Process for Glycine Production by Antisolvent Crystallization Using Its

Feb 5, 2016 - Simulation for the new process was performed by the model to investigate ... the glycine manufacturing are also incorporated in the flow...
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Process for Glycine Production by Antisolvent Crystallization Using Its Phase Equilibria in the Ethylene Glycol−NH4Cl−Water System Yan Zeng,†,‡ Zhibao Li,*,† and George P. Demopoulos‡ †

Key Laboratory of Green Process and Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China ‡ Department of Mining and Materials Engineering, McGill University, 3610 University Street, Montreal, Quebec H3A 2B2, Canada ABSTRACT: A new process for the production of glycine by using antisolvent crystallization with the mixture of ethylene glycol (MEG) and water as a substitute for methanol has been developed on the basis of chemical modeling phase equilibria for the glycine−NH4Cl−MEG−H2O system. MEG is considered as a green solvent because it has great higher boiling point up to 470 K and thus is almost nonvolatile compared with methanol. We discovered that the solubility of glycine, NH4Cl and their mixtures can be greatly changed by altering the composition of the mixed MEG−H2O solvents and realized the complete separation of glycine and NH4Cl by water evaporation. Phase equilibria for the glycine−NH4Cl−MEG−H2O system were measured from 278 to 353 K. The mixed-solvent electrolyte (MSE) model was applied with new binary interaction parameters obtained from regressing experimental and literature data. This newly modified model accurately predicted the solubilities in the quaternary glycine−NH4Cl−MEG−H2O system with average absolute relative deviations of 5.84% and 1.03% for glycine and NH4Cl, respectively. Simulation for the new process was performed by the model to investigate its operating conditions, from which the optimal composition of antisolvent was determined to be 50 wt % of MEG solution. Under this condition, glycine and NH4Cl were successfully separated from their solid mixtures in batch crystallization experiments, validating the feasibility of the proposed process for glycine production.

1. INTRODUCTION The usefulness of glycine (NH2CH2COOH) as building blocks for synthesis of a variety of natural and chemical products has made it an important organic compound in the food, pharmaceutical, chemical, and agricultural industries.1 China is the world’s main glycine producing country with an annual output of 600 000 tons and also a large consumer where more than 80% of the technical grade glycine is used as raw material for producing glyphosate, the mostly used herbicide.2 Among several common industrial synthesis methods, such as the monochloroacetic acid ammonolysis (MCA) process,3−5 the Strecker process6 and the hydantoin process,7 the MCA process has been predominantly adopted in the Chinese glycine manufacturing since 1980s due to its relatively simple technology, easily available raw materials, and low requirement for equipment. In the MCA process, glycine is formed with equal molar amount of ammonium chloride (NH4Cl) when treating monochloroacetic acid (ClCH2COOH, MCA) with excess amount of NH3 under the catalysis of hexamethylenetetramine (urotropine, HMTA) in aqueous mediums (eq 1).

lization is applied to crystallize glycine, and methanol is commonly used for this purpose in the industry.10,11 The mother liquor is then fed to the distillation section to recover methanol, whereas the bottom liquor mainly containing NH4Cl is left over. The existing MCA process has encountered several economic and environmental problems that will limit its utility in the upcoming future. First of all, the use of methanol is not only costly due to the energy-intensive distillation step but also damaging to both environment and operators because methanol is volatile, flammable, and highly toxic.12 In a local glycine factory, 20 tons of 80 wt % methanol is used to produce 1 ton of glycine. Nearly 5 tons of methanol are emitted to the surrounding environment; less than 15 tons of methanol can be finally regenerated by distillation. Second, the catalyst HMTA are failed to be effectively reused. Furthermore, a considerable amount of the byproduct NH4Cl, which have been contaminated by HMTA, are difficult to be separated from the residue, resulting in another severe pollution. Here we propose a new method, called the modified MCA (MMCA) process, for the production of glycine. In this process, aqueous ethylene glycol (MEG) instead of methanol is used as the antisolvent. As a nonvolatile green solvent, MEG is easier and safer to handle than methanol or other volatile alcohols and has been successfully adopted in the crystallization-based separation

HMTA

ClCH 2COOH + 2NH3 ⎯⎯⎯⎯⎯⎯→ NH 2CH 2COOH + NH4Cl (1)

Glycine has high solubility in water due to its very small sidechain of only one hydrogen atom.8 The separation of glycine and NH4Cl in aqueous solutions is hindered by their multiple saturation points which cannot be overcome by either cooling or evaporation.9 In order to isolate glycine, antisolvent crystal© 2016 American Chemical Society

Received: Revised: Accepted: Published: 2426

November 2, 2015 December 28, 2015 February 5, 2016 February 5, 2016 DOI: 10.1021/acs.iecr.5b04144 Ind. Eng. Chem. Res. 2016, 55, 2426−2437

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Industrial & Engineering Chemistry Research

previous work, was 2.2 mol·kg−1 solvent.17 This obvious difference in solubility indicates that MEG is a suitable antisolvent for separating glycine from NH4Cl. Phase equilibrium for the ternary glycine−NH4Cl−H2O system, which is encountered in the initial cooling step after reaction, was also investigated previously and will be useful to know the composition of the resulting mixed solid by cooling.9 The solubility of glycine at other temperatures and the phase equilibria for the quaternary glycine−NH4Cl−MEG−H2O system, however, are not available in the literature. Additionally, it has been proven by several researchers that the presence of NaCl in solutions increases the solubility of glycine.18,19 The solubility of NH4Cl, on the other hand, decreases with the increasing concentration of NaCl in aqueous solutions.20 Because the systems MEG−H2O with NaCl have been extensively studied relative to glycine and NH4Cl, the literature data for the NaCl−MEG−H2O system21 can be used to evaluate the modeling approach. Besides experimental measurements on the phase equilibria, process simulation with the aid of computer will be a reliable and efficient method to search for the optimal operating conditions including temperature adopted in each step and the concentration of the MEG−H2O mixture used in the antisolvent crystallization. First and foremost, a comprehensive thermodynamic model in calculating the activity coefficients and solubilities for the glycine−NH4Cl−NaCl−MEG−H2O system should be established. Three thermodynamic models that might be mostly applicable to this mixed solvent electrolyte system are22 the electrolyte nonrandom two-liquid model (eNRTL), the Extended UNIQUAC model, and the mixed-solvent electrolyte model (MSE). The eNRTL model developed by Chen et al. was proved to be successful in representing the solubility of several amino acids including glycine in the electrolyte and ethanol− water systems.23,24 In the eNRTL model, the excess Gibbs free energy (GE) consists of two contributions. One is the long-range interactions represented by the combination of the Pitzer− Debye−Hückel (PDH) equation25 and the Born equation.26 The other is the short-range interactions calculated by a modified form of the NRTL equation. The Extended UNIQUAC model, using only binary temperature-dependent interaction parameters, was also able to accurately represent the solid−liquid equilibrium (SLE) for the mixed-solvent electrolyte systems.27,28 The Extended UNIQUAC model combines the extended Debye−Hückel equation29 with the UNIQUAC model30 to take into account the long-range and short-range interactions. Referring to the MSE model, the UNIQUAC is used to represent the short-range interactions and the PDH equation to represent long-range terms.31,32 Additionally, a middle-range term calculated by an ionic strength-dependent symmetrical second virial coefficient-type equation was added to the MSE model to take account of specific ion−ion and ion−molecule interactions. Furthermore, the MSE model combines the excess Gibbs free energy model simultaneously with computation for speciation that results from chemical equilibrium reactions. The robustness of the MSE model for calculating complex phase behavior of mixed-solvent systems containing multiple salts was verified by many researchers including Lin et al., who made a comparison among the three models mentioned above.22 The study from Wang et al.21 on the application of the MSE model to calculate thermodynamic and transport properties of various systems containing MEG and various single or multiple salts further demonstrates the capability of the MSE model in representing solubilities for these types of systems.

Figure 1. Flow sheet of the newly proposed MMCA process for the production of glycine.

of many products such as sodium carbonate and magnesium chloride.13−15 The flow sheet of the proposed MMCA process is shown in Figure 1. Although this study does not focus on the synthesis reactions for preparing glycine and its raw material monochloroacetic acid (MCA), the commonly adopted routes in the glycine manufacturing are also incorporated in the flow sheet. As illustrated in Figure 1, MCA is prepared from the chlorination of acetic acid (CH3COOH), with sulfur as a catalyst (eq 2). S

CH3COOH + Cl 2 → ClCH 2COOH + HCl

(2)

The resulting MCA aqueous solution is then treated with NH3 and HMTA to generate concentrated solution of glycine and NH4Cl. A solid mixture of glycine and NH4Cl will be obtained by cooling and filtering. The mother liquor is returned to the glycine synthesis step so that in this way the catalyst HMTA can be recycled. The separation of glycine and NH4Cl in the solid mixtures is then carried out through three steps. Step 1 is the antisolvent crystallization by adding the MEG−H2O mixed solvent under ambient conditions to dissolve completely NH4Cl and then separate pure solid glycine. Step 2 involves the evaporation of the filtrate from step 1 to remove water, resulting in the crystallization of the solid mixture in which NH4Cl accounts the dominant portion. The aqueous MEG solution is regenerated as feed in next run. Step 3 is the dissolution of glycine in the solid mixture obtained from step 2. Pure solid NH4Cl is therefore separated, whereas the filtrate could be fed to next run to harvest more glycine and NH4Cl. Design and development of the crystallization-based MMCA process require comprehensive knowledge of the solid−liquid equilibria (SLE) for glycine and NH4Cl in the MEG aqueous solutions over wide concentration and temperature ranges. Solubility of glycine in MEG−H2O mixtures with MEG concentration from 0 to 90.5 wt % (salt-free) at 298.25 K was measured by Nozaki and Tanford in 1965.16 It was reported in their study that the solubility of glycine in 90.5 wt % MEG aqueous solution was 0.18 mol·kg−1 solvent. The solubility of NH4Cl in 90 wt % MEG at 298 K, which was determined in our 2427

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determined by drying and weighing in other experiments, and was found to be 7 wt %. The wet solid mixture was returned to the reactor. The prepared mixed solvent with 50 wt % of MEG was introduced to the reactor by using a peristaltic pump at a flow rate of 20 mL·min−1. The temperature was kept constant at 298.15 K. After 12 h, the slurry was filtered and thereafter the solid was washed with methanol and dried in an oven at 393.15 K for 12 h. The filtrate was evaporated to remove water, and slowly cooled to room temperature to separate the solid by filtration. The resulting solid was partially dissolved in water at 333.15 K. Finally, the undissolved solid was filtrated, washed, and dried. Crystalline phases of solids obtained in each step were confirmed by XRD. The crystal morphology was characterized by scanning electron microscopy (SEM, JEOL-JSM-6700F).

In the present study, the solubility of glycine in the MEG−H2O mixed solvent is measured from 278.15 to 353.15 K for solvents containing 0 to 1 mole fraction of MEG. Phase equilibria for the glycine(s)−NH4Cl(s)−MEG−H2O and the glycine(s)−NaCl− MEG−H2O systems containing 60 and 90 wt % of salt-free MEG from 278.15 to 353.15 K are also measured. These experimental data are used together with those reported in literature to develop a set of MSE model parameters that are capable of calculating SLE for systems involved in the MMCA process. Effects of temperature and the antisolvent concentration on the yield of glycine and the corresponding consumption of MEG solvent in the MMCA process are investigated systematically by the new model and thereby optimal operating conditions are selected. Batch crystallization experiments are finally carried out to validate the feasibility of the proposed MMCA process and the reliability of the modeling method as a tool in process development.

3. THERMODYNAMIC MODELING FRAMEWORK 3.1. Chemical Equilibrium Relationships. Glycine can be dissolved in solution partly as the zwitterion (+NH3CH2COO−) and partly as the cation (+NH3CH2COOH) and anion (NH2CH2COO−). In this study, only the zwitterionic form was considered because it is the predominant glycine species in isoelectric solutions.24,33−35 To establish a speciation-based thermodynamic model for the glycine−NH4Cl−NaCl−MEG− H2O system, the following dissolution reactions are mainly considered.

2. EXPERIMENTAL SECTION 2.1. Chemical Agents. Glycine (99.8% purity) was supplied by the Sinopharm Chemical Reagent Co., Ltd. Ammonium chloride (NH4Cl, 99.5% purity), sodium chloride (NaCl, 99.5% purity), and ethylene glycol (MEG, 99.5% purity) were supplied by Xilong Chemical Plant. All chemical reagents were used without further purification. Deionized water with a conductivity less than 0.1 μS·cm−1 produced in local laboratory was used in all the experiments. 2.2. Solubility Determination. Determination of solubilities for the glycine(s)−MEG−H2O, glycine(s)−NH4Cl(s)− MEG−H2O, and the glycine(s)−NaCl−MEG−H2O systems was carried out by a dynamic method. The investigated temperature range was from 278.15 to 353.15 K. All the chemical reagents were weighed with an electronic balance with an uncertainty of ±0.001 g. In a typical experiment, pure water and ethylene glycol were weighed and added to a 250 mL jacketed quartz vessel. The vessel was tightly sealed, equipped with a Teflon-covered magnetic stirring bar, and placed on a stirring magnetic plate to ensure agitation. Circulating water bath afforded thermostatic water through the vessel jacket (controlled to within ±0.1 K). One salt with weighed amount was dissolved in the mixed solvent when the effect of electrolyte concentrations was investigated. The salt under determination was then added to the solution with an initial amount equal to 50% of its predicted solubility. More doses of salts were added to the solution little by little. The addition was stopped when observing a trace of solid was remained undissolved for 6 h. The total mass of the solids added prior to the final addition is its solubility for a given condition. Each experiment was replicated three times, and the data reported are the averages of the replicates. When the solubility measuments were completed, excess salt was added to the saturated solution. After 6 h of equilibration, the solid was filtered, washed, dried, and then characterized by the X-ray diffraction (XRD, X’Pert PRO MPD, PANalytical). 2.3. Batch Crystallization. The batch crystallization experiments were carried out in a 2 L glass reactor, which was equipped with a propeller and connected with a thermostatic water bath. An aqueous solution containing 10 mol·kg−1 of glycine and 10 mol·kg−1 of NH4Cl was prepared in the reactor at 353.15 K. This solution composition is similar to that obtained from MCA ammonolysis reaction. The stirrer speed was set to 300 rpm. The solution was then slowly cooled to 283.15 K at a rate of 10 K·h−1. By filtration, a solid mixture of glycine and NH4Cl was obtained. The weight percent of the adhering water in the solid mixture was

NH 2CH 2COOH(s) ↔ + NH3CH 2COO−

(3)

NH4Cl(s) ↔ NH4 + + Cl−

(4)

NaCl(s) ↔ Na + + Cl−

(5)

The respective equilibrium constants for the above reactions above are K NH 2CH2COOH = a+ NH3NH2COO− = γ+NH NH COO−·m+NH3NH 2COO− 3

2

(6)

K NH4Cl = a NH4+ ·aCl− = (γNH +·m NH4+) ·(γCl−·mCl−)

(7)

KNaCl = a Na+ ·aCl− = (γNa+·m Na+) ·(γCl−·mCl−)

(8)

4

where a is the activity, γ is the activity coefficient, and m is the concentration in terms of molality. The equilibrium constant K is calculated from ln K = −

ΔR Go RT

(9)

where ΔRGo is the standard-state partial molal Gibbs free energy of reaction, which is ΔR Go =

∑ νiΔ Gfo i

(10)

where vi is the stoichiometric coefficient and Δ Gfo is the standardstate partial molal Gibbs free energy of formation for species i. In the MSE framework, Δ Gfo for aqueous species is calculated by the Helgeson−Kirkham−Flowers (HKF) equation of state.36−38 Seven HKF parameters (a1−a4, c1, c2, and ω) and related thermodynamic properties that are required in calculating equilibrium constants can be found in the literature and the databank of the OLI software. It should be mentioned that the molality-based standard-state properties have been converted to 2428

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Table 1. Experimental Solubility of Glycine in the MEG−H2O Mixed Solvents in the Temperature Range of 278.15 to 353.15 K and at Pressure p = 101.325 kPaa m(glycine), mol·kg−1 solvent x′(MEG)

b

wt % (MEG)

278.15 K

288.15 K

298.15 K

313.15 K

333.15 K

353.15 K

0.00 30.18 46.99 59.97 77.43 90.07 100.00

2.0111 0.9117 0.5356 0.3569 0.2020 0.0856 0.0924

2.7027 1.1910 0.6733 0.4588 0.2405 0.1219 0.0996

3.2440 1.5079 0.8834 0.5755 0.2998 0.1736 0.1150

4.3856 2.0795 1.1836 0.7943 0.3902 0.2609 0.1415

5.8068 3.0111 1.7422 1.1527 0.5551 0.3608 0.2051

7.5860 4.2179 2.4310 1.6304 0.7468 0.4850 0.3295

0.0000c 0.1115 0.2047 0.3031 0.4990 0.7248 1.0000

a Standard uncertainties u are u(T) = 0.10 K, ur(p) = 0.05, and ur(m) = 0.002. bx′ represents the salt-free-based mole fraction of ethylene glycol. cThe solubility of glycine in pure water was taken from our previous work.9

The short-range term is calculated by the UNIQUAC equation,30 which is a combination of a combinatorial term GC and a residual term GR

corresponding mole-fraction-based quantities when using the MSE model.31 3.2. Activity Coefficient Model. In the MSE model, there are three contributions for the excess Gibbs free energy (GE)31 E

E G LR

E GMR

E GSR GC GR = + RT RT RT ⎡ Φ θ⎤ = (∑ ni)⎢∑ xi ln i + 5 ∑ qixi ln i ⎥ − (∑ ni)[∑ qixi ln(∑ θτ j ji)] ⎢⎣ i xi Φi ⎥⎦ i i i i j

E GSR

G = + + RT RT RT RT

(11)

where GELR stands for the long-range electrostatic interactions, GEMR is the middle-range interactions between ion−ion and ion−molecule that are not included in the long-range term, and GESR is the short-range contribution that considers the local interactions between ion−ion, ion−molecule, and molecule− molecule. The long-range term is calculated from the Pitzer− Debye−Hückel expression25 ⎞ 4A I ⎛ 1 + ρIx1/2 ⎟ = −(∑ ni) x x ln⎜⎜ 0 1/2 ⎟ ρ RT ∑ + ρ x [1 ( I ) ] ⎠ ⎝ x ,i i i i

(17)

where

θi =

(12)

where the sum includes all the ionic and neutral species, Ax is the Debye−Hückel parameter for osmotic coefficient, Ix represents the ionic strength based on mole fraction, I0x,i is the ionic strength when the composition reduces to a pure component, and ρ is a hard-core collision diameter. The middle-range term is represented by a symmetrical second virial coefficient-type expression31 E GMR = −(∑ ni) ∑ ∑ xixjBij (Ix) RT i i j

(18)

rx i i ∑j rjxj

(19)

⎛ aji ⎞ ⎟ τji = exp⎜ − ⎝ RT ⎠

(20)

where summations are over all the species, qi and ri represent the relative surface area and molecular volume parameters, respectively, for pure species, and aji is the binary interaction parameter between species j and i with aji ≠ aij and aii = ajj = 0. In the MSE model, aij and aji are expressed by a quadratic function of the temperature31

(13)

where x is the mole fraction of a species; Bij(Ix) is a binary interaction parameter between species i and j (ion or molecule), which is a function of ionic strength Bij (Ix) = bij + cijexp( − Ix + 0.01 )

∑j qjxj

Φi =

E G LR

where Bij(Ix) = Bji(Ix), Bii(Ix) = Bjj(Ix) = 0, and bij and cij are temperature-dependent coefficients expressed by (15)

cij = c0, ij + c1, ijT + c 2, ij/T + c3, ijT 2 + c4, ij ln T

(16)

aij = a0, ij + a1, ijT + a 2, ijT 2

(21)

aji = a0, ji + a1, jiT + a 2, jiT 2

(22)

where T is the temperature in Kelvin, a0,ij, a0,ji, and so forth are adjustable parameters between species i and j. For all the three terms of GE, the activity coefficients are converted from symmetrical normalization to those based on the unsymmetrical reference state so that they are consistent with the HKF model for standard-state properties.31

(14)

bij = b0, ij + b1, ijT + b2, ij /T + b3, ijT 2 + b4, ij ln T

qixi

4. RESULTS AND DISCUSSION 4.1. Solubility of Glycine in the MEG−H2O Mixtures. The solubility of glycine in the MEG−H2O mixtures was determined in the temperature range from 278.15 to 353.15 K. These experimental data are reported in Table 1 and illustrated in Figure 2. It can be seen from Figure 2 that the solubility of glycine increases with increasing temperature but drops sharply with increasing MEG content. Compared with glycine, the solubility of NH4Cl in the MEG−H2O mixed solvent, which was determined in our previous work,17 is considerably larger especially in

where T is the temperature in Kelvin, b0,ij, b1,ij, c0,ij, c1,ij, and so forth are adjustable parameters between species i and j that can be obtained by the regression of experimental data. For most if the electrolyte solutions, only the first three terms of eqs 15 and 16 are required. 2429

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solvents containing more than 0.30 mole fraction of MEG. For example, in 0.72 mole fraction of MEG aqueous solution at 353.15 K, the solubility of NH4Cl is 3.2612 mol·kg−1, whereas that of glycine is 0.4860 mol·kg−1. Taking advantage of this difference in solubility, it is possible to separate glycine from NH4Cl by using MEG as the antisolvent. 4.2. Phase Equilibria of the Glycine−NH4Cl−MEG−H2O System. Glycine and NH4Cl have been found to have influence on the solubility of each other in water and methanol−water systems.17,39 This work determined their solubilies in glycine− NH4Cl−MEG−H2O system from 278.15 to 353.15 K for solvents containing 60 and 90 wt % of MEG, respectively, as summerized in Tables 2 and 3. It can be seen in Figure 3 that the presence of either glycine or NH4Cl increases the solubility of the other, and both solubilities increase with increasing temperature. Figure 4 illustrates the effect of glycine on the solubility of NH4Cl in mixed solvent containing 90 wt % of MEG.

Figure 2. Solubility of glycine in the MEG−H2O mixed solvent from 278.15 to 353.15 K.

Table 2. Experimental Solubilities of the Glycine−NH4Cl−MEG−H2O System in the Temperature Range of 278.15 to 353.15 K and at Pressure p = 101.325 kPaa (MEG = 60 wt %) m(NH4Cl), mol·kg−1

m(glycine), mol·kg−1

0.0000 0.4951 1.0178 1.4919 2.0043 3.4513 4.0145 3.6270 3.7258 3.7711 3.9300

T = 278.15 K 0.3569 0.4547 0.5010 0.5527 0.5989 0.6505 0.7568 0.0000 0.2003 0.5009 0.5994 T = 298.15 K 0.5755 0.6907 0.7741 0.8404 0.8628 1.1170 1.2884 0.0000 0.2003 0.5009 0.9999

0.0000 0.4951 1.0178 1.4919 2.0043 3.4925 4.7417 5.6036 5.7800 4.8534 5.1941 5.5373 5.8087

T = 333.15 K 1.1527 1.3198 1.4718 1.6135 1.7304 2.0904 2.4663 2.6696 2.7971 0.0000 1.0006 2.0024 2.5000

0.0000 0.4951 1.0178 1.4919 2.0043 2.5200 3.1688 2.9467 2.9947 3.0498 3.0656

solidb

m(NH4Cl), mol·kg−1

G G G G G G G + Nc N N N N

0.0000 0.4951 1.0178 1.4919 2.0043 3.0007 3.5818 3.2695 3.3626 3.4002 3.4423

G G G G G G G+N N N N N

0.0000 0.4951 1.0178 1.4919 1.9998 4.0049 4.2956 4.7146 4.1856 4.3596 4.4582 4.6801

G G G G G G G G G+N N N N N

0.0000 0.4951 1.0178 1.4919 2.0043 3.9936 5.7078 6.4922 7.0549 5.6073 5.9193 6.3722 7.0803

m(glycine), mol·kg−1 T = 288.15 K 0.4588 0.5588 0.6285 0.6773 0.7118 0.8258 0.9993 0.0000 0.2003 0.5009 0.8001 T = 313.15 K 0.7943 0.9155 1.0322 1.1172 1.2206 1.5827 1.6206 1.8286 0.0000 0.5025 1.0014 1.5007 T = 353.15 K 1.6304 1.8644 1.9849 2.1608 2.3764 3.0514 3.7069 4.0318 4.1000 0.0000 1.0006 2.0024 3.7001

solidb G G G G G G G+N N N N N G G G G G G G G+N N N N N G G G G G G G G G+N N N N N

a

Standard uncertainties u are u(T) = 0.10 K, ur(p) = 0.05, and ur(m) = 0.002. bSolid: G-glycine(s), N-NH4Cl(s). cSolubilities for multisaturated points were calculated by the MSE model with new parameters. 2430

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Table 3. Experimental Solubilities in the Glycine−NH4Cl−MEG−H2O System in the Temperature Range of 278.15 to 353.15 K and at Pressure p = 101.325 kPaa (MEG = 90 wt %) m(NH4Cl), mol·kg−1

solidb

m(NH4Cl), mol·kg−1

G G G G N N N N

0.0000 0.4989 1.4934 2.0569 2.0449 2.0688 2.0940 2.0997

0.0000 0.4989 1.4934 2.1547 2.2197 2.2456 2.2657 2.3005

T = 278.15 K 0.0856 0.1634 0.2114 0.2334 0.0000 0.0499 0.1002 0.1998 T = 298.15 K 0.1736 0.2466 0.3087 0.3568 0.0000 0.0999 0.1996 0.3458

G G G G N N N N

0.0000 0.4989 1.4934 2.3584 2.4741 2.5104 2.5387 2.6093 2.6178

0.0000 0.4989 1.4934 2.7802 2.8452 2.8851 2.9461 3.0345 3.1058

T = 333.15 K 0.3608 0.4446 0.5819 0.7750 0.0000 0.0999 0.3012 0.5020 0.7583

G G G G N N N N N

0.0000 0.4989 1.4934 3.1999 3.2604 3.2993 3.3990 3.6463 3.7183

0.0000 0.4989 1.4934 1.7760 1.8594 1.8599 1.8893 1.9211

a

m(glycine), mol·kg−1

m(glycine), mol·kg−1 T = 288.15 K 0.1219 0.2031 0.2654 0.2909 0.0000 0.0999 0.1996 0.2649 T = 313.15 K 0.2609 0.3103 0.4004 0.4784 0.0000 0.0999 0.1996 0.4272 0.4803 T = 353.15 K 0.4850 0.5929 0.8077 1.2232 0.0000 0.1997 0.4999 0.9983 1.2005

solidb G G G G N N N N G G G G N N N N N G G G G N N N N N

Standard uncertainties u are u(T) = 0.10 K, ur(p) = 0.05, and ur(m) = 0.002. bSolid: G-glycine(s), N-NH4Cl(s).

Figure 4. Solubility of NH4Cl in the glycine−NH4Cl−MEG−H2O system containing 90 wt % (salt-free) of MEG from 278.15 to 353.15 K.

Figure 3. Solubilities of glycine and NH4Cl in the glycine−NH4Cl− MEG−H2O system containing 60 wt % (salt-free) of MEG from 278.15 to 353.15 K.

4.4. Model Parameterization. Model parameters for the interactions between glycine and MEG are essential in calculating the solubility of glycine in the MEG−H2O mixtures by using the MSE model and also required in further modeling the multicomponent glycine−NH4Cl−NaCl−MEG−H2O system. Because the anion and cation species of glycine are negligible under the investigated conditions, the term glycine herein only refers to the neutral species of glycine that is known

4.3. Solubility of Glycine in the Glycine−NaCl−MEG− H2O System. The solubility of glycine in the glycine−NaCl− MEG−H2O system was determined from 278.15 to 353.15 K for solvents containing 60 wt % of MEG. The experimental data are presented in Table 4 and Figure 5. Similar to the phenomenon found in aqueous system,19 the presence of NaCl increases the solubility of glycine in the MEG−H2O mixed solvent. 2431

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used here were determined in our previous study from the experimental solubility of glycine in pure water,9 whereas those for MEG−H2O were taken from the OLI default databank. The comparison between the regressed (solid lines) and the experimental solubilities (symbols) for the glycine−MEG−H2O system is shown in Figure 2. It can be seen that the model with new parameters is able to represent the experimental solubility of glycine over the entire temperature and MEG composition ranges. The average absolute relative deviation (AARD) between the regressed and experimental solubility is 4.77%. The prevailing aqueous species involved in the glycine− NH4Cl−NaCl−MEG−H2O system are cation NH4+ and Na+, anion Cl−, and neutral zwitterionic glycine, MEG, and H2O. Modeling phase equilibria in this system requires binary interactions between any two of these species. Model parameters for ternary glycine−NH 4 Cl−H 2 O, NH 4 Cl−MEG−H 2 O, NaCl−MEG−H2O, and NaCl−NH4Cl−H2O systems have been reported in previous studies17,39 and were used here as a foundation for modeling the multicomponent glycine−NH4Cl− NaCl−MEG−H2O system. These parameters include the UNIQUAC interactions of glycine−NH 4 +, glycine−Cl− , MEG−NH4+, MEG−Na+, and the middle-range interactions of MEG−NH4+, MEG−Na+, and Na+−NH4+. Solubility of solid phases in the glycine−NaCl−H2O system has been reported by Gao and Li in the literature.19 These data were used here in the parametrization to determine the UNIQUAC interaction parameters between glycine and Na+. Table 5 lists the interaction parameters that were used in modeling phase equilibria of all the investigated ternary systems. After model parameters were established as summarized in Table 5, solubilities of solid phases in the quaternary glycine− NH4Cl−MEG−H2O and glycine−NaCl−MEG−H2O systems were predicted. As illustrated in Figure 3 where the solubility of glycine and NH4Cl in the mixed solvent containing 60 wt % of MEG is shown, the predicited values (solid lines) agree well with the experimental data (symbols). The AARDs for the solubilities of glycine and NH4Cl are 5.84% and 1.03%, respectively. The results for the glycine−NaCl−MEG−H2O system are shown in Figure 5 in which the solubility of glycine was predicted in MEG-containing mixtures in the presence of 0 to 3.5 mol·kg−1 of NaCl. The AARD between the prediction and experimental data is 5.47%. The model with newly developed parameters can accurately calculate the solubilities of glycine and NH4Cl, indicating that it has the capacity to be used in the simulation of process involving phase equilibira of the glycine−NH4Cl− NaCl−MEG−H2O system. Additionally, multiple saturation points for the glycine− NH4Cl−MEG−H2O system containing 60 wt % of MEG in the salt-free solvent at temperatures from 278.15 to 353.15 K were predicted by using new parameters. Calculation results are reported in Table 2 and illustrated in Figure 3. The prediction was carried out in OLI Stream Analyzer 9.1 by calculating the scaling tendency values (supersaturation) of the involved salts as a function of temperature and the solution composition. 4.5. Model Application and Optimization of Operating Conditions. Having developed a set of model parameters that are capable of calculating solid−liquid equilibria (SLE) for the glycine−NH4Cl−NaCl−MEG−H2O system, it is feasible to simulate the proposed MMCA process by using the MSE model. Through process simulation the optimal operating conditions can be determined efficiently. Specifically, process simulation was performed for the three key steps involved in the MMCA process with the aid of the newly equipped OLI Stream Analyzer 9.1

Table 4. Experimental Solubility of Glycine in the Glycine−NaCl−MEG−H2O System in the Temperature Range of 278.15 to 353.15 K and at Pressure p = 101.325 kPaa (MEG = 60 wt %) m(NaCl), mol·kg−1

m(glycine), mol·kg−1

m(NaCl), mol·kg−1

T = 278.15 K 0.4972

m(glycine), mol·kg−1

T = 298.15 K 0.4389

0.6804 0.4972

0.9994

0.4959

0.7587 0.9994

1.9983

0.5875

0.9127 1.9983

2.4881

0.6746 T = 313.15 K

0.4972

1.0250 2.4881 T = 333.15 K

0.8996

1.3096 0.4917

0.9994

1.0260

1.4711 0.9984

1.9983

1.2576

1.7770 2.0047

2.4881

1.3749

2.1412 3.0020

T = 353.15 K 0.4917

1.9144

0.9984

2.1463

2.0047

2.5413

3.4990

3.2048

a

Standard uncertainties u are u(T) = 0.10 K, ur(p) = 0.05, and ur(m) = 0.002.

Figure 5. Solubility of glycine in the glycine−NaCl−MEG−H2O system containing 60 wt % (salt-free) of MEG from 278.15 to 353.15 K.

as the zwitterionic glycine with formula +NH3CH2COO−. Only the short-range contribution from molecular interactions is considered. UNIQUAC parameters for the interaction between glycine and MEG were determined by regressing the solubility data of the glycine−MEG−H2O system at temperatures from 278.15 to 353.15 K. The newly obtained parameters are listed in Table 5. In addition to glycine−MEG, glycine−H2O and MEG−H2O are the other two binary interactions that play key roles in this ternary system. Model parameters for glycine−H2O 2432

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Table 5. Newly Regressed MSE Model Parameters of the UNIQUAC and the Middle-Range Interactions for the Glycine−NH4Cl− MEG−H2O Systema species

UNIQUAC interaction parameters

i

j

Q0IJ

Q0JI

glycine glycine glycine glycine glycine MEG MEG MEG MEG

H2Ob MEG NH4+b Na+ Cl−b H2Oc NH4+d Na+d Cl−c

−4160.187 3686.904 6138.974 9587.080 5801.943 195.6597 8859.905 1064.302 1521.117

2910.428 −29710.46 −655.0286 45475.72 −2109.955 −212.5369 873.8450 3774.311 2238.015

species

Q1IJ

Q1JI

8.134188 11.95076 −34.15892 204.4724 −44.59634 −43.2167 −114.3872 −214.5537 −43.24297 −36.13042 −17.72271 31.50075 0 0 0 0 0 0 middle-range interaction parameters

Q2IJ

Q2JI

−0.016874 0.0525726 0.049018 0.2593849 0.047077 0.0224403 0 0 0

−0.008421 −0.3001403 0.188542 0.2382182 0.178966 −0.0546301 0 0 0

i

j

BMD0

BMD1

BMD2

CMD0

CMD1

CMD2

MEG MEG MEG Na+ Na+ NH4+

NH4+d Na+d Cl−d NH4+d Cl−c Cl−c

5.945064 2.157143 −8.698285 55.38967 −213.9990 4369.664

0 0 0 −0.1028922 1.863230 2.325859

−829.2285 −302.2264 983.2170 −12536.65 16036.80 −96273.91

−0.8538574 −0.2711171 8.841474 29.01004 202.8870 −9748.479

0 0 0 0 −2.153910 −5.062129

0 0 0 0 −9832.110 219746.0

a

Parameters for glycine−MEG and glycine−Na+ were determined in this work. Other model parameters were taken from bref 37; cthe default databank of OLI (version 9.1); and dref 17.

program. Step 1 is antisolvent crystallization in which aqueous MEG is added to the wet solid mixture containing glycine and NH4Cl to dissolve NH4Cl completely, whereas glycine is dissolved to a minimum. Step 2 is the evaporation of water from the filtrate of step 1 to obtain a solid mixture in which NH4Cl accounts the dominant portion. Step 3 is the dissolution of the solid mixtures obtained from step 2 by using the water generated from evaporation. Step 1: Antisolvent Crystallization. The incoming feed stream of step 1 is a wet solid mixture containing 70 wt % of glycine, 23 wt % of NH4Cl, and 7 wt % of H2O. Effects of the composition of the aqueous MEG antisolvent and temperature on the yield of glycine and the corresponding consumption of MEG were investigated. It is clear that the yield should be maximized, whereas the use of MEG should be minimized. Figure 6 represents the yield of glycine as a function of the MEG concentration and temperature, which was calculated by dividing the mass of pure solid glycine gained from antisolvent

Figure 7. Effects of the MEG concentration and temperature on the consumption of pure MEG used during the antisolvent crystallization.

crystallization by the total incoming glycine included in the solid mixture. It can be observed from Figure 6 that the yield of glycine increases slightly with the increasing MEG concentration. However, it is shown in Figure 7 that with an increment in the MEG concentration, considerablely more pure MEG is needed to carry out the antisolvent crystallization. It should also be mentioned that less amount of MEG used in the process would favor the recovery of NH4Cl in the following steps. Therefore, antisolvent with 50 wt % of MEG was finally selected. Considering the effect of temperature, results in Figures 6 and 7 demonstrate that a lower temperature increases the yield of glycine but at the same time raises the consumption of MEG. The antisolvent crystallization temperature was therefore set at 298.15 K with an additional concern on the energy consumption. Under these circumstances, 82.3% of glycine could be separated from the mixed solid and 0.59 ton of MEG per ton of glycine is needed to achieve this goal. The filtrate is sent to next step for the

Figure 6. Effects of the MEG concentration and temperature on the yield of glycine obtained from antisolvent crystallization. 2433

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saturated with both glycine and NH4Cl at different temperatures as a function of the MEG mass fraction expressed on a salt-free basis. A temperature of 333.15 K was selected to perform the low pressure evaporation and the final concentration of MEG in the solvent was set at 90 wt %. As most of the water has been removed from the solution, glycine and NH4Cl will crystallize out together. The resulting slurry is then set at room temperature, 298.15 K for example, to deposit more solids. Through filtration, the MEG solvent is regenerated and used in the next cycle. For visually representing the process, a phase diagram for the glycine−NH4Cl−MEG−H2O system is constructed as shown in Figure 10. Solubility curves for glycine and NH4Cl at 298.15 K in

regeneration of the MEG solvent and further recovery of NH4Cl. To obtain the final product, recrystallization of glycine in pure water is required to remove the adhered MEG and NH4Cl impurities. This step is involved in the current glycine manufacturing process. Step 2: Evaporation. In step 2, water was removed from the filtrate of step 1 by evaporation at reduced pressure. This will lead to simultaneous deposition of NH4Cl and glycine. The operating temperature and pressure were determined according to the vapor pressure of the MEG aqueous solutions containing glycine and NH4Cl. Prior to calculating for the glycine−NH4Cl−MEG−H2O system, the accuracy of the MSE model with new parameters was evaluated by predicting the boiling points for the NaCl−MEG− H2O solution. The prediction is plotted in Figure 8 and

Figure 10. Phase diagram for the glycine−NH4Cl−MEG−H2O system and the operation in the antisolvent crystallization and evaporation steps. Figure 8. Experimental (in the literature40) and predicted boiling points for the NaCl−MEG−H2O system at p = 101.3 kPa.

mixed solvent containing 46 and 90 wt % of MEG are designated as Cx′F and Dy′E, respectively. Solubilities of both salts are plotted in moles per kilogram of mixed solvent (mol·kg−1 solvent). Point x refers to the total composition of the solid− liquid mixture after a required amount of MEG antisolvent has been added to the system at 298.15 K. The corresponding saturated solution is at equilibrium with both glycine and NH4Cl with a composition represented by point x′. By filtration, pure solid glycine is separated, whereas NH4Cl is left in the solution. Evaporation of water from the saturated solution along line x′y results in the coprecipitation of glycine and NH4Cl because of less amount of solvent and higher concentration of MEG. The composition of the final saturated MEG aqueous solution is represented by point y′. As a result of these operations, the MEG solvent is regenerated and used as feed in the next cycle. Step 3: Dissolution. Dissolution performed in step 3 is aimed at separating pure NH4Cl from the solid mixture. Water at 333.15 K recovered from evaporation is used to carry out this operation. Shown in Figure 11 is a phase diagram for the glycine−NH4Cl− H2O system at 333.15 K. By adding water to completely dissolve glycine, the total composition of this mixture is on the side of NH4Cl as represented by point a. Solid NH4Cl is then separated by filtration. The corresponding solution composition is shown by point b. This saturated solution is finally subjected to the next cooling step with the reaction mixture. 4.6. Lab-Scale Crystallization Verification. Based on the simulation with the modified MSE model, mass balances were calculated for the MMCA process operated under the aforementioned optimal conditions as illustrated in Figure 12.

compared with the experimental data reported in the literature.40 The AARD between the predicted and the reported values was 0.07%, indicating that the newly equipped MSE model could be used to calculate the vapor−liquid equilibria for the saltcontaining MEG aqueous systems. Figure 9 shows the calculated vapor pressures of the glycine−NH4Cl−MEG−H2O solution

Figure 9. Vapor pressure of the glycine−NH4Cl−MEG−H2O system saturated with glycine and NH4Cl as a function of the MEG concentation (salt-free wt %) at different temperatures. 2434

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Industrial & Engineering Chemistry Research Starting with a wet solid mixture of glycine and NH4Cl came from cooling the products of MCA ammonolysis reaction, the yield of glycine in a single operation could reach 82.3%. The yield for the recovery of NH4Cl, in a single run, is 31.4%. The rest of NH4Cl is returned to the cooling step or the antisolvent crystallization. The separation of glycine and NH4Cl was successfully tested in the laboratory following the process illustrated in Figure 1 under the conditions which had been determined to be optimal by

model calculations. The XRD patterns of solids obtained from antisolvent crystallization and dissolution steps showed that pure solid glycine and NH4Cl were separated from these two steps, respectively. Figure 13 shows the SEM images of solids that were obtained successively from cooling, antisolvent crystallization, evaporation, and dissolution steps.

Figure 13. SEM images of glycine and NH4Cl obtained in the MMCA process. a, mixture of glycine and NH4Cl from cooling in water; b, pure glycine from MEG antisolvent crystallization; c, mixture of glycine and NH4Cl from evaporation; d, pure NH4Cl from dissolution.

Figure 11. Phase diagram for the glycine−NH4Cl−H2O system and the operation in the dissolution step.

Figure 12. Mass balances of the MMCA process calculated by new model. 2435

DOI: 10.1021/acs.iecr.5b04144 Ind. Eng. Chem. Res. 2016, 55, 2426−2437

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Industrial & Engineering Chemistry Research

5. CONCLUSIONS A new process called the MMCA process for the production of glycine by using MEG−H2O antisolvent crystallization was proposed on the basis of chemical modeling and proven to be feasible by experiments. The MSE model with a set of new interaction parameters was used in calculating the phase equilibria for the glycine−NH4Cl−MEG−H2O system and simulating the MMCA process. Solubilities of glycine in the MEG−H2O mixed solvent and the NaCl−MEG−H2O solutions were measured from 278.15 to 353.15 K. Phase equilibria for the glycine−NH4Cl−MEG−H2O system containing 60 and 90 wt % of MEG were also measured. New model parameters have been determined based on the experimental solubility data for the glycine−MEG−H2O system measured in this study and the previously published solubility data for glycine−NaCl−H2O.19 These new parameters, combined with those previously reported parameters determined from the solubility data for the glycine− H2O, glycine−NH4Cl−H2O, and the NaCl−NH4Cl−H2O systems,17,37 provide a comprehensive set of MSE model parameters for predicting accurate solubilities in the quaternary glycine−NH4Cl−MEG−H2O and glycine−NaCl−MEG−H2O systems from 278.15 to 353.15K. The newly constructed chemical model makes it feasible and efficient to investigate various operating conditions for the MMCA process. The optimal concentration of MEG in the MEG−H2O antisolvent was determined to be 50 wt % with a temperature of 298.15 K. Theoretically only 0.59 ton of pure MEG is used to obtain 82.3% yield for glycine, which means about 1.5 tons of mixed solvent is needed to produce 1 ton of glycine. This is greatly less than the solvent consumption in the methanol antisolvent crystallization, which is nearly 20 tons, not to mention the fact that the green solvent MEG will be recycled in a continuous process. Glycine and NH4Cl were successfully separated from batch crystallization experiments on a laboratory-scale, indicating that the MMCA process is feasible.





Ix, ionic strength on the mole fraction basis K, dissociation or dissolution equilibrium constant m, molality (mol·kg−1 solvent) ni, number of moles of species i in eqs 11, 12, and 16 qi, UNIQUAC surface area parameter of species i QiIJ, QiJI (i = 1, 2, 3, 4), short-range adjustable parameters of the MSE model ri, UNIQUAC molecular volume parameter of species i R, gas constant (8.314 J·mol−1·K−1) T, absolute temperature (K) xi, mole fraction of species i xi′, mole fraction of solvent on a salt-free basis γi, activity coefficient of species i ρ, hard-core collision diameter

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AUTHOR INFORMATION

Corresponding Author

*Z. Li. E-mail: [email protected]. Tel./Fax.: + 86 10 62551557. Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS The authors gratefully thank the National Natural Science Foundation of China (Grants 21476235 and U1407112) and the National Basic Research Development Program of China (973 Program with Grant 2013CB632605) for financial support in this work.



NOMENCLATURE a, activity aij, UNIQUAC interaction parameter between species i and j a0,ij, a1,ij, a2,ij, a0,ji, a1,ji, and a2,ji, short-range adjustable parameters of the MSE model Ax, Debye−Hückel parameter AR, residual Helmholtz free energy bij, middle-range interaction parameter between species i and j b0,ij, b1,ij, b2,ij, and b3,ij, middle-range adjustable parameters of the MSE model Bij, middle-range interaction parameter between species i and j cij, middle-range interaction parameter between species i and j GE, excess Gibbs free energy 2436

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