Synthesis of dimethyl carbonate and propylene glycol in a pilot-scale reactive distillation column: Experimental investigation, modeling and process analysis

Accepted Manuscript Synthesis of Dimethyl Carbonate and Propylene Glycol in a Pilot-scale Reactive Distillation Column: Experimental Investigation, Modeling and Process Anal‐ ysis Johannes Holtbruegge, Sebastian Heile, Philip Lutze, Andrzej Górak PII: DOI: Reference:

S1385-8947(13)01107-8 http://dx.doi.org/10.1016/j.cej.2013.08.054 CEJ 11159

To appear in:

Chemical Engineering Journal

Received Date: Revised Date: Accepted Date:

18 April 2013 7 August 2013 14 August 2013

Please cite this article as: J. Holtbruegge, S. Heile, P. Lutze, A. Górak, Synthesis of Dimethyl Carbonate and Propylene Glycol in a Pilot-scale Reactive Distillation Column: Experimental Investigation, Modeling and Process Analysis, Chemical Engineering Journal (2013), doi: http://dx.doi.org/10.1016/j.cej.2013.08.054

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Synthesis of Dimethyl Carbonate and Propylene Glycol in a Pilot-scale Reactive Distillation Column: Experimental Investigation, Modeling and Process Analysis Johannes Holtbrueggea*, Sebastian Heilea, Philip Lutzea, Andrzej Góraka,b a b

TU Dortmund University, Department of Biochemical and Chemical Engineering, Laboratory of Fluid Separations, Emil-Figge-Strasse 70, D-44227 Dortmund, Germany. Lodz Technical University, Department of Environmental and Process Engineering, Department of Heat and Mass Transfer, ul. Wólczańska 213, PL-90924 Lodz, Poland.

[email protected] +49 (0) 231/755-4319 +49 (0) 231/755-3035 [email protected] [email protected] [email protected] *

Corresponding Author

Abstract The transesterification of propylene carbonate with methanol to produce the two valuable products dimethyl carbonate and propylene glycol is associated with an unfavorable chemical equilibrium and complex thermodynamic behavior. This results in a challenging and costintensive process currently used for their production. The application of reactive distillation, which integrates chemical reaction and distillation into one single column is considered as potential candidate to improve efficiencies and product yields within chemical-equilibriumlimited systems. However, the design of such a column for industrial-scale applications is challenging which needs the integration of model-based approaches with reliable experimental data. This paper presents an experimental and theoretical investigation of the simultaneous production of dimethyl carbonate and propylene glycol in a pilot-scale reactive distillation column. Experiments varying decisive operating parameters were successfully performed showing the feasibility of simultaneously producing dimethyl carbonate and propylene glycol in a reactive distillation column. The experimental results were used to select and validate a modeling approach for the simulation of the reactive distillation process. The successfully validated non-equilibrium stage model was applied to perform a process analysis pointing out the trends of both the reactant conversions and the product purities. The simulation results showed the option of achieving high propylene carbonate conversions while recovering an azeotropic mixture of dimethyl carbonate and methanol in the distillate.

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These results define the operating range for the economic optimization and establishment of an industrial-scale reactive distillation process for this chemical system. Keywords: catalytic distillation, homogeneous catalyst, non-equilibrium stage model, process intensification, reboiler efficiency

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Nomenclature Latin Letters

ai

activity of component i

(mol mol-1)

aij

UNIQUAC binary interaction parameter

(-)

bij

UNIQUAC binary interaction parameter

(K)

Ei h ΔhR Ka ka Mi i m

reboiler efficiency of component i

(-)

height of the pilot-scale column

(m)

enthalpy of reaction

(kJ mol-1)

activity-based chemical equilibrium constant

(-)

activity-based reaction rate constant

(kg3 kmol-2 m-3 s-1)

molar mass of component i

(kg kmol-1)

mass flow rate of flow i

(kg h-1)

nC ni ni

number of components

(-)

molar amount of component i

(mol)

molar flow rate of flow i

(mol h-1)

p

pressure

(kPa)

ra T Tb V wcat Xi xi yi

rate of reaction

(mol m-3 h-1)

temperature

(K)

boiling temperature

(K)

volume of the liquid phase

(m3)

mass fraction of catalyst

(g g-1)

conversion of component i

(-)

molar fraction of component i in the liquid phase

(mol mol-1)

molar fraction of component i in the vapor phase

(mol mol-1)

γi νi

activity coefficient of component i in the liquid phase

(-)

stoichiometric coefficient of component i

(-)

σ

standard deviation of the measurement

(-)

τij

UNIQUAC binary interaction parameter

(-)

Φ

objective function

(-)

χMeOH/PC

molar feed ratio between MeOH and PC

(mol mol-1)

Greek Letters

Subscripts B

bottom

D

distillate 3

exp

experimental value

CF

column feed

rec

reconciled value

T

top

Superscripts eq

thermodynamic equilibrium

out

exiting stream of the reboiler

Abbreviations CO2

carbon dioxide

DFmass

mass-based distillate-to-feed ratio

DMC

dimethyl carbonate

EC

ethylene carbonate

EQ

(phase-)equilibrium stage

GC

gas chromatograph

HETP

height equivalent to a theoretical plate

MeOH

methanol

MTBE

methyl-tert-butyl ether

NEQ

non-equilibrium stage

PC

propylene carbonate

PG

propylene glycol

RD

reactive distillation

RR

reflux ratio

UNIFAC

universal quasichemical functional group activity coefficients

UNIQUAC

universal quasichemical

VLE

vapor-liquid equilibrium

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1. Introduction In recent years, organic carbonates and, in particular dimethyl carbonate (DMC), have achieved increasing importance due to their versatile chemical properties and low level of hazard [1,2]. As a result, DMC production has increased from 47 kt a-1 in 1997 [3] to more than 70 kt a-1 in 2001 [4]. One important application of DMC is its use as a high-octane gasoline additive [5]. DMC has an oxygen content of 53.3 wt-% and is considered to be a promising substitute for the environmentally hazardous methyl-tert-butyl ether (MTBE), which has an oxygen content of 18.2 wt-% [3]. In contrast to MTBE, which is already banned by the US government, DMC does not pollute the groundwater because it decomposes on accidental release. Another broad field of application is its use as an intermediate for polycarbonates [6]. Here, DMC is widely used as a substitute methylating agent for toxic chemicals such as phosgene [7]. DMC is also utilized as solvent, particularly in the synthesis of electrolytes for lithium-ion batteries [8]. Another well-known and increasingly used bulk chemical is propylene glycol (PG); its production capacity rose from approximately 900 kt a-1 in 2000 [9] to 1200 kt a-1 in 2004 [10]. About 45% of worldwide PG production is used for the synthesis of unsaturated polyester resins [9]. The remaining amount is primarily used as de-icing fluid for aircrafts and as a solvent in several cosmetic products [9,11]. Both of these valuable chemicals can be produced in a single reaction – the transesterification of propylene carbonate (PC) with two molecules of methanol (MeOH). Besides selling the product PG, it can be reacted with carbon dioxide (CO2) to produce the reactant PC again [12]. That allows to produce DMC in a two-step reaction consuming one molecule of CO2 and two molecules of MeOH. Hence. the synthesis of DMC through PC transesterification is one promising candidate particularly interesting in the framework of “green chemistry” [13]. However, the reactant conversion of the transesterification reaction is strongly limited by its unfavorable chemical equilibrium [14]. This but also the complex thermodynamic behavior result in a difficult production process requiring several distillation columns interconnected in a complex recycling structure for product purification [15]. Therefore, the investment and the operating costs are considerably high. In a previous publication, we suggested the use of a reactive distillation (RD) column for the in-situ removal of one of the products from the reaction, thus overcoming the chemical equilibrium [16]. According to Harmsen [17], RD is one of the best-known and most promising possibilities for achieving process intensification. An RD column combines chemical reaction and distillation at the same time in one apparatus. An example is the in-situ removal of products from the reaction zone, increasing the yield of chemical-equilibrium-limited reactions such as esterifications [18–22], transesterifications [23,24], etherifications [25,26] and condensations as investigated by Darda and Ranade [27].

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Even complex chemical syntheses like the production of unsaturated polyesters comprising four chemical reactions were successfully implemented into an RD column as shown by Shah et al. [28]. Additionally, thermodynamic limitations such as the formation of azeotropes can be overcome. This results in a reduced number of required apparatuses, enabling lower investment and operating costs for an RD process in comparison to special distillation processes such as pressure swing distillations. RD is applied in several industrial processes and was studied in several publications summarized in a textbook by Sundmacher and Kienle [29] and in a review published by Hiwale et al. [30]. However, the design of an RD process is challenging due to the complex interactions of chemical reactions, thermodynamic separation and hydrodynamics accompanied by a nontrivial scale-up [29]. Several degrees of freedom including, besides the classical operating parameters, the large variety of available column internals and catalysts and the large number of possible feed locations and feed streams impede the accurate design of an RD process. Non-equilibrium and (phase-)equilibrium stage models are applied in academia to theoretically describe the phenomena occurring in an RD column [31]; however, experimental investigations at meaningful scale are still crucial for proving model accuracy. Several publications that focus on the transesterification of ethylene carbonate (EC) with MeOH to form DMC and ethylene glycol in an RD column are currently available. Fang and Xiao [32] studied this transesterification experimentally in a lab-scale RD column by applying sodium methoxide as homogeneous catalyst. In an additional study, they used a validated (phase-)equilibrium stage model of this set-up considering the reaction kinetics to show the influence of decisive operating parameters on the product composition and the reactant conversions, thus confirming the feasibility of a full EC conversion [33]. Wang et al. [34] applied an (phase-)equilibrium stage model to study the design and control of the transesterification of EC with MeOH in an industrial-scale RD column using the homogeneous catalyst sodium methoxide. They calculated the reaction rate by using the reaction kinetics published by Fang and Liu [33]. Despite their promising results, we believe that the transesterification of PC with MeOH is even more suited for use in an RD process than the transesterification of EC with MeOH, as the dosing of PC in an RD column is easier than EC, which is in a solid state under standard conditions because of its high melting point of 310 K [35]. In addition, the presence of a binary azeotrope between EC and the product ethylene glycol complicates the product purification [36]. This study presents a first time experimental investigation of the homogeneously catalyzed transesterification of PC with MeOH in a pilot-scale RD column. The gathered experimental data will be used to validate a modeling approach for the homogeneously catalyzed RD

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process. Reliable experimental data are necessary to promote the industrial application of the RD concept for the production of DMC and PG. Therefore, a set of experiments was performed varying important operating variables such as the reflux ratio, the mass-based distillate-to-feed ratio, the molar feed ratio, the catalyst mass fraction and the feed mass flow rate of the pilot-scale RD column. Within the experimental investigations, liquid-phase composition profiles and vapor-phase temperature profiles along the column were measured, and reactant conversions and product purities were determined. The comparison of the experimental and simulated data calculated with (phase-)equilibrium and non-equilibrium stage modeling approaches for the RD column allowed for the selection and validation of the most suitable approach. Finally, the influences of the varied process parameters on the reactant conversions and the product purities of the pilot-scale RD column, which are helpful in identifying the operating range of the RD column for further detailed optimization, are discussed.

2. Chemical System The chemical system studied in this publication is the transesterification of PC with two MeOH-molecules to form the two products – DMC and PG, graphically shown in Scheme 1.

Scheme 1: Transesterification of PC with two molecules of MeOH to form DMC and PG.

Table 1 lists the IUPAC names and the boiling points of the pure components at atmospheric pressure. The system exhibits a non-ideal thermodynamic behavior emphasized by the formation of a homogeneous, low-boiling binary azeotrope consisting of MeOH and DMC ( xMeOH = 0.850 mol mol-1 at Tb = 336.9 K and atmospheric pressure) [37]. Table 1: Nomenclature, molecular formula and pure-component boiling points at atmospheric pressure [38]. Component

IUPAC name

Formula

CAS Number

Tb (K)

MeOH

Methanol

CH4O

67-56-1

337.8

DMC

Carbonic acid, dimethyl ester

C3H6O3

616-38-6

363.5

PG

Propylene glycol

C3H8O2

57-55-6

460.0

PC

Carbonic acid, propylene ester

C4H6O3

108-32-7

513.2

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An experimental screening of nine heterogeneous and two homogeneous catalysts for the transesterification of PC with MeOH has been performed and discussed in an earlier publication [14]. None of the screened heterogeneous catalysts was sufficiently active to allow for the integration of this reaction into an RD column. Based on this result, it was recommended to use sodium methoxide as a highly active homogeneous catalyst for this reaction. Therefore, the chemical equilibrium and the kinetics of this reaction were investigated by applying sodium methoxide as catalyst in a temperature range between 333 – 433 K using initial molar reactant ratios between MeOH and PC of 6.0 – 14.0 mol mol-1. These ranges cover the expected operating range of our pilot-scale RD experiments as well as the expected industrial-scale operating range. The activity-based chemical equilibrium constant under standard conditions was found to be 0.21, indicating the unfavorable product formation for this chemical reaction. Furthermore, no side-product formations were observed for any of the experiments performed in the aforementioned study. Therefore, the use of an RD process to operate the transesterification of PC with MeOH was deemed suitable.

3. Materials and Methods 3.1. Chemicals For the pilot-scale RD experiments, MeOH and PC were supplied by Hanke+Seidel Ltd. in industrial barrels. The guaranteed purity was ≥ 99.7 wt-% for both chemicals. The homogeneous catalyst sodium methoxide was delivered by Merck KGaA as a solution having a concentration of 30 wt-% in MeOH. In the following, the mass fraction of the catalyst always refers to its pure state. High-purity chemicals were used for the calibration of the gas chromatograph. DMC, MeOH, PC, PG and the internal standard acetonitrile were obtained from Merck KGaA with purities ≥ 99.9 wt-%. 3.2. Analytical Methods The liquid-phase concentrations of DMC, MeOH, PC and PG were analyzed offline using a Shimadzu GC-17 gas chromatograph. The chromatograph was equipped with an autosampler (AOC 20i) and a flame-ionization detector. An Innopeg FFAP capillary column with an overall length of 25 m and an inner diameter of 0.32 mm was the stationary phase. The inner surface was a 0.6-µm thick polyethylene glycol film that was coated with 2-nitroterephthalate. Helium with a gas velocity of 27 cm s-1 was the carrier gas for the mobile phase.

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A temperature program was necessary for the analysis of the liquid-phase concentrations. The measurement began at a temperature of 373 K. After this temperature was maintained for 3.7 min, a temperature ramp with a slope of 30 K min-1 was applied to raise the temperature linearly to 493 K. This temperature was maintained for further 5 min. Single-component calibration curves that were established prior to the experimental investigations were used to calculate the component mass fractions from the chromatogram. Acetonitrile was used as an internal standard for the calibration. Each sample was analyzed three times, and the mean value was used for further evaluation. Typical retention times were 2.0 min for acetonitrile, 2.5 min for MeOH and 3.3 min for DMC. The heavy-boilers PG and PC passed the column within a time of 8.6 min and 12.2 min, respectively. To demonstrate the high accuracy of the GC analysis, the absolute and the corresponding standard deviations of all single-component calibrations are summarized in the Supplementary Data to this manuscript. During the experimental investigations in the pilotscale RD column, the quality of the calibration was continuously monitored by analyzing test samples with known compositions. Exemplary results for four test samples are also shown in the Supplementary Data.

4. Experimental Investigations 4.1. Experimental Set-up The experimental investigation of the homogeneously catalyzed transesterification of PC with MeOH was performed in a pilot-scale column (Fig. 1). The column was made of glass, with a nominal diameter of 50 mm and an overall height of approximately 12 m. The process control and the observation of the process parameters were executed with a Siemens SimaticTM PCS7 system. The overall packing height of the pilot-scale column was 5.12 m, divided into six sections equipped with Sulzer BXTM structured packings. The suitability of the available pilot-scale column packed with structured packings for the investigation of the homogeneously catalyzed transesterification of PC with MeOH is discussed in detail in the Supplementary Data. Along with the packing sections, the pilot-scale column consisted of liquid redistributors connecting each of the six packing sections and additionally allowed the attachment of feedstream or side-stream pipes. The redistributors also enabled vapor-phase temperature measurement using PT100-thermocouples (TST42, Endress+Hauser Ltd.) and sample extraction from the liquid phase by means of a syringe. Non-ideal flow behavior such as maldistribution or wall effects in the packing sections was minimized with the redistributors. 9

Because there was no contact between the vapor and liquid phase on the redistributors, no mass transfer between the phases occurred. Table 2 summarizes all measurement locations for the liquid-phase composition and the vapor-phase temperature along the pilot-scale column. Because the homogeneously catalyzed transesterification of PC with MeOH also took place in the liquid hold-up of the redistributors and the reboiler, their hold-up was determined by a volumetric measurement three times prior to the experimental investigations. The results of these measurements, listed in Table 2, showed a high degree of accuracy, with a maximal experimental error of 0.5 cm3. Table 2: Composition and temperature measurement locations along the pilot-scale column. Additionally, the total liquid hold-up of the reboiler and the liquid redistributors is given. The height was measured from the first liquid redistributor above the reboiler. Height

Composition (liquid phase)

Hold-up

Temperature (vapor phase)

(liquid phase)

5.12 m

QD

T7

12 cm³

4.16 m

Q6

T6

43 cm³

3.20 m

Q5

T5

67 cm³

2.24 m

Q4

T4

131 cm³

1.28 m

Q3

T3

138 cm³

0.48 m

Q2

T2

69 cm³

0.00 m

Q1

T1

75 cm³

Reboiler

QB

-

1554 cm³

The pilot-scale column was insulated to maintain an adiabatic operation during the experimental investigation. Three different layers of insulation were applied for this purpose; an inner layer of mineral wool was wrapped with an electric heating wire and subsequently encased with a second layer of mineral wool. The electric heating wire was controlled with a PI controller set to the mean value of the vapor-phase temperatures on the liquid redistributor below and above the particular packing section. A naturally circulating reboiler possessing a total liquid hold-up of 1554 cm3 was installed at the bottom of the column. The collection of the bottom product was performed with an overflow. The mass flow rate of the bottom product stream was measured using a balance (Sartorius Industry MC1, Sartorius AG) by monitoring the time derivative of the change in mass. A thermo-oil heat exchanger with a maximum heat duty of 6.6 kW was used to heat the reboiler.

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Figure 1: Scheme of the pilot-scale column used for the experimental investigation of the homogeneously catalyzed transesterification of PC with MeOH to form DMC and PG.

The vapor stream at the top of the pilot-scale column was condensed using a tap-water-cooled vertical glass-made total condenser. The condensed stream was subsequently subcooled in an additional heat exchanger operated with cold water. The subcooled mixture was split into the distillate and the reflux stream. Both streams were adjusted by the use of individual pumps. The mass flow rate of the distillate was calculated from the time derivative of the change in the distillate mass by using a balance (Sartorius Industry MC1, Sartorius AG). To monitor the 11

reflux mass flow rate, a calibrated Coriolis-type flow meter (RHM015, Rheonik Ltd.) was used. The reflux stream was preheated to a temperature of approximately 5 K below its boiling point by a thermo-oil heat exchanger (SE6, Julabo Ltd.) and was fed to the pilot-scale column via the upper liquid redistributor. For safety reasons, an additional condenser operated with cooling brine ( T = 273 K) was installed behind the glass-made total condenser. To collect any possible light-boiling side-products of the reaction that might not be condensed by the two condensers, two cooling traps cooled with liquid nitrogen ( T = 77 K) were installed between the condensers and the ventilation of the pilot-scale column. In addition, a pressure transducer (DMU01, Afriso-Euro-Index Ltd.) was installed in front of the first condenser to measure the pressure at the top of the column. The pressure drop along the packed section was measured using a U-tube manometer and was determined to be less than 0.2 kPa for all experiments. The pressure drop in the reboiler was used to estimate the liquid level in the naturally circulating reboiler and was monitored using a differential pressure sensor (DMU11D, Afriso-Euro-Index Ltd.). Table 3: Characteristics of the pilot-scale column. The heights were measured from the first liquid redistributor above the reboiler. Nominal diameter

50 mm

Total packing height

5.12 m

Height of rectifying section

2.88 m

Height of reactive section

2.24 m

Feed location of MeOH

2.24 m

PC

3.20 m

Sodium methoxide

2.24 m

Reboiler type

Naturally circulating reboiler

Operating pressure

Atmospheric pressure

Process control system

Siemens SimaticTM PCS7

Membrane pumps (Gamma g/4b, Prominent Ltd.) were used to dose the reactants from the feed tanks. The mass flow rate was adjusted with balances (Sartorius Industry MC1, Sartorius AG) by monitoring the time derivative of the change in mass. As previously noted in Section 3.1, the reactants were delivered with industrial purities. In a previously published contribution, we noticed an abreaction of the catalyst sodium methoxide, even with low amounts of water present in the reactants [14]. Sodium methoxide, water and the carbonates react to form sodium carbonate. Therefore, a minimum catalyst mass fraction of 4.5 ⋅10 −4 g g1

is necessary to compensate for the abreaction. To lower the amount of water in the reactants,

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and thus minimize the abreaction of the catalyst within the pilot-scale experiments, both reactants flowed separately through beds of molecular sieves (3-Å Sylobead MS 564C, W.R. Grace & Co.). The molecular sieves reduced the relative water content of MeOH and PC by 55.5% and 35.2%, respectively. The molecular sieves were replaced when 95% of their maximum capacity was reached. We previously determined that a low catalyst mass fraction is sufficient to guarantee an adequate reaction rate [14]. Therefore, a mass flow rate of 8 g h-1 pure catalyst is sufficient for operating the pilot-scale RD column. Because the dispensing of such a small mass flow rate is challenging, a solution of 5 wt-% of the homogeneous catalyst in MeOH was prepared and separately dosed into the MeOH-feed pipe. Under these conditions, a mass flow rate of the catalyst solution of 160 g h-1 was established. Therefore, a 2 L flask was placed on a balance (AZ3102, Sartorius AG) and the time derivative of the mass change was applied to calculate the mass flow rate. A gear pump (MCP-Z Process, Ismatec) was used to control the mass flow rate. The catalyst solution was mixed with the MeOH-feed directly behind the molecular sieves installed in the MeOH-feed pipe. Both the MeOH and the PC-feed stream tubes were equipped with heat exchangers to preheat them before feeding them into the pilot-scale column. MeOH was preheated to a temperature of 333 K and PC to a temperature of 393 K by means of thermo-oil heat exchangers (Haake N6, Thermo Fischer Scientific Ltd.). The feed locations for both reactants were fixed for all pilot-scale experiments. The high-boiling reactant was fed to the RD column above the low-boiling reactant to establish a countercurrent flow and guarantee excessive contact between the reactants in the reactive section. However, the homogeneous catalyst sodium methoxide had a low solubility in the heavy-boiler PC; thus, the catalyst was fed to the RD column with the low-boiling reactant MeOH. Therefore, the reaction took place in the entire column section below the MeOH-feed position. In such a situation, it is advisable to feed both reactants at the same position into the RD column. However, Keller and Górak [39] found a non-ideal mixing behavior on the used feed distributor feeding both reactants at the same position, resulting in difficulties in the theoretical description of the RD process. Therefore, a preliminary study was performed to identify a suitable feed configuration using the non-equilibrium stage model described in Section 6.1. This study showed that the highest reactant conversions occurred when feeding MeOH and the homogeneous catalyst at a height of 2.24 m and PC at a height of 3.20 m. As a result, the three lower packing sections, the corresponding liquid redistributors and the reboiler constituted the reactive section. Table 3 summarizes all the important characteristics of the pilot-scale column used for the experimental investigations within this study. In

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addition, a compilation showing different photographs taken from the pilot-scale RD column is given in the Supplementary Data to this manuscript. 4.2. Experimental Procedure First, a start-up procedure for the pilot-scale RD column was established. Several publications present optimal start-up procedures for heterogeneously catalyzed RD columns [40–43]. However, none of these were suited for the homogeneously catalyzed transesterification of PC with MeOH. Keller et al. [24] published a start-up procedure for the homogeneously catalyzed transesterification of DMC with ethanol in the same experimental set-up as applied in this work. Therefore, this start-up procedure was used in this work to reach steady-state conditions. After the start-up phase was completed, the fine-tuning of the operating conditions was performed and the column was operated until the following two criteria were fulfilled: ƒ The component balances and the reaction stoichiometry in the column were satisfied. ƒ The temperature deviation at each measurement location along the column was below ± 0.5 K within 2 h. This took in average 8 h of operating time. To prove the first criterion, a data reconciliation (described in detail in the Supplementary Data) was applied; the second criterion was verified by checking the online temperature measurements. After confirming the steady-state operating point, liquid samples were taken from the distillate and the bottom product, as well as from the liquid redistributors. All samples were collected in precooled glass vials and immediately cooled in liquid nitrogen ( T = 77 K). This procedure was especially necessary to stop the further reaction of the samples containing homogeneous catalyst. They were subsequently analyzed using gas chromatography (Section 3.2). Three profiles were measured at 60-min intervals for each experiment to generate reliable experimental data. After the third profile was measured, the shutdown procedure was initiated. In this step, the cooling traps were checked for the formation of side-products, but none was found in any experiment, confirming the high selectivity of the homogeneous catalyst. This conforms to the results from our previous study in which no side-product formation was found within the lab-scale kinetic measurements for this chemical system [14]. 4.3. Design of Experiments The experimental investigation of the homogeneously catalyzed transesterification of PC with MeOH in the pilot-scale RD column had two objectives. The first objective was to choose and validate an adequate modeling approach for this system; the second was to identify the 14

influences of the process parameters on the liquid-phase composition and vapor-phase temperature profiles as well as the reactant conversions and product purities. A factorial design of experiments (Fig. 2) was prepared for the experimental investigation because no experimental data for the homogeneously catalyzed transesterification of PC with MeOH in an RD column was available in existing literature. In total 13 experiments at atmospheric pressure were performed in the pilot-scale RD column. One experiment was performed without adding catalyst to the column to verify the accuracy of the thermodynamic and physical property models. Twelve experiments in the RD operation mode were performed, based on a factorial design of experiments with five varying operating parameters: (1) the reflux ratio RR , (2) the mass-based distillate-to-feed ratio DFmass , (3) the molar feed ratio between MeOH and PC χMeOH/PC , (4) the catalyst mass fraction in the feed wCF,cat and (5) the

 CF , resulting in a varied liquid and vapor load in the RD column. feed mass flow rate m

Figure 2: Factorial design of experiments. Investigated ranges for R R : 1.0 – 1.8; DFmass : 0.55 – 0.65 kg kg-1;  CF : 4.0 – 6.0 kg h-1. χ MeOH/PC : 6.0 – 16.0 mol mol-1; wCF,cat : 2 ⋅ 10 − 3 – 6 ⋅ 10 − 3 g g-1 and m

The limits of the operating parameters were selected by performing a process analysis using the non-equilibrium stage modeling approach introduced in Section 6.1. The reflux ratio was varied between 1.0 – 1.8 and the mass-based distillate-to-feed ratio was investigated in a range of 0.55 – 0.65 kg kg-1. The low chemical equilibrium constant and the need for a high PC conversion required an excessive level of MeOH in the feed. Thus, the molar feed ratio was varied between 6.0 – 16.0 mol mol-1. The catalyst mass fraction in the feed was set to a minimum value of 2 ⋅ 10 −3 g g-1 to prevent its complete abreaction in the presence of water in the pilot-scale column (Section 4.1). Therefore, the catalyst mass fraction was set to 2 ⋅10 −3 , 4 ⋅ 10 −3 and 6 ⋅ 10 −3 g g-1 (Experiments E9 – E11). The resulting catalyst mass fraction in the

15

 CF = 6.0 column was dependent on the operating conditions. All experiments except for E5 ( m kg h-1) were performed with a feed mass flow rate of 4.0 kg h-1. The reproducibility, and thus the reliability, of the experimental data has been tested by performing experiments E1 and E12 under the same operating conditions. The reconciled operating conditions of all 13 experiments are summarized in Table 4.

5. Experimental Results 5.1. Results of the Experimental Investigations Within the experimental investigation, 13 pilot-scale experiments were successfully performed and verified with the data reconciliation presented in the Supplementary Data. The three steady-state column profiles and the reactant conversions showed high agreement within one experiment, underlining the high reliability of the experimental data. The Supplementary Data contains the operating conditions, composition and temperature profiles and the reactant conversions for all experiments. Table 4 summarizes the reconciled mass flow rates and operating conditions of all the experiments carried out in the pilot-scale column. The objective function Φ of the data reconciliation, summing the weighted adjustments made to the experimental data, had a maximum value of 4.23 in the worst case and is also included. As the maximum allowable value of the objective function was 18.31 and none of the variations of the measured variables exceeded the experimental standard error, all experiments passed the data reconciliation. The differences between reconciled and experimental data are exemplarily shown for the experiment E10 in the Supplementary Data.

Figure 3: Results of the pilot-scale RD experiments E1 (closed symbols) and E12 (open symbols) performed at RR = 1.0, DFmass = 0.55 kg kg-1, χ MeOH/PC = 10.0 mol mol-1 and wCF,cat = 2 ⋅ 10 − 3 g g-1 showing the reproducibility of the experimental results: (left) molar composition profile of the liquid phase including DMC, MeOH, PC and PG; (right) temperature profile of the vapor phase.

16

Fig. 3 shows the column profiles for experiments E1, performed in the beginning of the investigation and E12, performed in the end of the investigation under the same operating conditions to demonstrate the reproducibility of the experimental results. The composition profile shows the molar fractions of DMC, MeOH, PC and PG in the liquid phase. The high excess of MeOH resulted in dominating concentrations along the entire column. The distillate was an azeotropic mixture consisting of MeOH and DMC. Due to the large boiling point difference, the heavy-boilers PC and PG were only present in the reactive section of the column below the MeOH-feed position. Note that an accurate sampling with the feed distributors was not possible due to configurational issues; these were not shown in any concentration profile. The temperature in the vapor phase showed no distinct profile. The temperature in the upper part of the column was nearly constant due to the enrichment of the narrow-boiling azeotropic mixture. In the region of the reboiler, an increasing temperature was observed caused by the enrichment of the heavy-boilers. Table 4: Reconciled mass flow rates and operating conditions of all experiments performed in the pilot-scale column. In addition, the calculated objective function of the data reconciliation Φ is also given. MeOHfeeda m CF/MeOH

PCfeed m CF/PC

Reflux ratio

Distillateto-feed

Molar feed ratio

Obj. function

m D

Bottom product m B

RR

ratio

χ MeOH/PC

(g g-1)

(kg h-1)

(kg h-1)

(-)

9.93

2 ⋅10−3

2.194

1.787

1.73

5.99

2 ⋅10

−3

2.208

1.791

1.52

2 ⋅10

−3

2.534

1.469

4.23

−3

DFmass -1

E1 E2 E3

-1

-1

(kg h )

(kg h )

(-)

(kg kg )

3.014

0.967

1.00

0.551

2.610 2.616

1.389 1.387

1.00 1.03

0.552 0.633

Catalyst mass fraction

Distillate

Φ

wCF,cat

(mol mol-1)

6.01

E4

3.032

0.968

1.00

0.653

9.98

2 ⋅10

2.610

1.390

0.88

E5

4.537

1.449

1.00

0.650

9.98

2 ⋅10−3

3.893

2.093

1.20

16.39

2 ⋅10

−3

2.606

1.388

3.99

2 ⋅10

−3

2.650

1.341

3.85

2 ⋅10

−3

E6 E7

3.344 3.328

0.650 0.663

0.99 1.77

0.653 0.664

15.99

E8

3.020

0.971

1.78

0.658

9.91

2.624

1.367

2.81

E9

3.045

0.956

1.80

0.549

10.15

2 ⋅10−3

2.199

1.802

2.66

10.10

−3

2.198

1.840

2.96

−3

2.211

1.799

3.04

−3

2.202

1.793

0.76

2.225

1.759

3.80

E10 E11

3.070 3.044

0.968 0.966

1.80 1.79

0.544 0.551

10.04

E12

3.026

0.969

1.00

0.551

9.95

E13

3.534b

0.450

0.99

0.559

-

4 ⋅10 6 ⋅10

2 ⋅10 -

a

Given values for E1 – E12 include the amount of MeOH that entered the pilot-scale column via the catalyst feed.

b

Given value is a ternary mixture consisting of 0.129 g g-1 DMC; 0.768 g g-1 MeOH and 0.103 g g-1 PC.

17

Both profiles, concentrations and temperature, shown in Fig. 3 confirm a high reproducibility of the experimental results gathered in the pilot-scale column. An absolute average deviation of all molar fractions between the experiments of 2 ⋅ 10 −3 g g-1 was determined. The absolute average deviation of the vapor-phase temperatures between both experiments was 0.2 K – being in the error range of the PT100-thermocouples. These findings were confirmed by the comparable reactant conversions in both experiments. The PC and the MeOH conversions for experiment E1 were 53.1% and 10.7%, respectively. Experiment E12 showed a PC conversion of 53.2% and a MeOH conversion of 10.7%.

6. Modeling and Simulation A simulation model of an RD process is necessary to analyze its performance, design RD columns or optimize processes incorporating the RD technology. Several modeling approaches taking into account the transport phenomena occurring in an RD column have been presented in existing literature [44–48]. The authors distinguish between (phase)equilibrium stage (EQ) and non-equilibrium stage (NEQ) modeling approaches. The EQ approach assumes that the exiting liquid and vapor streams in each stage of the RD column are in phase equilibrium to each other. This assumption often stands in contrast to the actual behavior of the chemical system. The NEQ (or rate-based) approach takes both mass and heat transfer between the vapor and the liquid phase into account by considering the actual transport rates. The disadvantage of the NEQ approach is the high complexity and the resulting high computational effort necessary to solve the problem in comparison to the EQ approach. Therefore, both modeling approaches were compared within this work with the aim to choose the most suitable approach to describe the homogeneously catalyzed transesterification of PC with MeOH. The equation-oriented simulation environment Aspen Custom Modeler® was used to implement the modeling approaches. 6.1. Modeling Approaches for the RD Column An internally developed process simulator was used to evaluate the different modeling approaches by switching between different groups of equations [47,49,50]. The following four modeling approaches are implemented into the process simulator: ƒ (Phase-)equilibrium stage model assuming an instantaneously reached chemical equilibrium (EQ-EQ), ƒ (Phase-)equilibrium stage model taking into account the reaction kinetics (EQ-KIN), ƒ Non-equilibrium stage model using effective diffusion coefficients (NEQ), 18

ƒ Non-equilibrium stage model using the Maxwell-Stefan equations (NEQ-MS). The first three modeling approaches were compared within this work for the transesterification of PC with MeOH. Keller and Górak [39] showed that the use of the NEQMS approach did not improve the simulation results for the homogeneously catalyzed transesterification of DMC with ethanol in comparison to the NEQ approach. As both chemical systems show a similar chemical and thermodynamic behavior, this modeling approach was not evaluated in this study. EQ-EQ Modeling Approach The EQ-EQ approach was the simplest modeling approach used in this study. The RD column was modeled assuming phase and chemical equilibrium in each stage. This implies that temperature, pressure and chemical potential of each component in both the vapor and liquid phase were the same. Thus, the molar and heat fluxes across the phase interface did not need to be calculated, meaning that knowledge about the transport properties is not required. The column was axially discretized into equilibrium stages. The height of each stage was equivalent to the height equivalent to a theoretical plate (HETP) of the used packing. To calculate the HETP value of the applied Sulzer BXTM packing, a correlation developed by Carillo et al. [51] was used. The chemical equilibrium was described by applying the stationary solution of the kinetic model (Section 6.3). It was assumed that chemical equilibrium was reached in each stage, both in the liquid redistributors and in the reboiler. EQ-KIN Modeling Approach The EQ-KIN approach also assumed phase equilibrium between the exiting streams of each stage. The difference was in the description of the reactant conversion, which was realized with a kinetic approach in this case (Section 6.3). To take the homogeneously catalyzed reaction into account, the liquid hold-up in each (phase-)equilibrium stage had to be known. A correlation published by Rocha et al. [52] was implemented into the simulation model to calculate the liquid hold-up of the used Sulzer BXTM structured packings. The hold-up of the liquid redistributors and the reboiler was measured in preliminary studies (Section 4.1). NEQ Modeling Approach The NEQ approach is more detailed than the EQ approach. The system of equations is more complex in comparison to the EQ approach, resulting in a higher computational effort.

19

However, evidence has shown that the NEQ approach is better able to describe reality than the EQ approach [45]. NEQ modeling approaches take both mass and heat transfer into account by using the actual transport rates. They also account for the hydrodynamics of the column internals, typically leading to improved results [44]. The NEQ simulation approach applied in this work used the two-film theory to describe the mass and heat transfer between the vapor and the liquid phase [53]. The phase equilibrium was assumed to be reached only at the phase interface. The mass transfer rate between the two phases was determined under consideration of the effective diffusion coefficients that were used to extract the effective mass transfer coefficients from the Sherwood number proposed by Rocha et al. [52]. The effective diffusion coefficients were calculated using the proposed method of Burghardt et al. [54]. The heat transfer rate between the vapor and liquid was determined using the Chilton-Colburn analogy [55]. In the NEQ approach, the column was discretized into equidistant axial discretes rather than (phase-)equilibrium stages. The height of each discrete was calculated from the HETP value of the used packing. Our own preliminary studies indicated that the use of more than four discretes per HETP equivalent did not significantly improve the results despite the longer CPU times. Therefore, a discretization of four discretes per HETP equivalent was used. The hydrodynamic behavior of the column internals was described using the correlations presented by Bravo et al. [56] for the effective interfacial area and Rocha et al. [52] for the liquid hold-up as well as the pressure drop along the column. The reaction rate was calculated using the approach presented in Section 6.3. The Hatta number which is the ratio of the time constants of the mass transport to the chemical reaction was used to predict whether the chemical reaction in the liquid film must be taken into account. The Hatta number for RD processes can be calculated in accordance to Sundmacher et al. [57]. The calculated Hatta numbers for all experiments were much smaller than unity, with a maximum value of approximately 6 ⋅ 10 −4 . Thus, the assumption of neglecting the influence of the chemical reaction on the mass transport in the liquid film was justified. Therefore, no liquid film discretization was taken into account in this modeling approach. 6.2. Thermodynamic and Physical Properties A precise simulation of an RD process strongly depends on the availability of reliable thermodynamic and physical data [58]. The thermodynamic and physical data in this work were calculated using Aspen Plus®. Computed pure component data such as vapor pressures, densities, viscosities, surface tensions, isobaric heat capacities and thermal conductivities

20

were compared to experimental data from existing literature and showed a high accuracy for all components. The non-ideal behavior of the liquid phase was described using activities ai ( = xi ⋅ γi ) for each component. For this purpose, the recommendations by Carlson [59] were followed and the UNIQUAC gE-model [60] was chosen to calculate the activity coefficients γi . In this model, the interaction between two components is described using the temperature-dependent binary interaction coefficient τij . Eq. A.1 shows the correlation used to calculate τij, and Table A.1 summarizes the parameters used for this correlation. They were regressed to experimental vapor-liquid equilibria (VLEs) from existing literature, if available (References in Table A.1); no equilibrium data were available in the literature for the system between MeOH and PC. Therefore, the group estimation method UNIFAC [61] was used to estimate the binary UNIQUAC parameters. Non-idealities such as the self-association of components were not expected for the vapor phase; the vapor phase was thus described using the ideal gas law. A graphical comparison between the experimental VLEs and the theoretical description using the UNIQUAC gE-model shows the high accuracy of this approach and is available in the Supplementary Data. 6.3. Chemical Equilibrium and Reaction Kinetics We screened several heterogeneous and homogeneous catalysts for the transesterification of PC with MeOH in a previous publication [14]. Within our studies, no heterogeneous ionexchange resin appeared appropriate to allow for an integration of the reaction in an RD column. Therefore, we suggested the use of sodium methoxide as homogeneous catalyst. We applied this catalyst to investigate the chemical equilibrium and the reaction kinetics in the expected operating range of the RD process. We varied the temperature between 333 – 433 K, the initial molar reactant ratio between MeOH and PC among 6.0 – 14.0 mol mol-1 and the catalyst mass fraction between 4.5 ⋅10 −4 and 7.0 ⋅10 −4 g g-1. As the liquid-phase behavior of the chemical system is non-ideal, we suggested the use of activities other than molar fractions to develop a kinetic model. For the calculation of the activities, the UNIQUAC gE-model introduced in Section 6.2 was used. Eq. 1 shows the activity-based kinetic model we have derived in our previous publication.

ra ( T ) = k a ( T ) ⋅

⎤ ⎛ 1 ⎞ 1 ⎡ ⋅ a ⋅ a MeOH 2 − ⎜⎜ ⎟⎟ ⋅ a DMC ⋅ a PG ⎥ ⋅ w cat ⋅ V 3 ⎢ PC M ⎢⎣ ⎥⎦ ⎝ Ka (T ) ⎠

(1)

21

The reaction rate ra depends on the temperature-dependent activity-based reaction rate constant ka . In addition, we crafted a correlation to describe this temperature dependency [14]: ln ⎡⎣k a ( T )⎤⎦ = 24.73 − 3494.63 ⋅ T-1

(2)

The reaction rate depends not only on the mean molecular weight M , the catalyst mass fraction wcat and the liquid hold-up of the reaction mixture V but also on the temperaturedependent activity-based chemical equilibrium constant K a . Eq. 3 shows the correlation used to describe the temperature dependency of the activity-based chemical equilibrium constant. ln ⎡⎣K a ( T )⎤⎦ = −5.41 + 1145.25 ⋅ T-1

(3)

Based on our measurements, a standard enthalpy for the exothermic reaction of ΔhR0 = -9.522 ± 0.858 kJ mol-1 has been determined which was subsequently integrated into the energy balances of the RD process model accounting for the chemical reaction.

7. Model Selection and Validation The modeling of an RD process requires a correct description of the thermodynamic and physical properties, the mass and heat transfer between the vapor and liquid phase and the hydrodynamics. In addition, the chemical equilibrium and the reaction kinetics must be accurately described. To select an appropriate modeling approach for the homogeneously catalyzed transesterification of PC with MeOH, the results of 13 pilot-scale experiments were compared to the simulated results generated from each of the modeling approaches presented in Section 6.1. Górak [62] emphasized that the use of experimental composition and temperature profiles is mandatory for proper model selection and validation. Thus, the profiles were used alongside the reactant conversions for this purpose. Fig. 4 compares the experimental and simulated results for experiment E9. Symbols represent the experimental results and lines represent the simulated results for the three investigated modeling approaches. Significant differences in the theoretical description of the composition and temperature profiles were found. The liquid-phase composition profile showed an insufficient accuracy using the EQ-EQ approach. In this case, the simulated product concentration is too high throughout the entire column. The two modeling approaches EQKIN and NEQ were able to predict the composition profile with a comparable and high accuracy. However, slight deviations between the experimental and simulated molar fractions

22

in the reactive section of the RD column were observed. The product concentrations calculated with the EQ-KIN and NEQ modeling approaches were slightly lower than the experimentally measured concentrations. In contrast, the reactant concentrations were overestimated by both modeling approaches. The most probable explanation for this behavior is an ongoing reaction in the glass vials after the sampling procedure. This hypothesis is supported by the well-predicted bottom product, where no ongoing reaction was supposed because the experimental samples were already in chemical equilibrium according to the simulation results. The simulated vapor-phase temperature profiles had a similar course for all modeling approaches, matching the experimental results with high precision. Nevertheless, deviations between the experimental and simulated temperature on the lowest redistributor were found. The reason for this discrepancy is discussed in Section 7.1.

Figure 4: Comparison of experimental and simulated results for pilot-scale RD experiment E9. This experiment was performed at RR = 1.8, DFmass = 0.55 kg kg-1, χ MeOH/PC = 10.0 mol mol-1 and wCF,cat = 2 ⋅ 10 − 3 g g-1. Closed symbols represent experimental and lines the corresponding simulated results. Continuous lines are simulation results using the EQ-EQ, dashed lines using the EQ-KIN and dotted lines using the NEQ modeling approach: (left) molar composition profile of the liquid phase including DMC, MeOH, PC and PG; (right) temperature profile of the vapor phase.

The experimental PC conversion was found to be 57.8% for this experiment. The simulated PC conversion using the EQ-EQ approach was overestimated, with a value of 73.9%. The other two simulation approaches resulted in a PC conversion of 59.7% for the EQ-KIN and 59.6% for the NEQ, in good accordance with the experimental results. The same was observed for the MeOH conversion. Thus, the use of reaction kinetics to describe the chemical reaction of this system in an RD column is necessary due to the low reaction rate and the EQ-EQ approach was excluded from further studies. A comparison between the EQKIN and NEQ approach did not allow a final choice of the modeling depth based on experiment E9 because the results were comparable. Therefore, a similar procedure was followed for all experiments performed within this work. The Supplementary Data contains a comparison between the experimental and simulated conversions using the three modeling approaches. The average absolute deviation of the PC conversion using the EQ-EQ approach 23

was 17.2%, while the deviation using the EQ-KIN approach was 1.9% and the use of the NEQ approach led to an absolute average deviation of 1.5%. This, along with the non-ideal thermodynamic behavior of the chemical system indicates the advantage of the NEQ approach. The theoretical optimization of the homogeneously catalyzed transesterification of PC with MeOH in an industrial-scale column needing high reactant conversions and product purities should be conducted using the presented NEQ modeling approach. In the following, the simulated lines are always calculated using the NEQ approach. Moreover, a comparison of experimental and simulated results using the NEQ modeling approach for experiment E13 which was conducted without adding catalyst to the pilot-scale column was performed. A graphical comparison of the results is included in the Supplementary Data, emphasizing the reliability of the thermodynamic and physical property models. 7.1. Non-ideality of the Naturally Circulating Reboiler

Despite the high accuracy of the NEQ modeling approach, the simulation model was not able to predict the experimentally determined temperature on the lowest liquid redistributor. The simulation model always assumed that the reboiler would act as a (phase-)equilibrium stage and was thus not able to predict the performed experiments. Keskinen et al. [63] and Jaćimović et al. [64] found that a reboiler exhibits a non-ideal behavior depending on (1) the type of reboiler, (2) the vaporization fraction and (3) the wideness of the boiling points of the components present. They found that naturally circulating reboilers do not act as (phase)equilibrium stages. In addition, the large difference between the boiling points of MeOH and PC ( ΔTb ~ 175 K) supported the non-ideal behavior of the reboiler. Thus, Keskinen et al. [63] suggested the implementation of a reboiler efficiency Ei (Eq. 4) into the simulation model. Ei =

yiout yieq

i = 1,…,nC

(4)

yiout is the molar fraction of component i leaving the reboiler as vapor; yieq is the molar fraction of component i in the vapor phase standing in phase equilibrium with the liquid phase. As the composition of the vapor phase leaving the reboiler was not measured within the experiments, it was not possible to directly calculate the reboiler efficiency. Thus, the reboiler efficiency was considered as an adjustable model parameter. Due to the lack of data, the efficiency was assumed to be identical for all components in the same experiment. Fig. 5 compares the simulated vapor-phase temperature profiles for a reboiler efficiency of 1 and 1.14, regressed to the experimental results of experiment E9. To determine the reboiler 24

efficiency, a least-square regression with the objective to minimize the error between experimental and simulated vapor-phase temperatures in the pilot-scale column was performed.

Figure 5: Comparison of experimental and simulated vapor-phase temperature profiles using the NEQ approach and considering the reboiler non-ideality for pilot-scale RD experiment E9. Symbols represent experimental results, and the lines represent the corresponding simulated results. Continuous lines are simulation results using an ideal and dashed lines using a non-ideal approach for the reboiler.

The temperature profile showed good agreement between the experimental and simulated results using the reboiler efficiency. The large boiling point difference between the involved components resulted in only minor composition changes when the temperature was varied. Thus, the composition profile, which is not shown here, was not affected by the reboiler efficiency. The reboiler efficiency was regressed for all pilot-scale experiments, resulting in efficiencies varying between 1.1 and 1.6. A connection between the reboiler efficiency and the molar ratio between the low and heavy-boilers in the bottom product stream, in this case between MeOH and PC, was found. Fig. 6 shows an increasing non-ideality for a decreasing molar ratio between MeOH and PC in the reboiler. Therefore, the non-ideality increased the more PC was present in the reboiler and thus, the higher the boiling temperature of the mixture in the reboiler was. Fig. 7 shows the parity-plots of the experimental and simulated molar fractions in the liquid phase, as well as the comparison of the experimentally determined and simulated temperatures in the vapor phase. The left diagram not only shows a high accuracy for the prediction of the liquid-phase composition in the range of high MeOH concentrations but also for the small concentrations of DMC, PC and PG. The right side of Fig. 7 also shows a high accuracy for all simulated temperatures except for the temperatures on the lowest liquid redistributor. The diagram also shows the increasing non-ideality for an increasing temperature and, thus for a decreasing molar ratio between MeOH and PC in the reboiler. The

25

open symbols show the improvement made by introducing reboiler efficiency into the simulation model.

Figure 6: Correlation between the regressed reboiler efficiency and the molar ratio between MeOH and PC in the bottom product for the experiments E1 – E13. The symbols represent the results of a regression using the NEQ modeling approach; the continuous line is an interpolation between the regressed values.

The slight deviation in the temperature on the lowest liquid redistributor was not crucial for the simulation of the homogeneously catalyzed transesterification of PC with MeOH. Therefore, to keep the model fully predictive, the reboiler efficiency was neglected in our further studies using the validated NEQ modeling approach.

Figure 7: Parity-plots for the developed NEQ approach to simulate the homogeneously catalyzed RD process for the transesterification of PC with MeOH: (left) Comparison between experimental and simulated molar fractions in the liquid phase. (right) Comparison between experimental and simulated temperatures in the vapor phase. The closed symbols represent simulation results using an ideal approach for the reboiler, open symbols were calculated using the non-ideal approach by considering the reboiler efficiency.

26

8. Process Analysis In this section, the effects of decisive operating parameters on the experimental and simulated composition and temperature profiles are shown. The influence of the operating parameters on the PC conversion and the product purities was investigated to identify a suitable operating range to produce high-purity dimethyl carbonate and propylene glycol on an industrial-scale. Within this section, the influence of (1) the reflux ratio RR , (2) the mass-based distillate-tofeed ratio DFmass , (3) the molar feed ratio between MeOH and PC χMeOH/PC and (4) the catalyst mass fraction in the feed wCF,cat was studied at an overall feed mass flow rate of 4.0

 CF and the resulting effects of both liquid kg h-1. The influence of the feed mass flow rate m and vapor load on the pilot-scale column were also investigated. Because the influence of the feed mass flow rate on the column profiles and the PC conversion was negligible, the results are not presented in this section; they are discussed in the Supplementary Data. 8.1. Reflux Ratio

The effect of the reflux ratio in the given operating range is shown in Fig. 8, which presents the experimental and simulated composition and temperature profiles of the experiments E4 and E8. The operating conditions are listed in Table 4 and differ only in the reflux ratio having values of 1.0 and 1.8, respectively. The symbols represent the experimental results and the lines represent the calculated results using the NEQ approach.

Figure 8: Influence of the reflux ratio R R on the pilot-scale RD column performance. This investigation was performed at DFmass = 0.65 kg kg-1, χ MeOH/PC = 10.0 mol mol-1 and wCF,cat = 2 ⋅ 10 − 3 g g-1. Closed symbols and continuous lines represent results for experiment E4 ( R R = 1.0); open symbols and dashed lines represent experiment E8 ( R R = 1.8): (left) molar composition profile of the liquid phase including DMC, MeOH, PC and PG; (right) temperature profile of the vapor phase.

The experimental results of both experiments qualitatively show the same behavior. Because of the relatively high molar feed ratio of χMeOH/PC = 10.0 mol mol-1, the MeOH molar fraction dominated the liquid-phase composition profile in the entire column for both experiments. In 27

the non-reactive section, the varied reflux ratio had only a small effect on the composition profile. The DMC molar fraction increased slightly by raising the reflux ratio due to the lowboiling azeotrope between MeOH and DMC; the enrichment in the non-reactive section was enhanced at higher reflux rates. However, the reflux ratio had a strong impact on the composition profile in the reactive section. At an increased reflux ratio, a larger reflux stream rich in MeOH entered the RD column, yielding a higher MeOH concentration and increased internal flow rates in the reactive section. The homogeneous catalyst, which had the same concentration referred to the feed mass flow rate for both experiments, was thus diluted at a higher reflux ratio, resulting in a lowered reaction rate. In addition, the higher internal flow rates resulted in a shortened residence time of PC in the reactive section. Nevertheless, the conversion of both reactants increased through raising the reflux ratio. The experimental PC conversion, for instance, increased from 51.9% to 56.0% between both experiments. Therefore, the catalyst dilution which had a linear influence on the reaction rate was overcompensated by the increased MeOH concentration in the reactive section which had a quadratic influence on the reaction rate (Eq. 1). The discussed effect of the reflux ratio on the composition profile was also identified in the vapor-phase temperature profile. While the temperature above the PC-feed remained unchanged by raising the reflux ratio, the temperature in the reactive section increased, especially on the lowest liquid redistributor. This temperature increase was caused by a higher PG concentration in the bottom product. For further optimization studies aimed at high reactant conversions and product purities, it can be concluded that, in the investigated operating range, an increased reflux ratio leads to raised reactant conversions as well as higher purities of DMC in the distillate and of PG in the bottom product. 8.2. Mass-based Distillate-to-feed Ratio

Fig. 9 shows the influence of the mass-based distillate-to-feed ratio in the investigated operating range while all other operational parameters remained constant. For this purpose, pilot-scale experiments E9 ( DFmass = 0.55 kg kg-1) and E8 ( DFmass = 0.65 kg kg-1) were compared. A similar course of both profiles for experiments E9 and E8 was found. The composition profile was dominated by the MeOH molar fraction, again caused by the high molar feed ratio. The distillate of both experiments consisted of a near-azeotropic mixture. The distillate-to-feed ratio exhibited a minor influence on the composition in the non-reactive section, a low influence on the composition in the reactive section and a major influence on the composition in the reboiler. At higher distillate-to-feed ratios, the light-boiler MeOH is preferentially stripped out of the reboiler, leading to a higher MeOH concentration in the

28

reactive section. The first result of this is a PG molar fraction in the bottom product increasing from 0.148 mol mol-1 to 0.218 mol mol-1 between both experiments. However, the conversion of both reactants decreased with an increased distillate-to-feed ratio. The experimental PC conversion for experiment E9 was 57.8%, compared to 56.0% for E8. Because of the higher internal flow rates at higher distillate-to-feed ratios, the dilution of the homogeneous catalyst in the reactive section increased. In this operating range of the distillate-to-feed ratio, the positive effect of the increased MeOH concentration in the reactive section is relativized by the dilution of the homogeneous catalyst, resulting in a reduced reaction rate and in lower reactant conversions.

Figure 9: Influence of the mass-based distillate-to-feed ratio DFmass on the pilot-scale RD column performance. This investigation was performed at R R = 1.8, χ MeOH/PC = 10.0 mol mol-1 and wCF,cat = 2 ⋅ 10 − 3 g g-1. Closed symbols and continuous lines represent results for experiment E9 ( DFmass = 0.55 kg kg-1); open symbols and dashed lines represent experiment E8 ( DFmass = 0.65 kg kg-1): (left) molar composition profile of the liquid phase including DMC, MeOH, PC and PG; (right) temperature profile of the vapor phase.

These findings were supported by the temperature profile in the vapor phase. The decreasing MeOH molar fraction in the bottom of the pilot-scale column resulted in increased temperatures in this section. The upper part of the temperature profile was not affected by a change in the distillate-to-feed ratio. For further optimization studies, it can be concluded that a raised distillate-to-feed ratio results in a decreased reactant conversion in this operating range. However, a higher purity of PG in the bottom product and a constant purity of DMC in the distillate are achieved in this operating range. 8.3. Molar Feed Ratio

The strong effect of the molar feed ratio between MeOH and PC on the RD column performance is illustrated in Fig. 10. For this purpose, experiment E2 (performed at a molar feed ratio of 6.0 mol mol-1) was compared to experiment E1 (conducted at a molar feed ratio of 10.0 mol mol-1). The other operating parameters were kept constant and are listed in Table 4.

29

Figure 10: Influence of the molar feed ratio χ MeOH/PC on the pilot-scale RD column performance. This investigation was performed at R R = 1.0, DFmass = 0.55 kg kg-1 and wCF,cat = 2 ⋅ 10 − 3 g g-1. Closed symbols and continuous lines represent results for experiment E2 ( χ MeOH/PC = 6.0 mol mol-1); open symbols and dashed lines represent experiment E1 ( χ MeOH/PC = 10.0 mol mol-1): (left) molar composition profile of the liquid phase including DMC, MeOH, PC and PG; (right) temperature profile of the vapor phase.

The increase of the molar feed ratio resulted in an increased MeOH molar fraction in the reactive section of the RD column. The higher MeOH, and the subsequent lower PC concentration in the reactive section, caused a strong increase of the experimental PC conversion, from 33.9% to 53.1% between the two studied operating points. Conversely, the MeOH conversion dropped from 11.3% for experiment E2 to 10.7% in experiment E1 due to the increased molar excess. Surprisingly, the composition profile in the non-reactive section remained unchanged. Therefore, the distillate in both experiments consisted of an almost identical near-azeotropic mixture. The temperature profile of the vapor phase was also affected by an increased molar feed ratio in the investigated operating range of the pilot-scale column. Due to the raised presence of the light-boiler MeOH in the reactive section at higher molar feed ratios, the temperature dropped in this section. The temperature in the non-reactive section remained constant. To summarize, an increasing molar feed ratio noticeably increases the PC conversion but lowers the MeOH conversion. The DMC purity in the distillate remains unchanged, while the purity of PG in the bottom product decreases in the investigated operating range. 8.4. Catalyst Mass Fraction

Fig. 11 illustrates the effects of a varying catalyst mass fraction in the feed on the RD column performance, with experiment E9 ( wCF,cat = 2 ⋅ 10 −3 g g-1) compared to experiment E11 ( wCF,cat = 6 ⋅ 10 −3 g g-1). All other operating parameters were kept constant for this study. The catalyst mass fraction in the feed exhibited a strong influence on the composition profiles of both experiments. An increased catalyst mass fraction in the feed also resulted in an increased catalyst mass fraction in the reactive section of the pilot-scale column. The reaction rate was thus increased, yielding a lowered reactant but increased product concentration in the 30

entire column. The reactant conversions also increased; the experimental PC conversion rose from 57.8% for experiment E9 to 66.6% by tripling the catalyst mass fraction in experiment E11. The catalyst mass fraction was the only operating parameter that had a major influence on the concentration profile in the non-reactive section. The DMC concentration in the distillate increased up to the azeotropic composition for an increased catalyst mass fraction. The temperature profile of the vapor phase was not sensitive towards a variation of the catalyst mass fraction between experiments E9 and E11. To conclude, an increasing catalyst mass fraction in the feed raises the conversion of both reactants. The DMC purity in the distillate increases up to the azeotropic composition, while the PG purity in the bottom product rises slightly in the investigated operating range.

Figure 11: Influence of the catalyst mass fraction wCF,cat on the pilot-scale RD column performance. This investigation was performed at R R = 1.8, DFmass = 0.55 kg kg-1 and χ MeOH/PC = 10.0 mol mol-1. Closed symbols and continuous lines represent results for experiment E9 ( wCF,cat = 2 ⋅ 10 − 3 g g-1); open symbols and dashed lines represent experiment E11 ( wCF,cat = 6 ⋅ 10 − 3 g g-1): (left) molar composition profile of the liquid phase including DMC, MeOH, PC and PG; (right) temperature profile of the vapor phase.

9. Conclusions The demand for high-purity dimethyl carbonate and propylene glycol has rapidly increased in recent years. Dimethyl carbonate is in particular demand; it is considered to be an efficient fuel additive and a promising alternative for methyl-tert-butyl ether. One route to synthesize both components is the transesterification of propylene carbonate with methanol using the homogeneous catalyst sodium methoxide. However, the synthesis and purification is challenging and cost-intensive due to the unfavored chemical equilibrium for the reaction and the complex thermodynamic behavior for this system. Therefore, the current industrial-scale process required to conduct the transesterification of propylene carbonate with methanol comprises several distillation columns interconnected in a complex recycling structure for product purification. Process intensification, in particular reactive distillation, is able to significantly decrease the number of apparatuses needed for the transesterification reaction, potentially resulting in decreased investment costs. The operating costs can also be reduced, 31

resulting in substantially improved sustainability. To achieve these advantages, an integrated extensive theoretical and experimental study at meaningful scale must be performed to prove the feasibility of reactive distillation for this chemical system. To our knowledge, this study presented the first experimental results of the transesterification of propylene carbonate with methanol in a reactive distillation column. The glass column had a nominal diameter of 50 mm and an overall packing height of 5.12 m. Twelve pilot-scale reactive distillation experiments were performed based on a factorial design of experiments varying the reflux ratio, the mass-based distillate-to-feed ratio, the molar feed ratio, the catalyst mass fraction in the feed and the feed mass flow rate. All experiments were verified with data reconciliation, and the results of this showed both the feasibility of this process and the high reliability of the experimental data gained in this study. In preparation of the model validation, a physical property set was established using Aspen Plus® and verified against experimental data from existing literature. A model selection and validation based on the experimental liquid-phase composition and vapor-phase temperature profiles was then performed. In addition, reactant conversions were used to evaluate the quality of the different modeling approaches. High accuracies for (phase-)equilibrium and non-equilibrium stage models both considering the reaction kinetics were found. Nonetheless, a deviation between the experimental and simulated results was found in the lower part of the vapor-phase temperature profile. The explanation for this was an experimental non-ideality of the naturally circulating reboiler. The non-ideality decreased for an increasing molar ratio between the low and heavy-boiler in the reboiler. A correlation to describe this behavior in a theoretical way was determined. However, to keep the simulation model predictive, this correlation was not implemented into the model because the composition profile and the reactant conversions were not affected by the reboiler non-ideality. The authors believe that the non-ideality can be reduced in the latter process by selecting another type of reboiler. Due to the complex thermodynamic behavior of this system and the high purity requirements in later process optimization studies, the non-equilibrium stage model was chosen to simulate the reactive distillation process. Finally, the influence of the operating parameters on the column profiles and the propylene carbonate conversion was discussed using both experimental and simulated results. This study provided information that can be used to identify an appropriate operating window for an industrial-scale process requiring high reactant conversions and product purities. To obtain a high conversion of propylene carbonate, a high reflux ratio, a high molar feed ratio and a high catalyst mass fraction were found to be necessary. To end up with a high purity of propylene glycol in the bottom product, a high reflux ratio, a high mass-based distillate-to-feed ratio, a low molar feed ratio

32

and a high catalyst mass fraction are advisable. Besides a high reflux ratio, a high catalyst mass fraction offers the largest leverage to increase the purity of dimethyl carbonate in the distillate. In future studies, we will focus on possibilities to separate the near-azeotropic distillate consisting of dimethyl carbonate and methanol. The validated non-equilibrium stage model will then be used to perform an economic process optimization of the transesterification of propylene carbonate with methanol on an industrial-scale.

Acknowledgements The authors gratefully acknowledge the German Federal Ministry of Education and Research (Project number: 01 RC1008H) for providing financial support, Sulzer Chemtech Ltd. for providing the structured packings and W.R. Grace & Co. for providing the molecular sieves.

33

Appendix The Appendix contains the correlation used to calculate the UNIQUAC binary interaction coefficient τij . The two parameters aij and bij applied to compute the interaction coefficient for each binary system are also given. b ⎞ ⎛ τij = exp ⎜ a ij + ij ⎟ T⎠ ⎝

(A.1)

Table A.1: Binary interaction parameters aij and bij used to calculate the UNIQUAC binary interaction coefficient (Eq. A.1). The references used for the determination of the interaction parameters are also given. Component 1 Component 2 aij bij (K) Ref. i j MeOH

DMC

1

2

-0.201

14.870

2

1

0.273

-306.550

2

0.000

- 42.880

MeOH

PG

1 2

1

0.000

90.698

MeOH

PC

1

2

0.000

- 38.031

2

1

0.000

-205.152

2

0.000

-209.935

DMC

PG

1 2

1

0.000

-2.664

DMC

PC

1

2

0.000

-110.727

2

1

0.000

41.865

1

2

1.494

-958.829

2

1

-1.418

674.112

PG a

PC

[37] [65] UNIQUACa [66] [66] [67]

The binary interaction parameters were estimated using the UNIFAC group contribution method.

Supplementary Data The Supplementary Data underlines the high accuracy of the applied analytics by showing a quality check of the gas chromatography analysis. Photographs of the pilot-scale column are shown. Afterwards, the selection of column internals for the investigated chemical system is then discussed, followed by a presentation of the applied data reconciliation. A table including all thermodynamic and physical property models used in Aspen Plus® and graphical comparisons of the experimental and simulated VLEs are shown to validate the UNIQUAC gE-model. The high accuracy of the applied thermodynamic and physical properties is supported by a graphical comparison of the experimental and simulated results for a pilotscale distillation experiment performed without adding the homogeneous catalyst to the column. Additionally, a summary of the operating conditions, the liquid-phase composition and the vapor-phase temperature profiles is given. For the RD experiments, the reactant

34

conversions are also shown. Furthermore, a table comparing the experimental reactant conversions with the calculated reactant conversions gathered using all the presented modeling approaches is given. Finally, the influence of the liquid and vapor loads on the performance of the RD column is discussed in detail.

35

References [1] P. Tundo, M. Selva, The Chemistry of Dimethyl Carbonate, Acc. Chem. Res. 35 (2002) 706–716. [2] S. Chankeshwara, Dimethyl Carbonate (DMC): A Versatile and Environmentally Benign Building Block, Synlett (2008) 624–625. [3] M.A. Pacheco, C.L. Marshall, Review of Dimethyl Carbonate (DMC) Manufacture and Its Characteristics as a Fuel Additive, Energy Fuels 11 (1997) 2–29. [4] D. Delledonne, F. Rivetti, U. Romano, Developments in the Production and Application of Dimethylcarbonate, Appl. Catal., A 221 (2001) 241–251. [5] M. Bilde, T.E. Møgelberg, J. Sehested, O.J. Nielsen, T.J. Wallington, M.D. Hurley, S.M. Japar, M. Dill, V.L. Orkin, T.J. Buckley, R.E. Huie, M.J. Kurylo, Atmospheric Chemistry of Dimethyl Carbonate, J. Phys. Chem. A 101 (1997) 3514–3525. [6] W.B. Kim, U.A. Joshi, J.S. Lee, Making Polycarbonates without Employing Phosgene: An Overview on Catalytic Chemistry of Intermediate and Precursor Syntheses for Polycarbonate, Ind. Eng. Chem. Res. 43 (2004) 1897–1914. [7] Y. Chang, C. Shu, Flammability Properties Analysis of Methylphenol-carbonate in Diphenylcarbonate Production Process, J. Therm. Anal. Calorim. 93 (2008) 135–141. [8] M. Berhil, N. Lebrun, A. Tranchant, R. Messina, Reactivity and Cycling Behaviour of Lithium in Propylene Carbonate-Ethylene Carbonate-Dimethyl Carbonate Mixtures, J. Power Sources 55 (1995) 205–210. [9] C.J. Sullivan, Propanediols, in: Ullmann's Encyclopedia of Industrial Chemistry, WileyVCH, Chichester, 2010. [10] SRI International, Chemical Economics Handbook Report: Propylene Glycols, Menlo Park, 2004. [11] D.S. Bausmith, R.D. Neufeld, Soil Biodegradation of Propylene Glycol Based Aircraft Deicing Fluids, Water Environ. Res. 71 (1999) 459–464. [12] K. Tomishige, H. Yasuda, Y. Yoshida, M. Nurunnabi, B. Li, K. Kunimori, Catalytic Performance and Properties of Ceria Based Catalysts for Cyclic Carbonate Synthesis from Glycol and Carbon Dioxide, Green Chem. 6 (2004) 206. [13] P.T. Anastas, M.M. Kirchhoff, Origins, Current Status, and Future Challenges of Green Chemistry, Acc. Chem. Res. 35 (2002) 686–694. [14] J. Holtbruegge, M. Leimbrink, P. Lutze, A. Górak, Synthesis of Dimethyl Carbonate and Propylene Glycol by Transesterification of Propylene Carbonate with Methanol: Catalyst Screening, Chemical Equilibrium and Reaction Kinetics, Chem. Eng. Sci. (2013) accepted. [15] J.S. Buchanan, Z. Jiang, J.A. Kowalski, J.G. Santiesteban, Integrated Process for Preparing Dialkyl Carbonates and Diols, Patent US 6,407,279, 2002. [16] J. Holtbruegge, P. Lutze, A. Górak, Modeling, Simulation and Experimental Investigation of a Reactive Hybrid Process for the Production of Dimethyl Carbonate, in: I.A. Karimi, R. Srinivasan (Eds.), 11th International Symposium on Process Systems Engineering, Elsevier, Amsterdam, 2012, pp. 1241–1245. [17] G.J. Harmsen, Reactive Distillation: The Front-runner of Industrial Process Intensification, Chem. Eng. Process. 46 (2007) 774–780. [18] V.H. Agreda, L.H. Partin, W.H. Heise, High-purity Methyl Acetate via Reactive Distillation, Chem. Eng. Prog. (1990) 40–46. [19] A. Orjuela, A. Kolah, C.T. Lira, D.J. Miller, Mixed Succinic Acid/Acetic Acid Esterification with Ethanol by Reactive Distillation, Ind. Eng. Chem. Res. 50 (2011) 9209–9220.

36

[20] M. Cruz-Díaz, C. Buchaly, P. Kreis, E.S. Pérez-Cisneros, R. Lobo-Oehmichen, A. Górak, Synthesis of n-Propyl Propionate in a Pilot-plant Reactive Distillation Column: Experimental Study and Simulation, Comput. Chem. Eng. 39 (2012) 118–128. [21] P. Patidar, S.M. Mahajani, Esterification of Fusel Oil using Reactive Distillation – Part I: Reaction Kinetics, Chem. Eng. J. 207-208 (2012) 377–387. [22] A. Niesbach, R. Fuhrmeister, T. Keller, P. Lutze, A. Górak, Esterification of Acrylic Acid and n-Butanol in a Pilot-scale Reactive Distillation Column—Experimental Investigation, Model Validation, and Process Analysis, Ind. Eng. Chem. Res. 51 (2012) 16444–16456. [23] S. Steinigeweg, J. Gmehling, Transesterification Processes by Combination of Reactive Distillation and Pervaporation, Chem. Eng. Process. 43 (2004) 447–456. [24] T. Keller, J. Holtbruegge, A. Górak, Transesterification of Dimethyl Carbonate with Ethanol in a Pilot-scale Reactive Distillation Column, Chem. Eng. J. 180 (2012) 309– 322. [25] K.-D. Mohl, A. Kienle, E.-D. Gilles, P. Rapmund, K. Sundmacher, U. Hoffmann, Steady-state Multiplicities in Reactive Distillation Columns for the Production of Fuel Ethers MTBE and TAME: Theoretical Analysis and Experimental Verification, Chem. Eng. Sci. 54 (1999) 1029–1043. [26] W. Kiatkittipong, P. Intaracharoen, N. Laosiripojana, C. Chaisuk, P. Praserthdam, S. Assabumrungrat, Glycerol Ethers Synthesis from Glycerol Etherification with tert-Butyl Alcohol in Reactive Distillation, Comput. Chem. Eng. 35 (2011) 2034–2043. [27] P.J. Darda, V.V. Ranade, Isophorone Reactor: Modelling and Performance Enhancement, Chem. Eng. J. 207-208 (2012) 349–367. [28] M. Shah, A.A. Kiss, E. Zondervan, A.B. de Haan, Pilot-scale Experimental Validation of Unsaturated Polyesters Synthesis by Reactive Distillation, Chem. Eng. J. 213 (2012) 175–185. [29] K. Sundmacher, A. Kienle, Reactive Distillation, Wiley-VCH, Weinheim, 2003. [30] R.S. Hiwale, N.V. Bhate, Y.S. Mahajan, S.M. Mahajani, Industrial Applications of Reactive Distillation: Recent Trends, Int. J. Chem. Reactor Eng. 2 (2004) 1–52. [31] C.D. Holland, Fundamentals of multicomponent distillation, McGraw-Hill, New York, 1981. [32] Y. Fang, W. Xiao, Experimental and Modeling Studies on a Homogeneous Reactive Distillation System for Dimethyl Carbonate Synthesis by Transesterification, Sep. Purif. Technol. 34 (2004) 255–263. [33] Y. Fang, D. Liu, A Reactive Distillation Process for an Azeotropic Reaction System: Transesterification of Ethylene Carbonate with Methanol, Chem. Eng. Commun. 194 (2007) 1608–1622. [34] S.-J. Wang, C.-C. Yu, H.-P. Huang, Plant-wide Design and Control of DMC Synthesis Process via Reactive Distillation and Thermally Coupled Extractive Distillation, Comput. Chem. Eng. 34 (2010) 361–373. [35] S. Schrödle, R. Buchner, W. Kunz, Automated Apparatus for the Rapid Determination of Liquid–liquid and Solid–liquid Phase Transitions, Fluid Phase Equilib. 216 (2004) 175– 182. [36] Y.-J. Fang, J.-M. Qian, Isobaric Vapor−Liquid Equilibria of Binary Mixtures Containing the Carbonate Group −OCOO−, J. Chem. Eng. Data 50 (2005) 340–343. [37] A. Rodríguez, J. Canosa, A. Domínguez, J. Tojo, Vapour–Liquid Equilibria of Dimethyl Carbonate with Linear Alcohols and Estimation of Interaction Parameters for the UNIFAC and ASOG Method, Fluid Phase Equilib. 201 (2002) 187–201. [38] NIST, Chemistry Web Book: http://webbook.nist.gov/chemistry, accessed December 2012.

37

[39] T. Keller, A. Górak, Modelling of Homogeneously Catalysed Reactive Distillation Processes in Packed Columns: Experimental Model Validation, Comput. Chem. Eng. 48 (2013) 74–88. [40] F. Reepmeyer, J.-U. Repke, G. Wozny, Time Optimal Start-up Strategies for Reactive Distillation Columns, Chem. Eng. Sci. 59 (2004) 4339–4347. [41] H.-X. Wu, Z.-G. Tang, H. Hu, C. Quan, H.-H. Song, S.-Y. Li, Predictions for Start-up Processes of Reactive Distillation Column via Artificial Neural Network, Chem. Eng. Technol. 29 (2006) 744–749. [42] R.L. de la Fuente, A.F. Tlacuahuac, Optimal Start-up and Product Transition Policies of a Reactive Distillation Column, Ind. Eng. Chem. Res. 46 (2007) 2092–2111. [43] I.-K. Lai, Y.-C. Liu, C.-C. Yu, M.-J. Lee, H.-P. Huang, Production of High-purity Ethyl Acetate using Reactive Distillation: Experimental and Start-up Procedure, Chem. Eng. Process. 47 (2008) 1831–1843. [44] R. Taylor, R. Krishna, Modelling Reactive Distillation, Chem. Eng. Sci. 55 (2000) 5183– 5229. [45] R. Taylor, R. Krishna, Modeling of Homogeneous and Heterogeneous Reactive Distillation Processes, in: K. Sundmacher, A. Kienle (Eds.), Reactive Distillation, WileyVCH, Weinheim, 2003, pp. 215–240. [46] C. Noeres, E. Kenig, A. Górak, Modelling of Reactive Separation Processes: Reactive Absorption and Reactive Distillation, Chem. Eng. Process. 42 (2003) 157–178. [47] M. Klöker, E.Y. Kenig, A. Hoffmann, P. Kreis, A. Górak, Rate-based Modelling and Simulation of Reactive Separations in Gas/Vapour–liquid Systems, Chem. Eng. Process. 44 (2005) 617–629. [48] E.Y. Kenig, A. Górak, Modeling of Reactive Distillation, in: F. Keil (Ed.), Modeling of Process Intensification, Wiley-VCH, Weinheim, 2007, pp. 323–363. [49] A. Górak, A. Hoffmann, Catalytic Distillation in Structured Packings: Methyl Acetate Synthesis, AIChE J. 47 (2001) 1067–1076. [50] A. Hoffmann, C. Noeres, A. Górak, Scale-up of Reactive Distillation Columns with Catalytic Packings, Chem. Eng. Process. 43 (2004) 383–395. [51] F. Carillo, A. Martín, A. Roselló, A Shortcut Method for the Estimation of Structured Packings HEPT in Distillation, Chem. Eng. Technol. 23 (2000) 425–428. [52] J.A. Rocha, J.L. Bravo, J.R. Fair, Distillation Columns Containing Structured Packings: A Comprehensive Model for their Performance. 1. Hydraulic Models, Ind. Eng. Chem. Res. 32 (1993) 641–651. [53] W.K. Lewis, W.G. Whitman, Principles of Gas Absorption, Ind. Eng. Chem. 16 (1924) 1215–1220. [54] A. Burghardt, K. Warmuziński, J. Buzek, A. Pytlik, Diffusional Models of Multicomponent Distillation and their Experimental Verification, Chem. Eng. J. 26 (1983) 71–84. [55] T.H. Chilton, A.P. Colburn, Distillation and Absorption in Packed Columns: A Convenient Design and Correlation Method, Ind. Eng. Chem. 27 (1935) 255–260. [56] J.L. Bravo, J.A. Rocha, J.R. Fair, Mass Transfer in Gauze Packings, Hydrocarbon Process. (1985) 91–95. [57] K.A. Sundmacher, L.K. Rihko, U. Hoffmann, Classification of Reactive Distillation Processes by Dimensionless Numbers, Chem. Eng. Commun. 127 (1994) 151–167. [58] H. Hasse, Thermodynamics of Reactive Separations, in: K. Sundmacher, A. Kienle (Eds.), Reactive Distillation, Wiley-VCH, Weinheim, 2003, pp. 63–96. [59] E.C. Carlson, Don't Gamble with Physical Properties for Simulations, Chem. Eng. Prog. (1996) 35–46.

38

[60] D.S. Abrams, J.M. Prausnitz, Statistical Thermodynamics of Liquid Mixtures: A New Expression for the Excess Gibbs Energy of Partly or Completely Miscible Systems, AIChE J. 21 (1975) 116–128. [61] A. Fredenslund, R.L. Jones, J.M. Prausnitz, Group-contribution Estimation of Activity Coefficients in Nonideal Liquid Mixtures, AIChE J. 21 (1975) 1086–1099. [62] A. Górak, Eine neue Berechnungsmethode für den axialen Konzentrationsverlauf bei der Mehrstoffrektifikation in Füllkörperkolonnen: Diskussion der Berechnungsergebnisse, Verfahrenstechnik 17 (1983) 469–473. [63] K.I. Keskinen, T. Nyman, J. Björk, J. Aittamaa, Considering the Non-ideality of Reboilers in the Calculation and Design of Distillation Columns, in: S.K. Sikdar (Ed.), AIChE Annual Meeting 2002, American Institute of Chemical Engineers, New York, 2002. [64] B.M. Jaćimović, S.B. Genić, N.B. Jaćimović, Reboiler Separation Efficiencies for Binary Systems, Ind. Eng. Chem. Res. 51 (2012) 5793–5804. [65] Y. Shi, W. Li, J. Tu, Vapor-Liquid Equilibria for Binary Systems of Methanol-Isoamyl Acetate, Dimethyl Carbonate-Isoamyl Acetate, and Methanol-1,2-Propanediol at 101.325 kPa, Journal of Chemical Engineering of Chinese Universities (1999) 147–151. [66] H. Luo, J. Zhou, W. Xiao, K. Zhu, Isobaric Vapor−Liquid Equilibria of Binary Mixtures Containing Dimethyl Carbonate under Atmospheric Pressure, J. Chem. Eng. Data 46 (2001) 842–845. [67] T. Mathuni, J.-I. Kim, S.-J. Park, Phase Equilibrium and Physical Properties for the Purification of Propylene Carbonate (PC) and γ-Butyrolactone (GBL), J. Chem. Eng. Data 56 (2011) 89–96.

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Graphical Abstract

Highlights •

Steady-state experiments performed in a pilot-scale reactive distillation column.

•

Effect of decisive operating parameters studied experimentally.

•

Modeling approach selected for the homogeneously catalyzed reaction.

•

Non-equilibrium stage model successfully validated using gathered experimental data.

•

Reboiler efficiency experimentally quantified and theoretically described.