Entrainer Selection and Systematic Design of Heterogeneous

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Entrainer Selection and Systematic Design of Heterogeneous Azeotropic Distillation Flowsheets Amgad S. Moussa† and Laureano Jime´ nez*,‡ Chemical Engineering Department, School of Chemical Engineering, RoVira i Virgili UniVersity, Tarragona, Spain

We present a systematic procedure for entrainer selection and synthesis of heterogeneous azeotropic distillation flowsheets. First, we partition the flowsheet into tasks (mixing, decantation, and distillation) and identify the main distillation task. Then, we investigate the location of this task in the residue curve maps (RCMs) reported by Kiva et al. (Kiva, V. N.; Hilmen, E. K.; Skogestad, S. Chem. Eng. Sci. 2003, 58 (10), 1903-1953). Third, we analyze feasibility constraints on the main distillation task and the effect of pressure on these constraints. Furthermore, we demonstrate the case that performing this task requires a combination of the concepts of heterogeneous and extractive distillations in a hybrid scheme. The developed procedure is illustrated for 11 representative ternary mixtures. For these mixtures, the sensitivity of reflux and stage requirements of the column carrying out the main distillation task to continuous degrees of freedom (e.g., composition) and discrete degrees of freedom (e.g., use of multiple feeds) is discussed, besides other mixture-specific problems. 1. Introduction In this work, we develop a systematic procedure to solve the following process design problem: given a problematic binary mixture and a candidate entrainer that forms a heterogeneous azeotrope with one of the feed constituents, devise a feasible distillation-based flowsheet with the minimum number of columns to split this mixture. By a problematic binary mixture we mean an azeotropic mixture or a mixture of which the cost of splitting using distillation is prohibitively large, due to tangent pinches or low volatility difference. A number of motivations for developing a systematic procedure for the aforementioned problem exist. First, the iterative design by simulation approach is time and effort consuming, and without a guaranteed result for distillation sequences handling highly nonideal mixtures.2 This is due to the many nonlinear phenomena that characterize phase transformations of nonideal mixtures. These phenomena are the subjects of many research papers.3-8 In addition, these phenomena complicate the optimization of azeotropic distillation sequences and their synthesis using mathematical programming.9,10 Second, the difficulties in the synthesis of feasible azeotropic distillation sequences limit their application in industry due to cost and the time required in the design phase, not due to the total cost or operability shortcomings.11 This can lead to overlooking more cost-effective solutions based on azeotropic distillation; see, for example, the case reported by Diamond et al.12 On the other hand, the declining margins in the global market of commodity chemicals and the increasingly stricter environmental regulations compel the designer to consider as many processing alternatives as possible. Third, process development time should be reduced to a minimum as a result of the change to products with short lifetimes where most of the profit is gained upon product introduction to the market.13,14 † Current address: Institut fu¨r Chemie- und Bioingenieurwissenschaften, Swiss Federal Institute of Technology Zurich, ETH-Ho¨nggerberg/HCI 134, CH-8093 Zu¨rich, Switzerland. ‡ Current address: Department of Chemical Engineering, University of Barcelona, Barcelona, Spain. E-mail: [email protected].

In such a situation, systematic synthesis and design methods are very helpful as they promise significant reductions in time and money required for process development. These potentials motivate the research efforts in this area, which are expected to continue and grow at least for the near future.15 The goal of research in systematic process design methods is to build knowledge bases, representation techniques, algorithms, and software that enable the transformation of process design from an original design activity based on intuition and experience into a routine one, yet maintaining an opportunity for innovation of nonconventional solutions. This goal is yet to be achieved for the design of entire processes; however, promising results have been obtained for the synthesis of process subsystems such as distillation sequences,16,17 utility networks, and heat exchange networks.18 2. Outline of the Present Work Process design consists of three iterative steps:19 conceptualization, synthesis, and analysis. Presently, the first step is intuitive and experience-based to a considerable extent, while systematizing and automation of the second step is an active research area. The third step is almost completely automated with process simulators. This work can be viewed in accordance with the previous division. In the conceptualization step, we selected heterogeneous azeotropic distillation as the key technology to solve the problem. This implies that distillation, mixing, and decantation are the “building blocks” of the flowsheet, and that an entrainer that forms a heterogeneous azeotrope with one of the binary feed constituents is to be added to the feed. The second step is the synthesis, understood as the generation of alternatives and selection of the best (most promising) of them without conclusive information.19 This step, for the problem in hand, is 3-fold: (a) selection of a suitable entrainersany chemical compound can be considered as an entrainer if it forms a heterogeneous azeotrope with any of the binary feed constituents in a reasonable range of temperatures and pressures and passes certain environmental, toxicity, and corrosion checks; (b) selection of a feasible entrainersfor each family of entrainers,

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i.e., entrainers leading to the same class of residue curve maps (RCMs), feasibility constraints on both process structures and process conditions exist (these constraints must be derived from the topology of the RCM in a presynthesis analysis; the conclusions extend to all the members of this family of entrainers); (c) selection of the best feasible process structure using the entrainer chosen in steps a and bsfor each family of entrainers many feasible process structures can be generated that differ in cost and operability. In this work, we focus on the second aspect. Finally, in the third step (analysis), we investigate the factors that could affect the cost of certain process structures using detailed simulations. Throughout this paper, we use the letters “A” and “B” to refer to the binary feed constituents and “E” for the entrainer. “B” denotes the component that forms the heterogeneous azeotrope with “E”, while “A” denotes the component that does not. In addition, by “top product” we mean top vapor product, because when an overhead decanter is used, the distillate and reflux composition can differ. Boundary crossing was not considered in this work; therefore the total feed, the top products, and the bottom product of any distillation task are constrained to be in the same distillation region. We limit the discussion to ternary mixtures, for two reasons: first, the concepts used in this work are best understood graphically and visualization of phase transformations for quaternary mixtures is not obvious (and for mixtures with more components is impossible). Second, a plethora of possible topologies of RCMs exist for multicomponent mixtures, which makes analyzing all the topologically feasible classes impossible. However, this does not reduce the importance of this work since ternary subsystems can be analyzed to understand the topology of the multicomponent mixture. In addition, clustering techniques can be used to represent the mixture in a smaller number of pseudocomponents. Recently, both approaches were successfully applied to synthesis and design an azeotropic distillation flowsheet for a large industrial problem.12 Moreover, difficult splits, including azeotropic, are usually performed at the end of the separation flowsheet. This, combined with the fact that quaternary azeotropes are scarce and the existence of azeotropes of more components is highly unlikely and even disputed,20 causes azeotropic distillation sequences to handle few components. 3. Tasks Constituting Heterogeneous Azeotropic Distillation Flowsheets To minimize the number of tasks that require distillation, and therefore the number of columns, we recover a pure component from each distillation task.21 In addition, there are only two final product streams from the flowsheet, one mostly A, and the other mostly B. Figure 1 illustrates the different tasks that might be needed in heterogeneous azeotropic distillation flowsheets: DT1 and DT2 are distillation tasks, M1 and M2 are mixers, Sp1 is a splitter, and D is a decantation task. Solid lines represent essential elements of the task network, while dashed lines are elements that can be redundant. These nonessential elements can be grouped into the following: (a) the splitter (Sp), the mixer (M2), and the recycle stream connecting them; these elements are not required when the distillation task (DT1) can produce a stream whose composition belongs to the immiscibility region. Throughout this paper we assume that DT1 can produce a mixture whose composition belongs to the immiscibility region and is close to a heterogeneous azeotrope. (b) The distillation task (DT2) and its output streams are

Figure 1. State task network in heterogeneous azeotropic distillation flowsheets.

essential when the composition of the entrainer-lean phase recovered from the decantation task D is inferior to the specification of product B, so further distillation is needed to recover pure B and an entrainer-rich recycle stream. However, for many mixtures RCM topology allows high recovery of product A in DT1 and the immiscibility region is wide enough that pure B can be recovered directly from the decanter. Examples of these mixtures are shown in section 6. Therefore, the mixing task (M1), distillation task (DT1), and decantation task (D) are indispensable in any flowsheet. Nevertheless, some remarks about them when being translated into equipment are helpful in flowsheet design. First, it is advantageous to carry out tasks M1 and DT1 in the same equipment, by using multiple feed stages, since having multiple feed stages gives more degrees of freedom for structural optimization and enables the incorporation of extractive distillation concept in the design, as we will demonstrate in sections 4 and 6. However, we distinguish between the mixing and distillation tasks in Figure 1 because the composition of the output stream of mixing, i.e., total feed to the column, must be in the distillation region of component A. Finally, the decantation task should be combined with DT1 in a distillation column with an overhead decanter to give more flexibility in operation to handle composition fluctuations. From the analysis performed we conclude that the distillation task (DT1) is central to any heterogeneous azeotropic distillation flowsheet. DT1 splits the feed and the entrainer into a product stream (A) and a second stream with a composition close to the heterogeneous azeotrope. RCM topologies where component A and the heterogeneous azeotrope lie in different regions can be considered just if curvature of the boundary is significant and the operational complications of placing a column across a boundary are compensated for. Preconcentrating the binary feed to partially recover one of the pure components and feed the process with the azeotropic mixture was not considered, although it might improve the process economics and/or controllability, since, as stated earlier, the focus of this paper is on carrying out presynthesis feasibility analysis for all the entrainer families that are likely to be encountered in the search for an entrainer. Feng et al.22,23 investigated the combinatorial complexity of the problem space for the synthesis of heterogeneous azeotropic distillation flowsheets. However, their work focused only on one family of entrainers. Although their work resulted in many nonintuitiVe structures, tasks DT2 and DT1 exist in all flowsheets. 4. The Main Task in Different Residue Curve Map Topologies Kiva et al.1 provided an extensive survey of the basics of RCMs as well as different classification systems. In addition, Peterson and Partin24 defined the so-called “temperature se-

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Figure 2. Cell types I, II, III, IV. “S” indicates a saddle, and “N” denotes a stable or unstable node.25

quence” and used it to categorize and identify all topological feasible distillation region diagrams (DRDs), a simplified version of the RCM. 4.1. Elementary Cell Types. Hilmen et al.25 noticed that all the DRDs of the mixtures reported in Reshetov’s report can be represented by a combination of only four elementary cells (Figure 2). They defined the elementary cell as a distillation region taken with its boundaries that is a subspace of the composition space constrained to simple distillation boundaries and simplex boundaries. This feature of RCMs guided us in selecting the mixtures studied in section 6. We tried to show mixtures where the main task belongs to cells with different types. This supports our claim that the mixtures discussed are representative of innumerable others. Types I and II constitute the majority of common RCM topologies.25 Elementary cell type I has three vertexes (singular points). These vertexes are one stable node, one unstable node, and a saddle. Elementary cell type II has four vertexes: one stable node, one unstable node, and two nonadjacent saddles. Elementary cell type III has the same number and type of vertexes as cell type II, but with adjacent saddles. Elementary cell type IV has five vertexes arranged as shown in Figure 2. 4.2. Location of the Main Task in Different RCM Topologies. This work covers all the residue curve map topologies encountered in the Reshetov survey: 1609 mixtures, of which 1365 are azeotropic.1 A notable finding of Reshetov’s is that azeotropic mixtures whose RCMs correspond to only 15 of Serafimov’s classes (out of the 25 topologically feasible) were encountered when searching for entrainers for various industrial problems. Furthermore, only six of these 15 represent around 90% of the mixtures surveyed. Unfortunately, Reshetov’s results are not published and just some partial analysis is available.1,25 In addition, whether liquid-liquid immiscibility was considered in Reshetov’s survey is not reported in these references. Thus, we cannot judge the possibility of finding mixtures whose RCMs belong to a certain Serafimov class and which exhibit liquidliquid immiscibility in a way that facilitates separation. Consequently we assumed that any minimum boiling azeotrope can be heterogeneous, since the same kind of deviation leads to both phenomena. Finally, we found ternary mixtures whose RCMs correspond to eight Serafimov classes (the six most occurring classes plus two others), where a heterogeneous azeotrope exists.

Column designs to carry out the main task in these mixtures are explored in section 6. We examined each one of those 15 classes, searching for distillation regions that have a minimum boiling azeotrope in the same distillation region as the third component in the mixture (i.e., component A). When such a distillation region was found, we examined which of the Matsuyama Nishimura (MN) classes that belong to this Serafimov class can have it. Then, we studied the type of the singular points representing the minimum boiling azeotrope and component A and the possible type of singular point representing the entrainer. The result is the catalog presented in Figure 3. In this figure, the 15 azeotropic Serafimov classes reported in Reshetov’s survey are shown. Arrows indicate the direction of saturation temperature increase for the case when at least one minimum boiling azeotrope exists. If more than one direction is possible, no indication is made. Each singular point is represented by S (saddle), SN (stable node), UN (unstable node), or N (node, which in some RCMs is unstable while in others is stable). The number following these letters is to distinguish between singular points of the same type in the same RCM when highlighting the main task. Below each diagram the Serafimov class is written followed by the corresponding MN classes. The splits that could be carried out by the main task are indicated in the last line. Bold underlined vertexes denote the possible places of the candidate entrainers to split the binary mixture located at the opposite edge. Indicating more than one vertex as candidate entrainer (i.e., bold and underlined) means that the same RCM topology might be encountered in the search of entrainer for two different separation problems, in each of which the entrainer is represented by a different singular point (an example to illustrate this is shown in subsection 6.8). As stated earlier, exploiting boundary curvature was not considered, and thus, the splits are indicated only for mixtures where component A is in the same region as the minimum azeotrope. For example, when considering Serafimov class 2.0-2a, only the topologies corresponding to MN classes 023 and 320 are shown, since the main task UN-S1 does not cross the distillation boundary. In the other MN classes (401 and 410, not shown in Figure 3) that belong to this Serafimov class, the singular points representing the minimum and maximum boiling azeotropes exchange their positions with respect to the distillation boundary. Therefore, the main task becomes SN1-SN2 and boundary crossing becomes necessary. Nevertheless, if a sufficiently curved boundary is found, feasible distillation flowsheets can be devised, as shown by Wilson et al.,26 who used aniline as entrainer to split a mixture of hydrazine + water. 5. Feasibility of the Main Separation Task The feasibility of a split is influenced by its position in the RCM and by RCM topology. Two significant phenomena that might be present in the RCM are distillation boundaries and compartment boundaries. For detailed information about these phenomena and other characteristics of RCMs, see refs 1, 3, 4, 27, and 28. For conceptual design, a distillation boundary can be approximated by a straight line if no splits demand that the column’s mass balance line or composition profiles intersects a distillation boundary,29 which corresponds to the cases analyzed in this work. Similarly, a compartment boundary can be approximated by a straight line connecting the stable and unstable node vertexes in the distillation region.30 A split is feasible when a range of reflux ratios exists such that the composition profiles of the different sections (e.g.,


Figure 3. Catalog of the location of the main separation task in different RCM topologies.

stripping and rectification) of a distillation column intersect.4 Many criteria were developed to affirm or to deny the existence of this range of reflux ratios, without exhaustive trial-and-error calculations that include solving the tray-to-tray model. In this work we were guided by the common saddle criterion31 and the overlap of operation leaves32,33 in feasibility assessment. Since there are only two types of singular points in the RCM (nodes and saddles), only three types of splits can be assigned to the main task. These splits are node-node (one stable and the other unstable), node-saddle, and saddle-saddle. See illustrations of these splits in Figure 3. 5.1. Node-Node Split: UN-SN. As stated by the basic RCM theory, the unstable node, in this case the minimum boiling azeotrope, is always recovered as top product, while

the stable node is recovered as bottom product. This type of split can be encountered in elementary cells with type II or type IV (Figure 2). In both types, a compartment boundary that connects these two nodes exists (Figure 4). Although the operation leaves of the products include the entire distillation region, trace components play a critical role, as their influence may place the bottom and top products in different distillation compartments. This aspect may have a negative effect on reflux and stage requirements for single feed columns, because composition profiles of the stripping (or rectifying) section have to reach regions very close to the unstable (or the stable) node to intersect. Thus, it is preferred to have both top and bottom products in the same compartment. In this elementary cell type, the edge representing the problematic binary mixture lies in only

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Figure 4. Compartment boundary in a node-node split.

Figure 5. Boundary of the operation leaf of a stripping profile with a saddle product.

one of the compartments. If the entrainer-to-feed ratio is selected in a way that column profiles operate in this compartment, they might pass through a pinched region close to the problematic binary edge, where a large number of stages is required. Thus, we suggest that carrying out the main task in the compartment that does not contain the problematic binary edge can be economically advantageous, although the entrainer-to-feed ratio might be higher. We illustrate these two issues: the need to carry the separation in one compartment and that this compartment should not contain the problematic binary mixture, with the mixture studied in subsection 6.2. 5.2. Node-Saddle Split: S-SN or UN-S. Whether the node is stable or unstable decides if the saddle product is going to be recovered as distillate or bottom product, respectively. These splits can be encountered in distillation regions with type I, III, or IV, where a minimum (or a maximum) bound exists on the entrainer-to-feed ratio. This can be clarified by examining the DRD shown in Figure 5. The heterogeneous azeotrope is an unstable node; consequently, it has to be recovered as top product and its operation leaf is the entire distillation region. On the other hand, the saddle product has to be recovered as bottom product, and its operation leaf, whose periphery is approximated by the straight line, is a portion of the distillation region. The intersection between these two operation leaves is the saddle product operation leaf. This feature limits the region, where column composition profiles can intersect, to the left side of the azeotrope. That means that the entrainer-to-feed ratio has a maximum value governed by the feasible top product specifications, indicated by the shaded area in Figure 5. Moreover, column profiles are close to the problematic binary

edge which may raise reflux and stage requirements. In the other case, where the entrainer is the saddle vertex instead of the stable node vertex, the entrainer-to-feed ratio would have to exceed a certain value to have column composition profiles in the feasible region. This bound can be calculated from the mass balance, assuming that the top product has the azeotropic composition. 5.3. Saddle-Saddle Split: S-S. Heterogeneous Extractive Distillation. Examining the RCM that represents mixtures separable using extractive distillation, the so-called “extractive map”,4,34 we can define the extractive distillation task as the splitting of two nonadjacent saddle products in the same distillation region from an overall feed in the same region. With this definition in mind, we found that the concept of extractive distillation must be combined with the exploitation of liquidliquid immiscibility to carry out the main task in some of the RCM classes studied in section 4, where cells of type II or type IV exist. The key difference between the designed scheme and the classical extractive distillation is that one of the saddle points obtained from extractive distillation is a heterogeneous azeotrope, not a pure component. For example, when the RCM of the ternary mixture belongs to the Serafimov class 2.0-2b and the entrainer is the stable node SN2 (the highest boiling component in its region), the main task is to split two saddle products S1 and S2. The DRD and the flowsheet of heterogeneous extractive distillation for this family of entrainers are shown in Figure 6,; notice the similarity between the main distillation task DT1, carried out in two columns (C1 and C2), and a classical extractive distillation task. Column C1 is very similar to a classical extractive distillation column, except for the overhead decanter. Note that both the entrainer E and component A form minimum boiling azeotropes with component B; this means that they are most probably similar chemical compounds with high affinity to each other. Therefore, they flow together to the bottom of the extractive column and are split in column C2. As is the case in classical extractive distillation, the higher the boiling point of the entrainer the easier it is to separate it from component A and the higher the reboiler temperature is in column C2. Extractive columns have an additional degree of freedom, the top feed to bottom feed ratio. This ratio, as well as the reflux ratio, has both an upper and a lower bound between which the column is feasible.7,8,35 These bounds are influenced by nonideal interactions in the liquid phase and by how these interactions impact the relative volatility in both magnitude and order.34 Consequently, the feasibility constraints on extractive distillation are system specific and cannot be generalized in contrast to the former two split types. Hilmen36 describes how this combination of concepts was used by Wijesinghe.37 However, we reached the conclusion that such a combination is needed and possible independently, from the analysis done in section 4, the result of which is illustrated in Figure 3, and the analogy drawn between separation tasks splitting products with the same types of singular points. 5.4. Effect of Pressure on Range of Feasible Specifications. Optimization of operating pressure has deep influence on azeotropic distillation systems, due to the sensitivity of the azeotrope composition and existence to pressure. The change in the azeotrope composition causes quantitative changes in the geometry of the RCM, where the azeotropes represent ends of distillation or compartment boundaries. If an azeotrope appears and/or disappears as a function of pressure, then the topology of the RCM is changed qualitatively. However, it is not recommended to operate at such pressures due to operability and controllability reasons.38 Thus, we focus


Figure 6. Heterogeneous azeotropic distillation flowsheet. The compartment boundary is overcome by the extractive column (C1) and the distillation boundary by the decanter.

on cases where azeotropes, distillation boundaries, and compartment boundaries change their positions. This behavior affects the feasible region in saddle-node splits by broadening or narrowing the saddle product operation leaf, thus changing the bounds on the entrainer-to-feed ratio. It also affects the nodenode splits by changing the relative size of compartments, and therefore the entrainer-to-feed ratio required to place the column profile in a certain compartment. The effect of pressure on the cost of separation is more pronounced for complex RCM topologies, and it could be the key to significant reduction in recycle flows. 6. Case Studies The objective of this section is to show examples of distillation columns carrying out the main distillation task in different RCM topologies, as shown in section 4. In addition, the feasibility constraints on this task are examined according to section 5, and the sensitivity of cost to the degrees of freedom is explored. The RCM classes of the mixtures examined here represent around 90% of the mixtures reported in Reshetov’s survey.1 Therefore, these types of RCMs are more likely to be encountered in the screening of candidate entrainers than others. We use the boundary values design method developed by Doherty and co-workers as implemented in Distill 5.0. The mixtures were selected to cover different topological characteristics (i.e., type of singular points of the products and type of elementary cell where the main task is placed). It is worth noting that until now all our discussion was done on a component-free basis: everything was derived from the RCM topology and the association of pure components and azeotropes to the singular points of different types. The headline of each case study states the components of the mixture, the Matsuyama Nishimura classification of the RCM (≈DRD), the type of the cell where the main task lies, and the type of split performed by the main task. All binary feeds were assumed to be equimolar. The composition of the A product stream was set to 99.5% (mole). The fraction of component A lost in the other product was set

to 0.1% except in case 4, due to the existence of a ternary azeotrope, and in case 6, due to the relatively close position of the boundaries. The operating pressure is 1 bar, unless otherwise specified. 6.1. Acetone + Water + Isobutyl Alcohol, Temperature Sequence 1435, DRD 020, Cell Type I, Node-Saddle. This system exhibits a tangent pinch at a high concentration of component A (acetone). In the main distillation task, component A is recovered as a top product, and afterward the bottom product is cooled to enter the immiscibility region (Figure 7). Thus, the rectifying section operates in a region with low volatility difference. For this reason, we do not expect that entrainers with this RCM topology lead to drastic improvements in the cost. In the design shown, the rectifying profile is located as far as possible from the pinched region on the edge of the problematic binary mixture. However, since the bottom product specifications are limited to fall in the immiscibility region (which for the case in hand is close to the edge of the problematic mixture), the rectifying and stripping profiles proceed in different directions and would meet only at the unstable node (acetone) with a very high reflux ratio. A solution to overcome this problem is the use of a double feed column, where the middle section links the rectifying and stripping profiles that proceed in different directions. 6.2. Acetic Acid + Water + Ethyl Acetate, Temperature Sequence 2135, DRD 100, Cell Type II, Node-Node. This system (Figure 8) exhibits a compartment boundary. As explained in section 4, it is better to have top and bottom product specifications in the same compartment to have lower reflux and stage requirements for separations in a single feed column. For the mixture in hand we compare between separations in the two different compartments: Figure 8a,b for separation in the compartment that contains the edge of the problematic binary mixture and Figure 8c,d for separation in the adjacent compartment. The reflux ratio of the designs shown in Figure 8a,b are 1.2 times the minimum, which corresponds to 16 stages in the design shown at Figure 8b. Reflux ratios in the designs shown

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Figure 7. Acetone + water + isobutyl alcohol. Rratio ) 4; Nstages ) 34; entrainer-to-feed ratio ) 1.16.

Figure 8. Acetic acid + water + ethyl acetate at 2 bar. (a) Rratio ) 4.26; Nstages ) 28 (Nmin ) 20); entrainer-to-feed ratio ) 0.25; ratio of vapor flow to case d ) 2.0. (b) Rratio ) 2.80; Nstages ) 16 (Nmin ) 11); entrainer-to-feed ratio ) 0.50; ratio of vapor flow to case d ) 1.9. (c) Rratio ) 0.27; Nstages ) 16 (Nmin ) 12); entrainer-to-feed ratio ) 1.27; ratio of vapor flow to case d ) 1.1. (d) Rratio ) 0.38; Nstages ) 16 (Nmin ) 13); entrainer-to-feed ratio ) 0.88.

in Figure 8c,d were computed such that the number of stages is 16, to facilitate the comparison based on the vapor flow rate. The analysis performed shows that it is more economical to have composition profiles in the compartment that does not

contain the problematic binary edge to avoid tangent pinches, despite the higher entrainer-to-feed ratio. This ratio can be decreased if the azeotrope composition is moved closer to the problematic binary edge, something that can be achieved by


Figure 9. Acetic acid + water + n-butyl acetate, Rratio ) 2.0. (a) Nstages ) 24 (Nmin ) 17); entrainer mole fraction in the top vapor ) 0.2755. (b) Nstages ) 33 (Nmin ) 22); entrainer mole fraction in the top vapor ) 0.2750.

Figure 10. Benzene + acetonitrile + n-heptane. (a) Benzene column, Rratio ) 6.0; Nstages ) 25; entrainer-to-feed ratio ) 0.5. (b) Acetonitrile column, Rratio ) 0.5; Nstages ) 9.

changing the pressure. For example, increasing the pressure from 1 to 2 bar allows a reduction in the entrainer ratio, the positive effect of which on vapor flow surpassed the increase in reflux ratio, due to the higher operating pressures (Figure 8c,d). 6.3. Acetic Acid + Water + n-Butyl Acetate, Temperature Sequence 6135, DRD 001, Cell Type III, Saddle-Node. This type of RCM has a limit on the entrainer-to-feed ratio. If the azeotrope is pressure sensitive, then this limit has a similar sensitivity. When the entrainer is the saddle component, this limit is a minimum; i.e., the entrainer-to-feed ratio must be higher than a certain value, and the separation has to be carried out far from the problematic binary edge. On the contrary, when the entrainer is the unstable node, as the case studied here, the limit is a maximum; i.e., the entrainer-to-feed ratio must be lower than a certain value. Moreover, the column composition profiles have to progress close to the problematic binary edge. We show two designs: one at the maximum entrainer-to-feed ratio (Figure 9a) and one slightly below it (Figure 9b). The difference between the two cases is remarkable, even with a very small change in the composition specifications. Furthermore, the composition profiles shown in Figure 9b remain approximately the same for a wide range of entrainer-to-feed ratios below the maximum. The minimum stage requirement also has a similar behavior.

Such high sensitivity to the initial conditions is typical of nonlinear systems having a multiplicity of steady states in a certain range of parameters (i.e., entrainer-to-feed ratio and reflux ratio). The results shown here agree with the conclusion of Bekiaris et al.39 that the existence of two adjacent saddles may lead to output multiplicity. Thus, such behavior is expected to occur when separation takes place in elementary cells of type III or type IV.25 This case illustrates another issue regarding the design of distillation sequences for nonideal mixtures: the crucial role of the accuracy in vapor-liquid equilibrium (VLE) and vaporliquid-liquid equilibrium (VLLE) models. Kurooka et al.40 studied the control of the column separating the same mixture. They assumed ideal gas phase and consequently ignored the fact that carboxylic acids tend to associate in the gas phase.41 This resulted in the prediction of a nonexistent azeotrope between acetic acid and water and a completely different RCM topology. 6.4. Benzene + Acetonitrile + n-Heptane, Temperature Sequence 762135, DRD 202-m, Cell Type IV, Saddle-Node. The problematic mixture is the azeotropic mixture of benzene + acetonitrile. n-Heptane is selected as entrainer as it forms a binary heterogeneous azeotrope with acetonitrile. Figure 10a shows the column carrying out DT1, while Figure 10b shows the column where DT2 is performed. To accomplish this separation, both distillation tasks stated in Figure 1 are required.

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Figure 11. Ethyl propanoate + n-heptane + ethanol, Rratio ) 1.5; Nstages ) 23; entrainer-to-feed ratio ) 1.

6.5. Ethyl Propanoate + n-Heptane + Ethanol, Temperature Sequence 21356, DRD 130, Cell Type IV, SaddleNode. This example illustrates the separation of a maximum boiling azeotrope (ethyl acetate + heptane) using a light entrainer (ethanol) in a heterogeneous azeotropic distillation. Note that the top vapor composition is limited to the small immiscibility region located in the region with high ethanol concentration (Figure 11). Thus the entrainer-to-feed ratio has both an upper and a lower bound to ensure that the product of the main distillation task can enter the decanter directly. 6.6. Isopropyl Alcohol + Water + Ethyl Acetate, Temperature Sequence 621435, DRD 221, Cell Type II, NodeNode. This system has two highly curved distillation boundaries (Figure 12). This curvature makes high recovery of isopropyl alcohol difficult since the rectifying composition profile must extend in the narrow region near the azeotrope, as shown in Figure 12a. The high reflux ratio and large number of stages make this alternative virtually impossible to implement. These drawbacks can be partially mitigated by reducing the operating pressure, since one of the homogeneous azeotropes is pressure sensitive and moves in a direction that widens the region between the two boundaries, which increases the feasibility region and makes the separation easier. Figure 12b shows the column for an operating pressure of 0.5 bar. 6.7. n-Propyl Alcohol + Water + n-Butyl Alcohol, Temperature Sequence 61435, DRD 021, Cell Type II, SaddleSaddle. In this mixture, component A (propanol) and the heterogeneous azeotrope (water + n-butyl alcohol) are saddle points in the same distillation region. Such a situation is similar to the separation of ethanol + water using ethylene glycol, a well-known example for extractive distillation: the addition of ethylene glycol creates a ternary mixture in which water and ethanol are both saddle points. By analogy, the separation of propyl alcohol and the heterogeneous water + n-butyl alcohol azeotrope could be carried out using the same flowsheet: a double feed extractive column, where one of the saddle points is recovered, and an entrainer recovery column, where the other saddle point is separated from the entrainer. The main difference of both processes is that, in the case studied here, the saddle point recovered from the extractive column is a heterogeneous azeotrope that splits in the decanter to give component B (water) rich phase. The composition profile of the heterogeneous extractive column is shown in Figure 13. The combination of the concepts of heterogeneous and extractive distillation increases the number of potential entrainers.

Figure 12. Isopropyl alcohol + water + ethyl acetate. (a) Rratio ) 30.0; Nstages ) 93; entrainer-to-feed ratio ) 4; P ) 1.0 bar. (b) Rratio ) 9.0; Nstages ) 49; entrainer-to-feed ratio ) 4; P ) 0.5 bar.

Figure 13. n-Propyl alcohol + water + n-butyl alcohol. Heterogeneous extractive distillation, Rratio ) 5.0; Nstages ) 34; entrainer-to-feed ratio ) 2.

6.8. Acetonitrile + Water + Acrylonitrile, Temperature Sequence 64135, DRD 021, Cell Type II, Node-Node. In this RCM, as the one shown in subsection 6.7, the entrainer (acrylonitrile) most probably has physical and chemical properties similar to those of component A (acetonitrile), since both of them have a minimum boiling azeotrope with the same compound (component B, water). As a consequence of the small


Figure 14. Acetonitrile + water + acrylonitrile. (a) Rratio ) 100; Nstages ) 130; entrainer-to-feed ratio ) 1. (b) Rratio ) 1.5; Nstages ) 38; entrainerto-feed ratio ) 1.

difference in the boiling points between component A and the entrainer (≈4 °C) a high reflux ratio and a large number of stages are required to perform the main task (Figure 14a). This disadvantage can be circumvented using a double feed column, where the middle section operates in a region of the composition space where a more favorable volatility difference exists, as shown in Figure 14b. From this case, it is clear that multiple feed columns can reduce cost drastically, even when the entrainer and component A have similar boiling points. Note also that this is a node-node split, and as shown before, it is preferred to perform it in just one compartment. Economical designs can be devised when column composition profiles proceed in the compartment that does not include the pinched edge, as discussed in subsection 4.2. Difficulties in VLLE modeling of this system were also encountered since many of the activity coefficient models incorporated in the software used (Distill 5.0) were unable to predict the RCM topology obtained experimentally by Volpicelli.42 Again, the designer must be cautious with VLE and VLLE models, since all results can be irrelevant if a nonsuitable thermodynamic model is selected or if erroneous parameters are used. 6.9. Acetic Acid + Toluene + Water, Temperature Sequence 21435, DRD 120, Cell Type II, Node-Node. This case illustrates the separation where the objective is to split the azeotropic mixture of acetic acid + toluene, using water as entrainer. Alternatively, it can be applied to separate acetic acid

Figure 15. Acetic acid + toluene + water. (a) Rratio ) 2.0; Nstages ) 16; entrainer-to-feed ratio ) 0.4 (water as entrainer). (b) Rratio ) 2.0; Nstages ) 21; entrainer-to-feed ratio ) 0.4 (toluene as entrainer).

+ water, where a pinched region at high water concentration exists, using toluene as entrainer. The first case is shown in Figure 15a and the second in Figure 15b. Both problems were solved using a double feed column to enable the optimization of the column composition profiles to avoid the pinched regions of the composition space. 6.10. Ethanol + Water + Benzene, Temperature Sequence 7246135, DRD 222-m, Cell Type II, Node-Node. This class of RCMs has been studied extensively22,23,43-45 (since it is very frequently encountered). Therefore we just mention it here, without any further explanation. For more information, please check the above-mentioned references. 6.11. Ethanol + Water + Ethyl Acetate, Temperature Sequence 7624135, DRD 222-m, Cell Type II, Node-Node. This case is similar to the one mentioned in subsection 6.10, but in this mixture the ternary azeotrope is homogeneous and the immiscibility region does not intersect with the distillation region of component A (ethanol). On the basis of the invention of Martin and Reynolds,46 we suggest a process structure in which the homogeneous azeotrope recovered from the main task (the ternary azeotrope) is mixed with the entrainer (ethyl acetate) in a ratio that yields an overall mixture with a composition inside the immiscibility region. The column carrying the main task has one liquid phase throughout.

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7. Conclusions This work shows that in heterogeneous azeotropic distillation it is sufficient to consider two selection criteria for entrainers. First, the entrainer must form a heterogeneous azeotrope with one of the binary feed constituents. Second, the other binary component (A) and the heterogeneous azeotrope, or the azeotrope close to the immiscibility region, must belong to the same distillation region. The combination of heterogeneous and extractive distillation concepts appears to be the standard solution when the main distillation task is to split two saddle products. Also, when one of the products is a node, the common saddle criterion is a good technique to predict the constraints on composition specifications. The cases developed reveal some important insights; these insights have ample implications since the cases studied cover most of the RCMs reported in Reshetov’s survey. For example, the separability of the binary mixtures of the entrainer and each of the binary feed constituents is not crucial to indicate the separability of the ternary mixture. As shown in the cases developed, distillation sequences with reasonable sizes can be devised using entrainers with boiling points close to those of the binary feed constituents, entrainers that form tangent pinches with the binary feed constituents, and entrainers that introduce azeotropes other than the heterogeneous one. In some cases, cost is highly sensitive to composition specifications. Thus, the whole range of feasible composition specification should be thoroughly investigated to capture those that lead to the most economic design. For pressure-sensitive azeotropes, optimization of operating pressure should be considered, since the ranges of feasible composition specification can change considerably. We have also demonstrated that the use of double feed columns should be considered, even if extractive distillation is not needed, because the system can work in wider composition specifications and an additional degree of freedom can be exploited for optimizing column profiles. This work highlights the utility of thinking in terms of singular point types and RCM topology while synthesizing distillation sequences for nonideal mixtures compared to thinking in terms of boiling point order. Finally, a systematic design of a heterogeneous azeotropic distillation sequences can proceed as follows: 1. Select an entrainer either through Computer-Aided Molecular/Mixture Design (CAMD), from a databank, or from a list of benign materials (nontoxic, nonhazardous, etc.). The catalog presented in Figure 3 can be helpful. The designer might select the type of split he/she wants in the main task and look for which RCM class allows such a split. Then, search for the entrainer whose interactions with the binary feed constituents lead to this RCM. 2. Calculate the temperature sequence to identify the DRD and consequently the MN class of the mixture. 3. Identify the main task to separate component A using Figure 3. 4. Establish feasibility constraints, based on the type of singular points to be split in this task (node-node, node-saddle, or saddle-saddle), as shown in section 4. 5. Start the design and optimization, taking into account the sensitivities shown in section 5. Acknowledgment We gratefully acknowledge the financial support of MECD (Spain, Scholarship No. 2019-2001). We also thank Dr. Megan Jobson for her collaboration during a research stay of A.S.M.

in the Department of Process Integration, UMIST, where COLOM and DISTIL were available. Nomenclature A ) binary feed constituent that does not form a heterogeneous azeotrope with the entrainer B ) binary feed constituent that does form a heterogeneous azeotrope with the entrainer Ci ) mass balance line of column i DTi ) distillation task i D ) decantation task DRD ) distillation region diagrams E ) entrainer Fb ) binary feed Mi ) mixer i MN ) Matsuyama Nishimura’s classes N ) node, either stable or unstable RCM ) residue curve map S ) saddle SN ) stable node Sp ) splitter UN ) unstable node Literature Cited (1) Kiva, V. N.; Hilmen, E. K.; Skogestad, S. Azeotropic phase equilibrium diagrams: a survey. Chem. Eng. Sci. 2003, 58 (10), 19031953. (2) Wasylkiewicz, S. K.; Kobylka, L. C.; Castillo, F. J. L. Synthesis and design of heterogeneous separation systems with recycle streams. Chem. Eng. J. 2003, 92 (1-3), 201-208. (3) Davydyan, A. G.; Malone, M. F.; Doherty, M. F. Boundary modes in a single feed distillation column for the separation of azeotropic mixtures. Theor. Found. Chem. Eng. 1997, 31 (4), 327-338. (4) Doherty, M. F.; Malone, M. F. Conceptual design of distillation systems; McGraw-Hill: Boston, 2001. (5) Doherty, M. F.; Perkins, J. D. On the dynamics of distillation processes. 1. The simple distillation of multicomponent non-reacting, homogeneous liquid-mixtures. Chem. Eng. Sci. 1978, 33 (3), 281-301. (6) Doherty, M. F.; Perkins, J. D. On the dynamics of distillation processes. 2. The simple distillation of model solutions. Chem. Eng. Sci. 1978, 33 (5), 569-578. (7) Laroche, L.; Bekiaris, N.; Andersen, H. W.; Morari, M. Homogeneous azeotropic distillationsComparing entrainers. Can. J. Chem. Eng. 1991, 69 (6), 1302-1319. (8) Laroche, L.; Bekiaris, N.; Andersen, H. W.; Morari, M. The curious behavior of homogeneous azeotropic distillationsImplications for entrainer selection. AIChE J. 1992, 38 (9), 1309-1328. (9) Bauer, M. H.; Stichlmair, J. Synthesis and optimization of distillation sequences for the separation of azeotropic mixtures. Comput. Chem. Eng. 1995, 19, S15-S20. (10) Frey, T.; Bauer, M. H.; Stichlmair, J. MINLP-optimization of complex column configurations for azeotropic mixtures. Comput. Chem. Eng. 1997, 21, S217-S222. (11) Tassios, D. P. Extractive and azeotropic distillationsPreface. AdV. Chem. Ser. 1972, No. 115, R9-R11. (12) Diamond, D.; Hahn, T.; Becker, H.; Patterson, G. Improving the understanding of a novel complex azeotropic distillation process using a simplified graphical model and simulation. Chem. Eng. Process. 2003, 43 (3), 483-493. (13) Keller, G. E.; Bryan, P. F. Process engineering: moving in new directions. Chem. Eng. Prog. 2000, 96 (1), 41-50. (14) Harold, M. P.; Ogunnaike, B. A. Process engineering in the evolving chemical industry. AIChE J. 2000, 46 (11), 2123-2127. (15) Barnicki, S. D.; Siirola, J. J. Process synthesis prospective. Comput. Chem. Eng. 2004, 28 (4), 441-446. (16) Yeomans, H.; Grossmann, I. E. Disjunctive programming models for the optimal design of distillation columns and separation sequences. Ind. Eng. Chem. Res. 2000, 39 (6), 1637-1648. (17) Shah, P. B.; Kokossis, A. C. New synthesis framework for the optimization of complex distillation systems. AIChE J. 2002, 48 (3), 527550.

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ReceiVed for reView October 27, 2005 ReVised manuscript receiVed March 13, 2006 Accepted March 29, 2006 IE051196K

Entrainer Selection and Systematic Design of Heterogeneous

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