC mixer, which enabled the two streams to attain the state of a perfect mixing before being loaded into the packed column. The total flow rate for the mixed stream (i.e., the loaded solution) was kept constant at 2 ml/min. Various feed compositions (2%, 4%, 6%, 8%, and %) were obtained by changing the ratio of the two streams, which could allow the loaded solution to have five different concentrations, The ratio was changed only after a concentration plateau was fully developed at the column outlet. The column effluent was monitored using the refractive index detector. In order to maintain temperature at 4 C during the experiment, the DDW at a fixed temperature was continuously circulated through the jacket enclosing the packed column, which was carried out by the HST-25WL circulator. In addition, both reservoirs containing DDW and the feed solution respectively were immersed in the BW-2G water bath, which was also maintained at 4 C. Based on the data from the aforementioned experiment, the adsorbed amount of organic acid on the solid phase can be calculated in accordance with the procedures reported in the literature [7,8,2,2]. The results from such calculations can then be expressed into a series of adsorption data (q and C), which enables us to determine the Henry constants by using a linear regression based on a least-square analysis. In addition to the Henry constants, it is also necessary to obtain the mass-transfer parameters that can account for the above experimental data, which include the axial dispersion coefficient (E b ), film mass-transfer coefficient (k f ), molecular diffusivity (D ), and intra-particle diffusivity (D p). These mass-transfer parameters were obtained in the following manner. First, the E b and k f values were estimated from the Chung and Wen correlation [22] and the Wilson and Geankoplis correlation [23], respectively. The D value was calculated from the Wilke and Chang correlation [24]. The initial value of D p was calculated first from the Mackie and Meares correlation [25], and then fine-tuned by fitting the chromatographic model simulation with the aforementioned single-component multiple frontal experimental data. Secondly, a mixture frontal experiment was carried out at 4 C in a similar manner to that of the aforementioned multiple frontal experiment. The only difference was that the loaded solution contained a mixture of succinic acid and lactic acid, each of which had a concentration of g/l. In addition, the column effluent was collected and the concentrations of each organic acid in the collected fractions were measured by the Waters HPLC system with the Acclaim Organic Acid analytic column SMB experiment The three-zone SMB experiment was performed using the mixture of succinic acid and lactic acid as a feed solution. The concentration of each organic acid in the feed solution was set at g/l. The SMB experiment was started by turning on the pumps and triggering the timer of the valve controller (Labview 8.) simultaneously. During the experiment, the temperature was maintained at 4 C. For this purpose, the DDW at 4 C was continuously circulated through the jacket enclosing each of the three columns (Fig. 3), which was implemented by the HST-25WL circulator. In addition, the reservoirs containing the feed and the desorbent were wrapped with a TP2P(K) heating tape from Misung Scientific Co. (Yangju, South Korea), which was also maintained at 4 C. The experiment was continued for 45 steps and then stopped at the end of the final step. At this moment, the pumps were shut down and the internal-concentration samples were taken from the bottom of each column.

5 2422 H.-G. Nam et al. / Process Biochemistry 47 (22) (a) (b) Time (min) Experiment Simulation Time (min) Experiment Simulation Fig. 4. Experimental data and simulation results of the single-component multiple frontal experiments at 4 C. (a) and (b) lactic acid. q (g/l S.V.) q = C R 2 =.9998 q = C R 2 = Fig. 5. Plot of the adsorption data from the single-component multiple frontal experiments at 4 C. 4. Results and discussion 4.. Determination of intrinsic parameters (Henry constants and mass-transfer parameters) In order to facilitate an efficient development of the threezone SMB process under consideration, the model-based design approach was adopted in this study. One of the important tasks in this approach is to determine the Henry constants and masstransfer parameters of the feed components (succinic acid and lactic acid), which serve as key input data in the stage of process design and simulation. As a first step for this task, a singlecomponent multiple frontal experiment was carried out for each organic acid at 4 C and the results are presented in Fig. 4. The adsorption data (q and C) stemming from such experimental results were plotted in Fig. 5, which were then used to determine the Henry constant of each organic acid. The resulting values of the Henry constants are presented in Table 2. The mass-transfer parameters were also obtained in accordance with the procedures explained in the previous section and they are reported in Table Validation of the determined intrinsic parameters with the frontal experimental data The simulations based on the Henry constants and masstransfer parameters in Table 2 were carried out to check against the data from the single-component multiple frontal experiments. The results from such simulations were found to be in good agreement with the experimental data (Fig. 4). It is thus confirmed that the intrinsic parameters in Table 2 are valid as far as a single-component system is involved for the chromatographic system of interest. To check further whether the intrinsic parameters in Table 2 are valid in a mixture system, an additional frontal experiment was performed at 4 C while using the mixture of succinic acid and lactic acid as a feed solution. The result from this experiment was then compared with the chromatographic model simulations, which were carried out on the bases of the parameter values in Table 2. As shown in Fig. 6, the experimental and the simulation results agree well with each other. This indicates that the Henry constants and mass-transfer parameters in Table 2 are reliable in the chromatographic system under consideration and can thus be applied to the optimal design of the three-zone SMB process of interest Optimal design of the three-zone SMB process In the previous section, the intrinsic parameters of succinic acid and lactic acid on the Amberchrom-CG3C adsorbent were determined at 4 C in the linear isotherm region. These parameters were used in this section for optimizing the three-zone SMB process of interest, which had the column configuration of. This optimization was carried out in such a way that the desired separation of the two organic acids could be fulfilled while maximizing throughput. To attain such a separation goal, the feed flow rate, which is representative of throughput, was employed as an objective function to be maximized while taking into account the following constraint that the purities of both organic acids should be maintained higher than 98%. The other details in such an optimization task are available in the supplementary material file. The aforementioned optimization problem was solved by the SMB optimization tool that was prepared by combining the NSGA- II-JG algorithm [9,7,8] and Aspen Chromatography simulator as explained in the theory section. The resultant operating parameters Table 2 Intrinsic parameters, feed concentration, and column properties used in the optimization of the three-zone SMB process based on the Amberchrom-CG3C adsorbent at 4 C. Henry constant (H) Molecular diffusivity (D ), cm 2 /min Intra-particle diffusivity (D p), cm 2 /min Axial dispersion coefficient Chung and Wen correlation [22] (E b ), cm 2 /min Film mass-transfer coefficient Wilson and Geankoplis correlation [23] (k f ), cm/min Feed concentration (C feed ), g/l. for each component Adsorbent particle diameter 2 (d p), m Column bed length (L c), cm.6 Column bed diameter (d c), cm.5 Bed voidage (ε b ).376 Particle porosity (ε p).723

6 H.-G. Nam et al. / Process Biochemistry 47 (22) Table 3 The operating parameters and process performance of the optimized three-zone SMB for separation of succinic acid and lactic acid at 4 C. Optimal operating parameters Zone flow rates (ml/min) Inlet and outlet flow rates (ml/min) Q 5. Q 2 3. Q Q feed.29 Q des 5. Q ext.99 Q raf 4.3 Switching time (min) t sw 9.26 Process performance of the optimized three-zone SMB Product purities (%) Product concentrations (g/l) (a) the internal concentration profiles of the two organic acids were obtained from the simulations at the beginning, the middle, and the end of a switching period after a cyclic steady state was reached. The resulting concentration profiles are presented in Fig. 7. Note that the front and the rear of succinic acid band are well confined within zones III and I, respectively, while the rear of lactic acid band is well confined within zone II during the entire switching period. Obviously, such type of solute band distribution will ensure the continuous collections of succinic acid and lactic acid with high purities through the extract and raffinate ports, respectively. (b) Time (min) Time (min) Fig. 6. Result of the mixture frontal experiment at 4 C. (a) and (b) lactic acid. Symbols and lines indicate the experimental data and the simulation results, respectively. from this optimization and the performance of the optimized process are summarized in Table 3. One of the noteworthy phenomena in Table 3 is that the concentration of the raffinate product (lactic acid) is much lower than that of the extract product (succinic acid). The reason for such phenomenon is that the three-zone SMB under consideration possesses the enrichment zone in favor of high extract concentration (zone II) but has no enrichment zone in favor of high raffinate concentration. The occurrence of such a low raffinate concentration due to the absence of its relevant enrichment zone, however, is of little importance because the product of our interest in this work is the one collected from the extract port (i.e., succinic acid) whereas the lactic acid from the raffinate port is regarded as an impurity component. To check whether the solute migration behaviors in the optimized process are in agreement with the targeted separation goal, 4.4. Experimental validation of the optimized three-zone SMB process for separation of succinic acid and lactic acid In regard to the three-zone SMB process of interest, its optimal operating parameters were determined in the previous section. Using these parameters (Table 3) and the self-assembled SMB equipment (Fig. 3), the experimental testing of the optimized process was carried out in this section at the temperature of 4 C. During such SMB experiment, the samples from the raffinate and extract ports were collected and their concentrations were measured by the HPLC system. Since the samples were collected over an entire switching period (between two switches), the concentration of each sample represents the average concentration over one switching time. The experimental data of such a sample concentration are plotted in Fig. 8a and b as a function of the step number (i.e., the number of switching periods). It is clearly seen that most of the succinic acid and lactic acid molecules loaded into the feed port are continuously collected from the extract and raffinate ports, respectively. This indicates that the optimized process is effective in continuous fractionation of the two organic acids with high purities. The experimental evidence for such a successful fractionation is demonstrated in Fig. 9, which shows the raw data of the HPLC chromatograms for the feed mixture and for the two samples collected from the corresponding product ports at the final step. To facilitate the comparison between each other, all the HPLC chromatograms were obtained at the same wavelength, 2 nm. As seen in Fig. 9, the chromatogram for the feed mixture contains the peaks of both succinic acid and lactic acid. These two peaks can be compared with those in the chromatogram for each of the product samples (Fig. 9) in order to examine whether the separation of interest has been accomplished. First, it is worth noting in the HPLC chromatogram for the extract sample in Fig. 9 that only a succinic-acid peak is clearly identified whereas there is almost no trace of lactic-acid peak. Note also in the HPLC chromatogram for the raffinate sample in Fig. 9 that only a lactic-acid peak can readily be identified whereas there is almost no trace of succinic-acid peak. Considering all the aforementioned analyses based on the HPLC chromatograms, it is evident that the optimized three-zone SMB process was successful in

7 2424 H.-G. Nam et al. / Process Biochemistry 47 (22) (a) Desorbent Extract Feed.2 Zone I Zone II Zone III (b) Bed position Desorbent Extract Feed Zone I Zone II Zone III (c) Bed position Desorbent Extract Feed Zone I Zone II Zone III 2 3 Bed position Fig. 7. Simulated internal-concentration profiles at cyclic steady state for the optimized three-zone SMB process for separation of succinic acid and lactic acid. The internal concentration profiles were obtained at (a) the beginning, (b) the middle, and (c) the end of a switching period. performing the targeted separation between succinic acid and lactic acid Comparison of the SMB experimental data and the relevant model-predicted results Using the aforementioned SMB experimental data, the prediction capability of the mathematical model (Eq. ()) based on the intrinsic parameters in Table 2 could be evaluated for the optimized process. For this task, the relevant model simulations were carried out regarding the product concentration profiles, which were then compared with the experimentally measured concentration profiles. As can be seen in Fig. 8a and b, the simulation results are in reasonable agreement with the experimental data. In addition to the product concentration profiles, the internal concentration profiles were also obtained from both the SMB experiment and the model simulation. Both results are compared in Fig. 8c, where a satisfactory agreement between them can readily be observed. Such agreements between the experimental and the simulations results, which were confirmed in both the product concentration and the internal concentration profiles, indicate that the intrinsic parameters used in the optimal design of the three-zone SMB are relatively accurate and the model-based design approach based on genetic algorithm and simulation model is efficient Additional remark about the effect of some other impurities on the SMB separation of succinic acid and lactic acid In this study, only two components such as succinic acid and lactic acid were treated as the feed components to be separated by the SMB process under consideration. Of course, some other

8 H.-G. Nam et al. / Process Biochemistry 47 (22) (a) Step number (t/ts) sim. (lactic) sim. (succinic) exp. (lactic) exp. (succinic) (b) Step number (t/ts) sim. (lactic) sim. (succinic) exp. (lactic) exp. (succinic) (c) Desorbent Extract Feed.2. Zone I Zone II Zone III sim. (lactic) sim. (succinic) exp. (lactic) exp. (succinic) 2 3 Column number Fig. 8. Experimental data and simulation results for the optimized three-zone SMB process for separation of succinic acid and lactic acid. (a) Extract concentration profile, (b) raffinate concentration profile and (c) internal concentration profile. The concentrations of succinic acid and lactic acid in the extract and raffinate profiles were averaged over one switching period Feed AU Extract min Fig. 9. HPLC chromatograms for the feed mixture and for the samples collected from the extract and raffinate ports at the final step. All the above HPLC chromatograms were obtained at the wavelength of 2 nm.

9 2426 H.-G. Nam et al. / Process Biochemistry 47 (22) impurities may be contained in the output from the fermentation process. However, most of impurities existent in the fermentation output could be eliminated by the preceding nanofiltration procedures [4]. It was known that only a very small amount of acetic acid and formic acid could remain in the output from the nanofiltration procedures [4]. To check the possible effect of such two impurities on the SMB separation of succinic acid and lactic acid, additional frontal experiments were carried out for each of the two impurities (acetic acid and formic acid). It was confirmed from such additional experiments that both acetic acid and formic acid followed a linear isotherm relationship in the range of liquid-phase concentration up to those of succinic acid and lactic acid in the SMB separation. This implies that the presence of the two impurities would not affect the adsorption behaviors of succinic acid and lactic acid, because it is the general feature of a linear isotherm system that there is no competition among different components. It was confirmed further that the data from the single frontal experiment of succinic acid in the presence of the two impurities (acetic acid and lactic acid) could be predicted well by the simulation based on the intrinsic parameters in Table 2. It is therefore evident that the results of this study on the SMB separation of succinic acid and lactic acid will still be valid, even if the two impurities may be present in the feed mixture. 5. Conclusions A three-zone SMB process for continuous separation of succinic acid and lactic acid was developed in accordance with the model-based design approach, which covered the experimental validation of a targeted process as well as its optimal design. First, the intrinsic parameters of succinic acid and lactic acid on the Amberchrom-CG3C resin were estimated from a series of multiple frontal experiments at 4 C. The resulting intrinsic parameters were then applied to optimize the operating conditions of the three-zone SMB equipment, which was handled by the SMB optimization tool based on the NSGA-II-JG algorithm and the detailed chromatographic model. Under the operating conditions from such optimization, the relevant SMB experiment was carried out at 4 C. It was confirmed that the continuous separation of succinic acid and lactic acid was performed successfully. The experimental concentrations for the samples from the product ports and column outlets were also in reasonable agreement with the model predictions. Acknowledgments This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (grant number 22RA2A2A979). Also, it was partially supported by the Manpower Development Program for Energy & Resources supported by the Ministry of Knowledge and Economy (MKE), Republic of Korea. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at References [] Sauer M, Porro D, Mattanovich D, Branduardi P. Microbial production of organic acids: expanding the markets. Trends Biotechnol 28;26: 8. [2] Zeikus JG, Jain MK, Elankovan P. Biotechnology of succinic acid production and markets for derived industrial products. Appl Microbiol Biotechnol 999;5: [3] Hofvendahl K, Hahn-Hagerdal B. Factors affecting the fermentative lactic acid production from renewable resources. Enzyme Microb Technol 2;26:87 7. [4] Kang SH, Chang YK. Removal of organic acid salts from simulated fermentation broth containing succinate by nanofiltration. J Membr Sci 25;246: [5] Nam HG, Park KM, Lim SS, Mun S. 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