Design of Alternative Purification Processes for Potassium Sulfate

Experimental data on the solubility and particle size distribution were obtained for use in the conceptual design of a drowning-out crystallization pr...
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Ind. Eng. Chem. Res. 2005, 44, 5845-5851

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RESEARCH NOTES Design of Alternative Purification Processes for Potassium Sulfate M. E. Taboada and L. A. Cisternas* Departamento de Ingenieria Quimica, Universidad de Antofagasta, Casilla 170, Antofagasta, Chile

Y. S. Cheng and K. M. Ng Department of Chemical Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong

Experimental data on the solubility and particle size distribution were obtained for use in the conceptual design of a drowning-out crystallization process for the purification of potassium sulfate in an aqueous feed. This process is compared to the conventional evaporative crystallization process in terms of equipment cost, energy requirement, process flows, and product crystal quality. 1. Introduction Potassium sulfate is an important fertilizer for chloridesensitive crops. A common production route is through the reaction of potassium chloride and a double salt, scheoenite (K2SO4‚MgSO4‚6H2O) or langbeinite (K2SO4‚ 2MgSO4).1 Irrespective of its source, potassium sulfate is often refined by evaporative crystallization. Considerable energy consumption is associated with this evaporation process because of the heat of evaporation for solvent removal. As an alternative, it is highly desirable to consider drowning-out crystallization, which can be carried out at ambient temperature. For such a process, it is important to evaluate factors such as the miscibility of the drowning-out solvent with the existing solvent, the solubility of the solute in the drowning-out solvent, the cost for separating the drowning-out solvent from the existing solvent, etc. These issues were covered by Berry et al.,2 who presented a procedure for the synthesis of a crystallization separation process based on drowning-out phenomena. The major tradeoffs and process limitations of drowning-out crystallization were examined. Also, Weingaertner et al.3 studied in detail the purification of NaCl and Na2CO3 using various organic antisolvents such as propanol, butanol, and diisoproplyamine. A significant energy savings was found with respect to a triple-effect evaporation plant. Similarly, the conceptual design for the drowning-out crystallization of sodium carbonate using poly(ethylene glycol) was studied.4 The objective of this research is to design a drowningout crystallization process and compare it with evaporative crystallization. The effectiveness of two drowningout agents, 1-propanol and 2-propanol, was also compared in this study. To support process design, a solid-liquidphase equilibrium (SLE) diagram of potassium sulfate, water, and antisolvent was determined by experiments. Also measured are the particle size distributions (PSDs) * To whom correspondence should be addressed. Tel.: 5655-637323. Fax: 56-55-637801. E-mail: [email protected].

of the crystals resulting from both evaporative and drowning-out crystallization, which can affect the cost of the downstream filter. 2. Experimental Procedure and Results The performance of a crystallization process is governed by the thermodynamic behavior of the salt and solvents. Therefore, to begin the process synthesis, the isobaric-isothermal SLE data of the system are needed. The SLE data of a potassium sulfate + water + 1-propanol system at several temperatures were collected from experiments. The detailed procedure will be described in section 2.1. In addition, Wibowo and coworkers5 had pointed out that the PSD of crystals plays an important role in the design of downstream processes. It has high influences on the cake porosity and permeability, which directly impact the work load of the filter and the downstream processes. The identity of the drowning-out solvents also affects the PSD of the crystals. Experiments were carried out to investigate these ideas. Their impact on the purchase price of the filter used in the downstream processes will be discussed in later sections. Most importantly, the performance of the drowning-out crystallization will be compared with that of an evaporative crystallization process. 2.1. SLE Data of the Ternary System. The isothermal SLE data of the ternary system at 25, 35, and 45 °C were measured using a rotary and thermostatically controlled water bath with a holder containing eight 90-mL glass jars. The system works in the range of 20-90 °C, with a precision of 0.1 °C. Anhydrous potassium sulfate (99% pure), absolute 1-propanol (99.5% pure), and distilled water with a conductivity of 0.05 µS/cm were used in this study. Sixteen mixtures of alcohol/water with mass ratios ranging from 0 to 1.2 were prepared in triplicate. Each mixture was stirred at the desired temperature for 48 h until equilibrium and then left to settle for another 12 h. The solid in the mixture was recovered by filtration and then dried at 120 °C. The amount of

10.1021/ie0503390 CCC: $30.25 © 2005 American Chemical Society Published on Web 06/14/2005

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Figure 1. Ternary isothermal phase diagram of a K2SO4 + 1-propanol + H2O system at T ) 25, 35, and 45 °C.

dissolved potassium sulfate in the saturated solution was taken to be the weight difference between the total potassium sulfate in the system and the dry crystals recovered. The identity of the crystals was checked using X-ray diffraction. A total of 16 sets of saturation data of potassium sulfate were collected at each temperature of 25, 35, and 45 °C. The results of the ternary isothermal phase diagram of a K2SO4 + 1-propanol + H2O system at 25, 35, and 45 °C are shown in Figure 1. It can be seen that the solubility of potassium sulfate decreases with an increase in the 1-propanol concentration, and similar trends were obtained at three different temperatures. On the basis of these results, an empirical correlation of the solubility of potassium sulfate, S (wt % of solute/wt of the total solution), concentration of 1-propanol, P (wt % of 1-propanol/wt of the total solution), and temperature, T (°C), was developed:

S)

6.514 - 0.138P + 0.071T 1 + 0.057P - 0.00716T

(1)

Mydlarz et al.6 published the density and solubility data of K2SO4 in a water + 2-propanol mixture between 20 and 30 °C. Similarly, a solubility correlation was developed for use in design calculations.

S)

6.967 - 0.316P + 0.173T 1 + 0.076P + 0.00172T

(2)

For consistency, all solubilities or concentrations throughout the paper will be presented in wt % of solute/ wt of the total solution. 2.2. PSD. Separate experiments of drowning-out crystallization using either 1-propanol or 2-propanol as the drowning-out solvent were performed. The reagents used for these solutions included potassium sulfate pa (99%, Merck) and propanol pa (99.5%, Merck). Prior to use, potassium sulfate was dried in an oven at 120 °C for 24 h. Distilled and deionized water used for the solutions has a conductivity of >0.05 µS/cm. Then, 83.55 g of potassium sulfate was dissolved in 759.58 g of water at 25 °C in a closed 2000-mL jacketed crystallizing vessel with deflectors, which is equipped with a helical stirrer. The solution temperature of 25 °C was maintained using an in-vessel heat exchanger whose temperature was regulated by water circulated from an external thermostatically controlled water bath. The stirring speed was maintained, in all cases, at 500 rpm. Next, 200 g of a solution of 70:30 1-propanol/water

Figure 2. (a) PSD and (b) cumulative PSD of K2SO4 crystals from drowning-out crystallization processes using 1-propanol and 2-propanol as drowning-out solvents.

weight ratio was then added to the system to induce precipitation at the rate of 60 mL/min. Stirring was maintained for 15 min; after that, the solution was allowed to stand for 15 min. The solution was then vacuum-filtered off, and the remaining crystals were airdried at 70 °C in a rotary system to avoid agglomeration. Experiments were repeated using an aqueous solution of 90 wt % 1-propanol and 70 wt % 2-propanol. Each experiment was carried out in duplicate. The dry crystals were sieved into 12 size ranges and weighed: 600 µm. The PSDs and the cumulative PSDs of potassium sulfate crystals produced from the three experiments are shown in Figure 2a and 2b, respectively. As can be seen, 70% 1-propanol and 2-propanol gave similar distributions with mean sizes of 106 and 130 µm, respectively. Smaller crystals were obtained with the 90 wt % 1-propanol solution. PSD data of crystals from evaporative crystallization were also obtained (Figure 3a,b). In this case, the dried crystals were sieved into 13 ranges: 1000 µm. A much wider distribution was observed with a mode at 600-850 µm. Clearly, evaporation crystallization produces larger crystals, with a mean size of approximately 450 µm.

Ind. Eng. Chem. Res., Vol. 44, No. 15, 2005 5847 Table 1. Material Balances for the 1-Propanol Processa mass flow, kg/h

w/w %

stream

temp, °C

flow rate, kg/h

density, g/cm3

K2SO4(s)

K2SO4(aq)

C3H8O

H 2O

K2SO4(s)

K2SO4(aq)

C3H8O

H2O

enthalpy Q, Mcal/h

1 2 3 5 6 7 8 9 10 11′ 11 12′ 12 13 14

20 20 45 45 45 20 45 45 45 88 46 95 48 100 100

6 440 297 78 805 78 794 108 472 223 9 719 6 949 111 242 39 174 39 174 72 067 72 067 6 342 607

2.593 0.997 1.080 1.080 0.990 0.849 0.990 2.290 0.956 0.849 0.849 1.026 1.026 2.658 0.937

6337 0 0 0 0 0 6317 6317 0 0 0 0 0 6336 0

0 0 9637 9636 3218 0 101 19 3300 0 0 3300 3300 0 0

0 0 0 0 26 739 156 839 156 27 422 27 422 27 422 0 0 0 156

103 297 69 168 69 158 78 515 67 2 462 457 80 520 11 752 11 752 68 767 68 767 6 451

98.40 0.00 0.00 0.00 0.00 0.00 65.00 90.91 0.00 0.00 0.00 0.00 0.00 99.91 0.00

0.00 0.00 12.23 12.23 2.97 0.00 1.04 0.27 2.97 0.00 0.00 4.58 4.58 0.00 0.00

0.00 0.00 0.00 0.00 24.65 70.00 8.63 2.24 24.65 70.00 70.00 0.00 0.00 0.00 25.70

1.60 100.00 87.77 87.77 72.38 30.00 25.34 6.58 72.38 30.00 30.00 95.42 95.42 0.09 74.30

12 893.7 1 128.1 279 665.7 279 626.3 334 092.4 440.1 22 911.3 14 380 342 622.6 76 774.4 64 571.2 265 643.9 262 432.6 12426.2 1 585.1

a

K2SO4(s): crystallized potassium sulfate. K2SO4(aq): aqueous potassium sulfate.

Figure 3. (a) PSD and (b) cumulative PSD of K2SO4 crystals from the evaporative crystallization process.

3. Conceptual Design 3.1. Drowning-Out Crystallization Process. A drowning-out crystallization process to purify potassium sulfate using either 1-propanol or 2-propanol as the drowning-out agent was designed (Figure 4a). Figure 4b shows the process paths on the H2O + 1-propanol +

K2SO4 ternary diagram. Tables 1 and 2 summarize the material balance and enthalpy data for the two processes. The process would produce 6336 kg/h of pure potassium sulfate (stream 13), with 1-propanol as the antisolvent. Impure potassium sulfate crystals (stream 1) are fed to the dissolver, together with the recycle stream 12. The dissolver effluent (stream 3) is then filtered to remove insoluble particles, which are assumed to be the only impurity in the system. A makeup stream of a 70 wt % 1-propanol aqueous solution (stream 7), together with distillate (stream 11), is added to the salt solution (stream 5) to induce the precipitation of K2SO4 in the crystallizer. This crystallizer has two outlets: one mother liquid outlet (stream 6) and one slurry outlet (stream 8). The slurry enters the downstream process that is composed of a filter and a dryer. Wet K2SO4 crystals (stream 9) are filtered out, and the filtrate stream (stream 10) combined with stream 6, is then fed to a distillation column. A total of 3300 kg/h of dissolved potassium sulfate is collected at the bottoms. The bottoms stream (stream 12) is recycled to the dissolver. Normally, a trace amount of heavy impurity is present and is purged (stream 17) at the bottoms stream. This amount is ignored in our material balances. The distillate, which contains a 70 wt % 1-propanol solution (stream 11′), is recycled to the crystallizer after cooling. Finally, the pure potassium sulfate is recovered after drying, and the aqueous phase is vented (stream 15). A recycle (stream 16) could be considered if solvent loss is significant. If 90% solvent loss in stream 14 were recovered, the potential savings in material cost for 1-propanol and 2-propanol would be US$1 266 305/year and US$521 664/year, respectively. Furthermore, a computer code (HSC chemistry for windows) was used to calculate the enthalpy data listed in Table 1. The energy requirement in the distillation step is 15 618.8 Mcal/h. Energy integration was not attempted in this study. The same process design as that shown in Figure 4a was applied to the 2-propanol process, and the material balances are listed in Table 2. The energy consumption in the distillation step was 21 674.6 Mcal/h, which is higher than that of the 1-propanol process. 3.2. Traditional Evaporation Process. The traditional purification process of potassium sulfate is shown in Figure 5, and the material balances are listed in Table 3. Impure potassium sulfate (stream 1) is dissolved in 462 kg/h of freshwater (stream 2). The insol-

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Figure 4. (a) Schematic process flow diagram of purification of K2SO4 by drowning-out crystallization using 1-propanol as the drowningout agent and (b) the process paths depicted on an isothermal phase diagram at 45 °C. Table 2. Material Balances for 2-Propanol Processa mass flow, kg/h

w/w %

stream

temp, °C

flow rate, kg/h

density, g/cm3

K2SO4(s)

K2SO4(aq)

C3H8O

H2O

K2SO4(s)

K2SO4(aq)

C3H8O

H2O

enthalpy Q, Mcal/h

1 2 3 5 6 7 8 9 10 11′ 11 12′ 12 13 14

20 20 45 45 45 20 45 45 45 88 46 95 48 100 100

6 440 291 109 246 109 234 154 148 219 9 703 6 938 156 914 54 399 54 399 102 515 102 515 6 342 596

2.596 0.997 1.080 1.080 0.981 0.831 0.981 2.291 0.957 0.830 0.830 1.042 1.042 2.658 0.929

6337 0 0 0 0 0 6307 6307 0 0 0 0 0 6336 0

0 0 13 360 13 358 6 899 0 152 28 7 023 0 0 7 023 7 023 0 0

0 0 0 0 37 408 153 824 153 38 079 38 079 38 079 0 0 0 153

103 291 95 886 95 886 109 841 66 2 420 449 111 812 16 320 16 320 95 492 95 492 6 443

98.40 0.00 0.00 0.00 0.00 0.00 65.00 90.92 0.00 0.00 0.00 0.00 0.00 99.91 0.00

0.00 0.00 12.23 12.23 4.48 0.00 1.57 0.40 4.47 0.00 0.00 6.85 6.85 0.00 0.00

0.00 0.00 0.00 0.00 24.27 69.86 8.49 2.21 24.27 70.00 70.00 0.00 0.00 0.00 25.67

1.60 100.00 87.77 87.77 71.26 30.14 24.94 6.47 71.26 30.00 30.00 93.15 93.15 0.09 74.33

12 894.0 1 104.0 387 696.0 387 656.7 474 681.7 443.6 22 872.5 14 327.6 483 198.4 92 310.6 109 455.8 369 213.3 373 699.0 12 426.2 1 568.3

a

K2SO4(s): crystallized potassium sulfate. K2SO4(aq): aqueous potassium sulfate.

Ind. Eng. Chem. Res., Vol. 44, No. 15, 2005 5849

Figure 5. Schematic diagram of a traditional evaporative crystallization process to purify K2SO4. Table 3. Material Balance for the Evaporation Processa mass flow, kg/h

w/w %

stream

temp, °C

flow rate, kg/h

density, g/cm3

K2SO4(s)

K2SO4(aq)

H 2O

K2SO4(s)

K2SO4(aq)

H 2O

enthalpy Q, Mcal/h

1 2 3 5 6 7 8 9 10 11 12 13

20 20 45 45 80 100 49 100 100 45 100 100

6 440 462 51 820 51 732 51 732 44 917 44 917 9 745 2 930 6 815 474 6 340

2.593 0.997 1.080 1.080 1.080 0.997 0.997 1.844 1.209 2.381 0.997 2.658

6337 0 0 0 0 0 0 6334 0 6334 0 6334

0 0 6337 6334 6334 0 0 822 822 0 0 0

103 462 45 483 45 398 45 398 44 917 44 917 2 589 2 108 481 474 6

98.40 0.00 0.00 0.00 0.00 0.00 0.00 65.00 0.00 92.94 0.00 99.91

0.00 0.00 12.23 12.24 12.24 0.00 0.00 8.44 28.05 0.00 0.00 0.00

1.60 100.00 87.77 87.76 87.76 100.00 100.00 26.56 71.95 7.06 100.00 0.09

12 893.8 1 755.4 183 899.5 183 575.5 182 061.8 14 595.4 169 250.3 23 638.5 9 451.2 14 282.1 1 506.2 12 423.8

a

K2SO4(s): crystallized potassium sulfate. K2SO4(aq): aqueous potassium sulfate.

uble particles (stream 4) are separated by filtration in the next step. The filtrate (stream 5) is preheated to 80 °C in the heat exchanger by water vapor (stream 7) coming from the evaporator, and it is sent to the evaporative crystallizer. The slurry (stream 9), with a magma density of 1.86 kg of solid/kg of liquid, from the evaporator is sent to the second filter. Finally, 6334 kg/h of pure potassium sulfate is obtained in the dryer. The energy requirement in the evaporation step is 25 279.1 Mcal/h, which is considerably higher than that in the drowning-out process.

Table 4. Comparison of the Production Parameters and Cost Evaluation of the Drowning-Out Crystallization and Evaporation Processes

4. Comparison of Process Alternatives

Energy Requirements energy (Mcal/year) 27535012 23788188 energy cost (US$/year) 186585 160352

Let us compare the three process alternatives for a production rate of 50 000 tons/year in terms of energy requirements and capital costs. Table 4 summarizes the key production parameters and costs. The raw material and utility costs are shown in Table 5. 4.1. Equipment Cost. Leaving out the auxiliary units, the traditional evaporation process has five major equipment items, while the drowning-out crystallization process has six. The costs for the dissolver, the first filter for the insoluble impurity, the crystallizer, and the dryer are expected to be approximately the same. There will be two significantly different costs: the second filter downstream of the crystallizer and the distillation column that is used in the drowning-out process. These are calculated as follows. Filter. Darcy’s law for single-phase flow through porous media is

Q ) A

∆P x µ + Rm k

(

)

(3)

where Q is the volumetric flow rate of the filtrate in

process 1-propanol 2-propanol evaporation Plant Dimensions sum of flow rates (tons/h) 637.1 771.6 no. of equipment 6 6 water (tons/year) 1-propanol (tons/year) 2-propanol (tons/year)

Inputs 2869.8 1229.9 0.0

2814.6 0.0 1206.3

Equipment Purchase Pricesa rotary vacuum filter (US$) 92000 93000 filter area (m2) 2.16 2.37 distillation column (US$) 176000 232000 column diameter (m) 3.02 3.24 no. of trays 16 18 column height (m) 9.63 10.84

278.3 5 3642.4 0.0 0.0 43494987 293156 84000 0.52

a The prices are updated to year 2003 using the Marshall & Swift equipment index of 2003 ()1123.6).

m3/s, A is the filtration area in m2, and ∆P is the pressure difference across the filter. The filter area depends on the cake thickness, x (m), the cake porosity, , the permeability, k (m2/s), the specific resistance of the filter, Rm (m-1), and the viscosity of the mother liquor, µ (kg/m‚s). The permeability can be determined from the modified Blake-Kozeny equation:7

k)

( )

M2 3 1 2 180 (1 - ) M1

2

)

3 1 D2 180 (1 - )2 p

(4)

where M1 and M2 are the first and second moments of

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Table 5. Costs and Selling Prices of Raw Materials and Final Products item

value

K2SO4 impure (US$/ton) K2SO4 pure (US$/ton) 1-propanol (US$/ton) 2-propanol (US$/ton) industrial water (US$/ton) natural gas (US$/Mcal)

135 220 1144 480.5 1 6.74 × 10-3

process column dimensions column diameter (m) no. of trays (stainless steel bubble-cap tray) column height (m) purchase price (US$)

Table 6. Cake Properties and Filter Areas in Each Process 1-propanol mean particle size, Dp (m) porosity,  permeability, k (m2) solid density (kg/m3) cake thickness (m)

2-propanol

evaporation

Cake Properties 1.06 × 10-4 1.30 × 10-4

4.50 × 10-3

0.377 7.14 × 10-12 2662 0.12

0.336 1.06 × 10-11 2662 0.12

0.383 6.17 × 10-12 2662 0.12

Filtrate Properties filtrate flow rate, 0.0323 0.0456 Q (m3/s) viscosity, µ (kg/ms) 0.001 0.001 liquid density (kg/m3) 990 981

8.51 × 10-4 0.001 1209

Filter Parameters pressure difference, 35000 35000 ∆P (Pa) -1 10 filter resistance (m ) 1× 10 1× 1010 filter area, A (m2) 2.16 2.37

35000 1× 1010 0.52

the PSD, respectively. The cake porosity can be calculated using the following correlation developed by Ouchiyama and Tanaka:8 m

)1-

∑ i)1

m

(1/n j)

/{∑ m

Di3fi

(Di - 〈D〉)3H(Di - 〈D〉)fi +

}

i)1

[(Di + 〈D〉)3 - (Di - 〈D〉)3H(Di - 〈D〉)]fi ∑ i)1

(5)

where

n j)1+ m

4(7 - 8j)〈D〉 0 13

(

m

〈D〉

3

(Di + 〈D〉)2 1 ∑ 8D i)1

i

)

+ 〈D〉

Table 7. Dimensions and Purchase Prices of the Distillation Columns for the Two Drowning-Out Crystallization Processes

fi (6)

[Di3 - (Di - 〈D〉)3H(Di - 〈D〉)]fi ∑ i)1

Here, fi is the number fraction of particles in interval i; 0 is the average porosity of uniformly sized spheres, which is assumed to be 0.4 in this case. H is the Heaviside function. Di and 〈D〉 are the particle size in interval i and the mean particle diameter, respectively. The number fraction for each size interval and the mean size can be calculated from the PSD data. The values of these parameters are summarized in Table 6. We assume that a rotary vacuum filter operating under vacuum at ∆P ) 35 000 Pa is used in the process. Rm is assumed to be 1 × 1010 m-1. With those parameters, the filter areas are 2.16 and 2.37 m2 for the drowningout crystallization using 1-propanol and 2-propanol as the drowning-out solvents, respectively. These are about 4 times larger than the filter that has an area of 0.52 m2 for the evaporative process.

1-propanol

2-propanol

3.02 16

3.24 18

9.63 176 000

10.84 232 000

The purchase price of the rotary vacuum filter could be estimated using the correlations in eq 7 with the base year of 1985 (Marshall & Swift Index ) 789.6 as quoted in Chemical Engineering).9 The updated purchase prices for year 2003 (Marshall & Swift Index ) 1123.6 as quoted in Chemical Engineering) of the filters for the 1-propanol, 2-propanol, and evaporation processes are US$92 000, US$93 000, and US$84 000, respectively (Table 4).

C ) exp[11.27 - 1.3408(ln A) + 0.0709(ln A)2] 10 < A < 1500 ft2 (7) Distillation Column. The purchase price of the distillation columns was estimated based on the Fenske-Underwood-Gilliand method and the procedure suggested by Peters et al.10 The calculated column dimensions and purchase prices are listed in Table 7. If tray columns with bubble-cap trays made of stainless steel 304 were used, their purchase prices would be about US$176 000 and US$232 000 for 1-propanol and 2-propanol processes, respectively. 4.2. Energy Consumption. It can be seen in Table 4 that the evaporation process employs 57% more energy than the 1-propanol process and 82% more than the 2-propanol process. Because the energy requirement of the evaporation process is significantly higher, natural gas with a relatively low cost of US$6.47 × 10-3/ Mcal is used for all of these processes. Heat integration, particularly those that allow the use of multieffect structures such as multieffect distillation and multieffect evaporation, can reduce the utility use, but a higher capital cost is necessary. For example, if a tripleeffect evaporator is used to replace the single-effect evaporator, the energy consumption will be reduced to approximately one-third of that for the single-effect evaporator. 4.3. Comparison of Drowning-Out Agents. The two drowning-out agents are compared in terms of consumption, price, and crystal quality. As shown in Table 4, approximately the same amount of 1-propanol and 2-propanol is required because the potassium sulfate solubility behavior in the two solvents is similar. Also, the product crystals have similar PSDs. Yet, 1-propanol is 58% more costly than 2-propanol. 5. Conclusions A drowning-out crystallization process has been designed based on experimental solubility and crystal size distribution data. We found that drowning-out crystallization using 1-propanol or 2-propanol as drowning-out agent could realize 35-45% energy savings compared to the conventional evaporative crystallization process. Although the energy consumption of the evaporation process could be reduced by two-thirds if a triple-effect evaporator is used, it results in a higher capital cost.

Ind. Eng. Chem. Res., Vol. 44, No. 15, 2005 5851

However, the drowning-out crystallization process has two major disadvantages. It requires a distillation column to recover and recycle the antisolvent, thus incurring additional capital cost. The crystals from the drowning-out process are much smaller than those from the evaporative crystallization process. This is not unexpected because of the difficulty in avoiding excessive supersaturation in drowning-out crystallization. However, this has led to the need for a large filter. We conclude that the choice of one process over the other depends on the energy cost at the plant site. There is not a definite winner. This study has discussed some of the important issues related to the process synthesis of crystallization processes for the purification of potassium sulfate, a simple salt. Similar issues are expected for crystallization processes of organics, chiral compounds, polymorphs, etc. Also, no attempt was made to perform energy integration, optimization of filtration, crystallization operations, etc. Further efforts in these directions are underway. Acknowledgment The authors thank CONICYT for financing of this study (FONDECYT Projects 1020892 and 1011049). Additional support from the Research Grant Council DAG03/04 is also gratefully acknowledged. Literature Cited (1) Kroschwiz, J. I.; Howe Grant, M. Encyclopedia of chemical technology, 4th ed.; Wiley: New York, 1991; Vol. 19; pp 10581092.

(2) Berry, D. A.; Dye, S. R.; Ng, K. M. Synthesis of DrowningOut Crystallization-Based Separations. AIChE J. 1997, 43 (1), 91103. (3) Weingaertner, D. A.; Lynn, S.; Hanson, D. N. Extractive Crystallization of Salts from Concentrated Aqueous Solution. Ind. Eng. Chem. Res. 1991, 30 (3), 490-501. (4) Taboada, M. E.; Graber, T. A.; Cisternas, L. A. Sodium Carbonate Extractive Crystallization with Poly(ethylene glycol) Equilibrium Data and Conceptual Process Design. Ind. Eng. Chem. Res. 2004, 43 (3), 835-838. (5) Wibowo, C.; Chang, W. C.; Ng, K. M. Design of Integrated Crystallization Systems. AIChE J. 2001, 47 (11), 2474-2492. (6) Mydlarz, J.; Jones, A. G.; Millan, A. Solubility and Density Isotherms for Potassium Sulfate-Water-2-Propanol. J. Chem. Eng. Data 1989, 34 (1), 124-126. (7) MacDonald, M. J.; Chu, C. F.; Guilloit, P. P.; Ng, K. M. A Generalized Blake-Kozeny Equation for Multisized Spherical Particles. AIChE J. 1991, 37 (10), 1583-1588. (8) Ouchiyama, N.; Tanaka, T. Porosity Estimation for Random Packings of Spherical Particles. Ind. Eng. Chem. Fundam. 1984, 23, 490. (9) Walas, S. M. Chemical Process EquipmentsSelection and Design; Butterworth-Heinemann: Newton, MA, 1988; p 667. (10) Peters, M. S.; Timmerhaus, K. D.; West, R. E. Plant Design and Economics for Chemical Engineers, 5th ed.; McGraw-Hill: London, 2003.

Received for review March 14, 2005 Revised manuscript received May 9, 2005 Accepted May 23, 2005 IE0503390