Kinetics of esterification of acetic acid and
methanol using Amberlyst 36 cation-exchange
resin solid catalyst
Mallaiah Mekala* and Venkat Reddy Goli
Department of Chemical Engineering, National Institute of Technology, Warangal, 506004, India *E-mail:mmyadav2001@gmail.com
ABSTRACT
Catalytic esterification of acetic acid with methanol to produce methyl acetate in a stirred batch reactor was investigated in the presence of Amberlyst 16, Indion 180 and Amberlyst 36 catalysts. Amberlyst 36 was found to be an effective solid catalyst for this reaction compared to the other solid catalysts. The reaction was performed in the temperature range of 323.15–353.15 K and the catalyst loading in the range of 0.01–0.05 g cm-3. The initial reactant feed molar ratios of acetic acid to methanol were
varied from 1:1 to 1:4. The influence of different parameters like temperature, catalyst loading, magnetic stirrer speed and average catalyst particle sizes on the conversion kinetics of acetic acid has been investigated. The maximum conversion of acetic acid was increased on increasing the feed molar ratio. From the experimental results, it was observed that the reaction is kinetically controlled rather than controlled by internal and external mass transfer. The experimental data were correlated with the pseudo homogeneous (PH), Eley–Rideal (ER) and Langmuir–Hinshelwood (LH) models. The activity coefficients were calculated using UNIQUAC model to account for the non-ideal behaviour of the components. Of the different kinetic models; the LH, surface rate-determining model, fitted best with the experimental data.
KEYWORDS:
esterification, ion exchange, Amberlyst 36, kinetic modelling1. INTRODUCTION
Esters produced from organic synthesis are used in many industrial applications. The major applications are as plasticisers and cosmetics, and in the medicinal, textile, polymerisation, food and flavour industries. A comprehensive review of synthetic routes to organic esters is available [1]. Among the different esters, methyl acetate is a commercial chemical, produced in bulk quantities.
Methyl acetate is obtained by the esterification reaction of acetic acid and methanol. The reaction scheme is
CH3COOH+CH3OH↔CH3COOCH3+H2O (1)
Progress in Reaction Kinetics and Mechanism, 2015, 40(4), 367–382 doi:10.3184/146867815X14413752286146 Paper: 1400345
The normal esterification reaction is a liquid-phase reversible process, in which the limiting conversion of reactants is determined by the equilibrium. An esterification reaction is very slow without a catalyst and requires several days to attain equilibrium [2]. The addition of catalysts enhances the reaction rate and the system reaches equilibrium very rapidly. The mineral acids like H2SO4, HCl, HBr and HI are used as homogeneous catalysts for the esterification reaction. Heterogeneous catalysts are preferred to homogeneous catalysts due to advantages like the elimination of the corrosive environment, better selectivity towards desired product, high purity of the product due to suppression of side reaction, and easy separation of the catalyst from the post-reaction mixture.
Solid catalysts such as ion exchange resins, zeolites, acid clay catalysts and new solid acids and bases are available. Among them, ion exchange resins are favoured heterogeneous catalysts for esterification reactions [3-5]. These ion exchange resins not only catalyse the reaction, but also improve the equilibrium conversion because of their selective adsorption of reactants and swelling nature [6]. In heterogeneous catalysis, the forces acting on solid surface can distort or even dissociate an adsorbed reactant molecule and hence increase the rate of reaction [7].
Most esterification reactions have been studied by using Amberlyst-type ion exchange resin catalysts [8-12]. A comparison between heterogeneous- and homogeneous-catalysed esterification of acetic acid with methanol using a commercial Nafion/silica nanocomposite catalyst (SAC-13) and H2SO4 was investigated by Liu et al. [13]. The kinetics of the esterification of acetic acid with methanol using Amberlyst 36 was studied by Tsai et al. [14] in a continuous packed bed reactor under different temperatures and molar ratios of the feed. The authors developed kinetic rate equations using different reaction mechanisms by accounting for the non-ideality of a solution using a non-random two-liquid (NRTL) model.
The desired kinetic rate equation is required for the simulation of a reactive distillation process. In the present work, the experiments were conducted to find the best catalyst in relation to acetic acid conversion for further investigation. The effects of various parameters like catalyst type, agitation speed, average size of catalyst particle, reaction temperature, catalyst loading and initial reactant concentration on the esterification reaction were studied for the selected catalyst. For the first time, detailed reaction mechanisms for the esterification of acetic acid and methanol have been studied in presence of Amberlyst 36. Here we report several reaction mechanisms, i.e. the PH model, ER model and LH models to find the best kinetic model for the reaction. Activity coefficients were calculated from the UNIversal QUAsiChemical (UNIQUAC) thermodynamic model. Of the different kinetic models, the best is identified, which is useful for the simulation of the Reactive Distillation Process of our laboratory column.
2.1 Chemicals
Methanol (purity = 99% w w-1) and acetic acid (purity = 99.95 % w w-1), supplied
from SD Fine Chemicals Ltd. (Mumbai, India). These were used as such without any further purification.
2.2 Catalysts
Indion 180 was supplied by Ion-Exchange India Limited, Mumbai and Amberlyst 16 wet and Amberlyst 36 were supplied by Rohm & Hass, Mumbai. The catalysts were dried for 2 hours in an air oven at a temperature of 363.15 K to remove moisture. The physical and chemical properties of the ion-exchange resin catalysts are shown in Table 1.
2.3 Experimental setup
The esterification reactions were carried out in a 500 mL three-necked round-bottom flask which was placed in a heating rota mantle. The rota mantle contained a heating control knob and magnetic stirrer speed control knob. The magnetic stirrer speed was varied from 240 to 640 rpm. A mercury thermometer was dipped into the flask to measure temperature inside the liquid reaction mixture. A vertical spiral condenser was connected to the reaction flask to condense the vapours and return them to the reacting mixture to reduce vapour losses.
2.4 Experimental procedure
The measured quantities of methanol and acetic acid were charged to the reactor. The pure liquid reactants were weighed with an electronic balance with an accuracy
Table 1 Physical and chemical properties of ion-exchange resin catalysts
Physical property Amberlyst 16 wet Indion 180 Amberlyst 36 Manufacturer Rohm &Hass Co. Ion exchange India
Limited Rohm &Hass Co.
Shape Beads Beads Beads
Physical form Opaque beads, brown coloured
Opaque, grey to dark grey coloured
Opaque beads, black coloured
Size (µm) 600-800 725 600–850
Apparent bulk density
(g cm-3) 0.98 0.55 – 0.60 1.0 – 1.3
Surface area (m2 g-1) 30 28–32 33
Pore volume (mL g-1) 0.20 0.32–0.38 0.20
Max. operating
temperature (°C) 130 150 150
Hydrogen ion capacity
(mequiv. g-1) 4.8 5.0 5.4
Matrix type Styrene-DVB Styrene-DVB Styrene-DVB
pHrange – 0–7 5–7
Resin type Macro porous strong acidic cation
Macro porous strong acidic cation
Macro porous strong acidic cation
Functional group –SO3- –SO
3- –SO3
of ± 0.001g. The reaction mixture was heated to the desired reaction temperature. The catalyst was added to the reaction mixture when the reaction mixture had reached the desired temperature. The corresponding time was considered as the initial reaction time after the addition of the catalyst. The samples were withdrawn at specific time intervals and analysed by gas chromatography. Since the withdrawn liquid samples did not contain any catalyst particles, and also because the samples were immediately cooled to room temperature, the reaction was completely stopped. The reaction was carried out for sufficient time to reach equilibrium under different operating conditions.
2.5 Analysis
The samples were analysed by using gas chromatography (GC-2014 ATF, Shimadzu, Japan). The gas chromatograph was equipped with a thermal conductivity detector (TCD) and a Porapak-Q (2 m length and 3.17 mm of id) dual-packed column. High purity hydrogen gas was used as carrier gas. The flow rate of the hydrogen gas in the dual packed column was maintained at 30.0 mL min-1. The oven temperature was
programmed as 323.15 K for 1 min and then raised from an initial value of 323.15 K to 443.15 K at a ramp rate of 10 K min-1 and held for 2 min. The detector temperature
was maintained at 473.15 K. The typical retention times of the components water, methanol, methyl acetate and acetic acid obtained from the analysis were 4.2 min, 7.2 min, 13.1 min and 13.5 min respectively. The chromatogram under optimized conditions is shown in Figure 1.
3. EXPERIMENTAL RESULTS AND DISCUSSION
Catalytic esterification of acetic acid and methanol in the presence of the cation exchange resin catalyst was investigated at mole ratios 1:1 to 1:4. The reaction temperature was varied from 323.15 K to 353.15 K and the catalyst loading was varied from 0.01 g cm-3 to 0.05 g cm-3 based on the initial reaction mixture. The
average size of the catalyst particle was varied from 425 µm to 925 µm and the magnetic stirrer speed was varied from 240 rpm to 640 rpm. The effect of different operating parameters on the reaction kinetics is discussed below.
2.5 5.0 7.5 10.0 12.5 min -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 uV Chromatogram Water/3.925 Methanol/7.012 Methyl acetate/13.12 1 Acetic acid/13.875 (X10, 000)
Figure 1 Characteristic peaks
of a gas chromatogram for acetic acid–methanol–methyl acetate–water under different initial concentration of reaction mixture.
3.1 Catalyst selection
One of the objectives of the present study was to select a suitable catalyst for the esterification of acetic acid with methanol. With this aim, the resin catalysts such as Indion 180, Amberlyst 16 wet and Amberlyst 36 were used. The suitability of each catalyst was studied and the efficacy of the same is represented by acetic acid conversion as a function of time shown in Figure 2. The temperature was maintained at 343.15 K, catalyst concentration was 0.025 g cm-3 of reaction mixture, the initial
mole ratio of the reactants was 1:1 and the agitation speed was 240 rpm for all types of catalyst.
The conversion of acetic acid was calculated from Eqn (2).
0 1 A A A N N X = − (2)
where XA is the conversion of acetic acid at time t, NA is the number of moles of acetic acid at time t and NA0 is the initial moles of acetic acid. From Figure 2, it is observed that Amberlyst 36 accelerates the reaction more as compared to the other solid catalysts, Indion 180 and Amberlyst 16 wet. From Table 1, it is observed that the Amberlyst 36 have a greater H+ ion capacity (mequiv g-1) compared to the other
solid catalysts. Hence the kinetic model was developed for the esterification in the presence of Amberlyst 36.
3.2 Effect of external mass transfer
The experiments were conducted at different agitation speeds of 240 rpm, 480 rpm and 640 rpm to investigate the effect of external mass transfer resistance on the esterification reaction. The experiments were carried out with catalyst concentration: 0.025 g cm-3, reaction temperature: 343.15 K, and average catalyst particle size:
725 µm. Figure 3 shows the conversion of acetic acid with time at different agitation speeds. From Figure 3, it is observed that the conversion of acetic acid is not affected by increasing the stirrer speed beyond 240 rpm. This indicates that the external mass transfer resistance is negligible for the esterification reaction. These results also agree
Figure 2 Conversion of acetic acid
with time for different solid catalysts. Experimental conditions: T=343.15 K, catalyst loading=0.025 g cm-3, average
catalyst particle size=725 µm, acetic acid to methanol mole ratio=1:1
with literature data [2, 3, 14]. Further, all the experiments were carried out with the minimal speed of 240 rpm.
Further, the external mass transfer effect on acetic acid conversion was also studied theoretically by calculating Mears parameter as given in Eqn (3).
Ab c c b obs A M kC n R r C = , ρ (3)
where ρb is bulk density of the catalyst, Rc is the catalyst radius, n is the reaction
order, kcis the mass transfer coefficient and CAb is the bulk concentration of the limiting reactant (acetic acid). The reaction rate of acetic acid was calculated from Eqn (4).
(
)
t W N N r C A A obs A, = 0 −× (4)where rA obsis the observed reaction rate, WC is the amount of catalyst in grams and
t is the reaction time in min.
The mass transfer coefficient, kc wascalculated from the Dwidevi–Upadhyay correlation [15]. ∆ + + = − 2 3 / 2 31 . 0 2 c c Sc p AB c g N d D k ρ ρµ (5)
where DABis the diffusion coefficient of the limiting reactant in the bulk reaction mixture, dp is the average diameter of the catalyst particle, NSc is the dimensionless Schmidt number, ∆ρ is the difference between the densities of the solution and catalyst particle, μc is the viscosity of the reaction solution and ρc is the catalyst density.
The diffusivity of the multi-component mixture is calculated by using the correlation of Perkins and Geankoplis as given below [16].
∑
≠ = = n A j j j Aj j m Am x D D 1 8 . 0 8 . 0 µ µ (6)where DAj is the dilute binary diffusion coefficient of A in j, DAm is the dilute diffusion coefficient of A in the mixture, xj is the mole fraction of j, μj is the viscosity of the component j and μm is the reaction mixture viscosity. The binary diffusion coefficients were calculated from the Wilke–Chang correlation [16] as in Eqn (7),
(
)
8 . 0 5 . 0 18 10 3 . 117 A B B B AB M T D υ µ φ − × = (7)where φB is the association factor of component B, MB is the molecular weight of B,
The calculated Mears parameters at all reaction temperatures are given in Table 2, from which it is observed that at all reaction temperatures, the Mears parameters are below 0.15, which indicates that the external mass transfer could be neglected [17].
3.3 Effect of internal mass transfer
To investigate the effect of internal mass transfer resistance on the reaction kinetics, experiments were conducted in the presence of the same amount (0.025 g cm-3) of
catalyst with different particle sizes of 425 µm, 550 µm, 725 µm and 925 µm. The catalyst particles were separated into different sizes using sieve analysis. For example the average size of the catalyst particle 725 µm was obtained based on average sizes of 850 and 600 mesh sizes. The experimental conditions were reaction temperature: 343.15 K, agitation speed of 240 rpm and feed molar ratio of 1:1. Figure 4 shows that the effect of average catalyst particle size on the conversion of acetic acid with time. From Figure 4, it is observed that the catalyst particle size has no significant effect
Table 2 Criteria for external and internal diffusion at different temperatures
Reaction
temperature robs
Weisz –Prater parameter Mears parameter
Deff (cm2 s-1) CW-P kc(cm s-1) CM
323 5.57778E-05 2.26163E-7 0.602 0.306382 0.001499402
333 6.42222E-05 2.45381E-7 0.727 0.662835 0.000941709
343 6.83333E-05 2.66031E-7 0.755 0.744684 0.000977573
353 7.27000E-05 2.87055E-7 0.793 0.829414 0.001038573
Figure 3 Conversion of acetic acid
with time at different agitation speeds. Experimental conditions: catalyst: Amberlyst 36, T=343.15 K, catalyst loading=0.025 g cm-3, average catalyst
particle size=725 µm, acetic acid to methanol mole ratio=1:1
Figure 4 Conversion of acetic acid with time
at different catalyst average particle sizes (in microns). The experimental conditions: catalyst: Amberlyst 36, T=343.15 K, catalyst loading=0.025 g cm-3, agitation speed=240
on the acetic acid conversion, which confirms that the esterification reaction is not controlled by internal mass transfer [18-22].
Further the effect of internal mass transfer on the reaction kinetics was also investigated by calculating the dimensionless Weisz–Prater parameter.
li e c c Aobs P W rDC R C − =− ρ 2 (8)
where rA is the rate of reaction of A at a given time, ρc is catalyst density, Rc is the
ratio of the catalyst volume to external surface area De is the effective diffusivity and
Cli is the limiting reactant concentration in the reaction mixture. The effective diffusivity is calculated as
lm
e D
D =
ε
2(9)
Dlm is the diffusivity of the limiting reactant and 𝛆 is the void fraction of solid catalyst. The diffusion coefficient of the limiting reactant was calculated from the Perkins–Geankoplis and Wilke–Chang correlations.
Table 2 shows the values of the Weisz–Prater parameter at different temperatures; these are less than one, which indicates that mass transfer inside the catalyst particle can be neglected [17]. These results confirm the literature claim that, for all esterification reactions catalysed by ion exchange resins, internal and external mass transfer resistances were negligible [18-22]. Further, all the experiments were carried out with an average catalyst particle size of 725 µm.
3.4 Effect of reaction temperature
The results obtained at different temperatures on the conversion of acetic acid with time at a fixed amount of catalyst loading of 0.025 g cm-3 are shown in Figures 5a, 6a
and 7a along with model predictions of adsorption-based models. The other operating conditions were: average size of catalyst particle of 725 µm, agitation speed of 240 rpm and molar ratio of 1:1. From Figures 5a, 6a and 7a, it is observed that the acetic acid conversion increases with an increase in temperature. This indicates that the reaction rate is controlled by chemical steps. The dissociation of acetic acid is not found under our experimental conditions so that self-catalytic activity is neglected.
3.5 Effect of catalyst loading
The effect of catalyst loading on the conversion of acetic acid with time was investigated under experimental conditions of average size of catalyst particle: 725 µm, agitation speed: 240 rpm and molar ratio: 1:1. The results obtained with different catalyst concentrations of 0.01 g cm-3 to 0.05 g cm-3 and at a fixed temperature of
343.15 K, along with model predictions of adsorption-based models, are shown in Figures 5b, 6b and 7b. From these it is observed that as the catalyst loading increases, the conversion of acetic acid also increases. When the amount of catalyst in the reaction mixture is increased, the reaction rate increased because of the increase of catalyst-active surface area.
(c)
Figure 6 Comparison of experimental and simulation results: (a) for different temperatures;
(b) for different catalyst loadings; and (c) different acid to alcohol mole ratios using #model 6. Solid line represents the simulation results. Experimental conditions: catalyst: Amberlyst 36, average catalyst particle size=725 mm, agitation speed=240 rpm.
Figure 5 Comparison of experimental and simulation results: (a) for different temperatures;
(b) for different catalyst loadings; and (c) different acid to alcohol mole ratio using #model 2. Solid line represents the simulation results. Experimental conditions: catalyst: Amberlyst 36, average catalyst particle size=725 mm, agitation speed=240 rpm.
(a) (b)
(c)
3.6 Effect of initial reactant mole ratio
Figures 5c, 6c and 7c show that the effect of initial molar ratio on the conversion of acetic acid with time. The initial molar ratios of acetic acid to methanol were varied from 1:1 to 1:4 under the experimental conditions of catalyst concentration: 0.025 g cm-3, temperature: 343.15 K and stirrer speed: 240 rpm. From Figures 5c, 6c and 7c,
it is observed that the conversion of acetic acid increases with increase in the mole ratio, thus the conversion increased from 68.9to 92.9% with increase in the mole ratio of acetic acid to methanol from 1:1 to 1:4.
4. KINETIC MODELLING
The esterification of acetic acid with methanol to form methyl acetate and water was carried out in presence of Amberlyst 36 solid catalyst. The different types of kinetic model used for the esterification reaction are based on the assumption of reaction mechanisms and rate-determining steps. The pseudo-homogeneous model assumes negligible sorption effects of reactants and products on the solid acid catalyst. The ER model is based on the assumption that the reaction takes place between adsorbed and non-adsorbed molecules, whereas the LH model is based on the assumption that the reaction takes place between both adsorbed reactant molecules. The reaction mechanisms and rate-determining steps are given in Table 3.
(a) (b)
(c)
Figure 7 Comparison of experimental and simulation results: (a) for different temperatures;
(b) for different catalyst loadings; and (c) different acid to alcohol mole ratio using the #model 10. Solid line represents the simulation results. Experimental conditions: catalyst: Amberlyst 36, average catalyst particle size=725 mm, agitation speed=240 rpm.
S.No Model Name Rate-determining step Reaction equation 1 PH Surface reaction = − a water ester alcohol acid f cat i M k a a a Ka r 2 ER_Acid_Surf Surface reaction
( acid acid water water)
a water ester alcohol acid acid f cat i K a K a K a a a a K k M r + + − = 1
3 ER_Acid_Ads_Acid Acid adsorption
+ + − = water water alcohol water ester a acid alcohol a water ester acid acid cat i a K a a a K K a K a a a k M r 1
4 ER_Acid_Des_Ester Ester desorption
( ) + + − = water acid alcohol ester a acid acid a ester water alcohol acid a ester cat i a a a K K a K K a a a a K k M r 1
5 ER_Acid_Des_Water Water desorption
( ) + + − = ester acid alcohol water a acid acid a water ester alcohol acid a water cat i a a a K K a K K a aa a K k M r 1
6 ER_Alc_Surf Surface reaction
( alcohol alcohol water water)
a water ester alcohol acid alcohol f cat i K a K aK a a a a K k M r + + − = 1
7 ER_Alc_Ads_Acid Alcohol adsorption
+ + − = water water acid water ester a alcohol acid a water ester alcohol alcohol cat i a K aa a K K a K a a a k M r 1
8 ER_Alc_Des_Ester Ester desorption
( ) + + − = water acid alcohol ester a alcohol alcohol a ester water alcohol acid a ester cat i a a a K K a K K a a a a K k M r 1
9 ER_Alc_Des_Water Water desorption
( ) + + − = ester acid alcohol water a alcohol alcohol a water ester alcohol acid a water cat i a a a K K a K K a aa a K k M r 1
10 LH_Surf Surface reaction
(1 )2 water water ester ester alcohol alcohol acid acid a water ester alcohol acid alcohol acid f cat i K a K a K a K a K a a a a K K k M r + + + + − =
11 LH_Ads_Acid Acid adsorption
+ + + + − = water water ester ester alcohol alcohol alcohol a water ester acid alcohol a water ester acid acid cat i a K a K a K a K a a K a K a a a k M r 1
12 LH_Ads_Alc Alcohol adsorption
+ + + + − = water water ester ester acid acid acid a water ester alcohol acid a water ester alcohol alcohol cat i a K a K a K a K a a K a K a a a k M r 1
13 LH_Des_Ester Ester desorption
+ + + + − = water water water acid alcohol ester a alcohol alcohol acid acid a ester water acid alcohol a ester cat i a K a a a K K a K a K K a a a a K k M r 1
14 LH_Des_Water Water desorption
+ + + + − = ester acid alcohol water a ester ester alcohol alcohol acid acid a water ester acid alcohol a water cat i aa a K K a K a K a K K a aa a K k M r 1
4.1 Activity coefficient
Activities are used to account for the non-ideality of the liquid solution. Activity is defined as
i i
i x
a = γ (10)
The activity coefficient of component i is calculated using the UNIQUAC model [23] as given below, ( )
∑
∑
+ −∑ ∑
− − + + = j k k kj ij j i i j j ji i j j j i i i i i i i i i x z q l x xl q q q θτ τ θ τ θ φ φ θ φ γ ln ln 2 ln ln (11)(
)
(
1)
2 − − − = i i i i z r q r l (12)∑
= j j j i i i qqxx θ (13)∑
= j j j i i i r x x r φ (14) + + − = cT T b aij ij ij ij exp τ (15)where z is the lattice coordination number, ri and qi are relative van der Waals surface and volume of component i. The constants aij, bij, cij are binary interaction parameters, T is temperature and R is the gas constant. The UNIQUAC relative van der Waals volume (ri), surface values (qi) and temperature-dependent interaction parameters are taken from the literature [24].
4.2 Chemical equilibrium
The equilibrium constant is calculated at all reaction temperatures of 323.15 K, 333.15 K, 343.15 K and 353.15 K and at a catalyst loading of 0.025 g cm-3. All
experiments were conducted at different temperatures and catalyst loadings until the system reached chemical equilibrium. The chemical equilibrium constant was calculated from the equilibrium conversions obtained at all reaction temperatures using Eqn (16). water ester alcohol acid alcohol acid water ester alcohol acid water ester water ester alcohol acid alcohol acid water ester water ester alcohol acid S a K K K K x x x x K K K K a a a a K K K K K K = × = × = × × γ γ γ γ (16) where Ka is the overall equilibrium constant of the reaction, KS is the surface reaction equilibrium constant, Kacid, Kalcohol, Kester and Kwater are adsorption constants, a is activity, x is the mole fraction of the component at equilibrium and γ is the activity coefficient of the component at equilibrium.
The van’t Hoff equation gives the relation between equilibrium constant and temperature to calculate the heat of a reaction as given in Eqn (18).
− ∆ − =ln ( 0) 1 10 ) ( ln T T R H T K T K R S S (17) ∆ + ∆− = R S RT H K R R S ln (18)
Where ΔHR is the heat of reaction (kJ mol-1); ΔS
R is the entropy of reaction
(J K-1 mol-1).
Figure 8 shows the relationship between ln (equilibrium constant) versus reciprocal temperature, from which the heat of reaction is calculated to be 4.328 kJ mol-1, which
indicates a slightly exothermic reaction.
4.3 Estimation of parameters
The steps used to determine the adsorption and kinetic parameters for the various kinetic models are given below
1. The experimental data were used at different temperatures and at 0.025 g cm-3
catalyst loading to obtain the kinetic and adsorption constants. The same constants were used at different catalyst loadings at a fixed reaction temperature. 2. The squared differences between the experimental acetic acid conversions and acetic acid conversions from the model predictions were found from Eqn. (19).
(
)
∑
− = ns s cal aceticacid aceticacid abs n X X F 2 exp (19)3. The mean relative error of acetic acid conversion from experiment and acetic acid conversion from the model predictions was found from Eqn (20).
∑
− = ns s cal aceticacid aceticacid rel n X X F | exp | (20)Figure 8 Temperature dependence
of equilibrium constant using Eqn (18). Experimental conditions: catalyst: Amberlyst 36, catalyst loading=0.025 g cm-3, agitation
speed=240 rpm, average catalyst particle size=725 µm, acetic acid to methanol mole ratio=1:1
The temperature dependent of the kinetic parameters were calculated by using the Arrhenius equation as given below.
− = RT E k k f f f exp (21)
where kf0 is forward pre-exponential factors, and Efis the forward activation energies. The kinetic model equations as shown in Table 3 were solved using the ODE-45 Mat-lab tool. The predicted values from the model were compared with experimental data at all experimental conditions. The kinetic parameters obtained from the different kinetic models are given in Table 4.
First, the pseudo-homogeneous model was fitted with the experimental data. The mean relative error was calculated at all the experimental conditions to find better kinetic parameters (frequency factor, kf0 and activation energy, Ef). These two parameters were used as the initial estimate to the ER model to decrease the complexity of the parameters estimation. The ER model was fitted with the experimental data by adjusting the adsorption constants to get the minimal error. Similarly, by using the information about the frequency factor, activation energy and adsorption constants from the PH and ER models as initial estimates, the LH model was fitted to the experimental data to get the least error.
From Table 4, the activation energies were found to lie in the range of 32.124 kJ mol-1
to 48.84 kJ mol-1. The reaction rate increases significantly with temperature as well
as catalyst loading. This indicates that the overall reaction is controlled by a surface reaction. From the experimental findings it is also observed that effect of stirrer speed and size of catalyst particle on the acetic acid conversion was negligible. The adsorption equilibrium constants follow the order of Kwater> Kmetahnol> Kacetic acid>
Kmethyl acetate which agrees with literature values for all the kinetic models [2, 14, 19]. From Table 4, it is observed that the LH model fits well to the experimental data with
Table 4 Estimated parameter data from the different kinetic models
S.No Model number k0f
(mol g-1 min-1)
Ef
(kJ mol-1) Kacid Kmethanol Kmeac Kwater
Mean relative error (Frel) Mean squared difference (Fabs) 1 PH 5619 36±0.3 – – – – 2.14% 2.1 × 10–4 2 ER_Acid_Surf 19400 34.9±0.4 0.232 – – 0.212 2.74% 3.2 × 10–4 3 ER_Acid_Ads_Acid 11400 41.1±0.6 0.182 – – 0.211 4.41% 8.31 × 10–4 4 ER_Acid_Des_Ester 1140 41.1±0.4 0.183 – – 0.199 3.31% 5.1 × 10–4 5 ER_Acid_Des_Water 9190 48.3±0.6 0.12 – – 0.10 4.36% 6.9 × 10–4 6 ER_Alc_Surf 10191 33.8±0.4 – 0.30 – 0.28 2.46% 2.4 × 10–4 7 ER_Alc_Ads_Acid 12990 41.1±0.6 – 0.190 – 0.215 4.83% 1.1 × 10–4 8 ER_Alc_Des_Ester 4987 48.8±0.4 – 0.150 0.135 – 3.69% 6.0 × 10–4 9 ER_Alc_Des_Water 10988 47.2±0.3 – 0.189 – 0.20 3.58% 6.2 × 10–4 10 LH_Surf 70990 32.1±0.2 0.150 0.221 0.130 0.278 1.82% 1.9 × 10–4 11 LH_Ads_Acid 998 33.5±0.6 0.149 0.229 0.125 0.287 3.65% 6.2 × 10–4 12 LH_Ads_Alc 989 33.9±0.6 0.150 0.221 0.113 0.298 4.493% 9.7 × 10–4 13 LH_Des_Ester 590 39.2±0.4 0.147 0.239 0.12 0.29 3.29% 5.0 × 10–4 14 LH_Des_Water 602 39.1±0.4 0.15 0.23 0.115 0.17 2.36% 2.2 × 10–4
a minimum error. Moreover the LH model can be incorporated into commercial simulators to describe the kinetics of the esterification reaction, for example; in the reactive distillation processes.
4.4 Simulation results
The comparison of experimental and simulation results for the conversion of acetic acid is shown in Figures 5–7 for the models #2 (ER_Acid_Surf), #6 (ER_Alc_Surf) and #10 (LH_Surf) respectively. Each figure is composed of three diagrams which contain different operating conditions of temperature, catalyst loading and molar ratio of acetic acid to methanol. Diagram (a) represents the temperature variation (b) represents the variation in catalyst loading and (c) represents variation in the acetic acid to methanol mole ratio. As discussed in the experimental results section, when the temperature increases, the conversion of acetic acid increases due to the more energetic collisions of reactants to form products. Similarly, when the catalyst loading increases, the conversion of acid increases due to the availabity of more catalyst active. From Figures 5–7, it is observed that the simulation results and experimental data are in good agreement for models #2 (ER_Acid_Surf), #6 (ER_Alc_Surf) and #10 (LH_Surf). But of these models, model #10 (LH_Surf) gives better model predictions to experimental data with little error.
The parity plot for experimental results versus model prediction results for the best kinetic model #10 (LH_Surf) is given in Figure 9 from which it is observed that model #10 (LH_Surf) results are in good agreement with the experimental data with minimal error (1.82%).
5. CONCLUSIONS
The catalytic esterification of acetic acid with methanol was investigated in the presence of three different types of catalyst, i.e. Amberlyst 16 wet, Indion180 and Amberlyst 36. From the initial investigations, Amberlyst 36 was found to be the best catalyst. The absence of internal and external mass transfer resistance was verified
Figure 9 Parity plot for experimental
data versus best model (#model 10) prediction.
with experimental investigations as well as the theoretical criteria of Mears and Weisz-Prater parameters. The conversion of acetic acid increases with temperature, which is kinetically controlled. Reaction rate equations were proposed based on different reaction mechanisms. Of the different kinetic models employed, the best was found to be the LH_Surf model (# model 10). The heat of reaction for the esterification in the presence of Amberlyst 36 is –4.328 kJ mol-1, which is slightly exothermic.
6. REFERENCES
[1] Yadav, G.D. and Mehta, P.H. (1994) Ind. Eng. Chem. Res., 33, 2198. [2] Popken, T., Gotze, L. and Gmehling, J. (2000) Ind. Eng. Chem. Res., 39, 2601. [3] Chakrabarti, A and Sharma, M.M. (1993) React. Funct. Polym., 20, 1. [4] Yadav, G.D. and Thathagar, M.B. (2002) React. Funct. Polym., 52, 99. [5] Zhang, Y., Ma, L. and Yang, J. (2004) React Funct Polym., 61, 101. [6] Altiokka, M.R. and Citak, A. (2003) Appl. Catal. A: Gen., 239, 141. [7] Yadav, G.D. and Kulkarni, H.B. (2000) React. Funct. Polym., 44, 153.
[8] Song, W., Venimadhavan, G., Manning, J.M. et al. (1998) Ind. Eng. Chem. Res., 37, 1917. [9] Chan, K.W., Tsai, Y.T., Lin, H.M. and Lee, M.J. (2011) J. Taiwan. Inst.Chem. Engrs., 42, 271. [10] Yu, W., Hidajat, K. and Ray, A.K. (2004)Appl. Catal. A: Gen., 260, 191.
[11] Kirbasla, S.I., Terzioglu, H.Z. and Dramur, U. (2001) Chin. J. Chem. Eng., 9, 90. [12] Alime, I., Esra, U. and Ertugrul, I. (2009)Chem. Eng. Comm., 196, 56. [13] Liu, Y., Lotero, E. and Goodwin Jr, J.G. (2006).J. Catal., 242, 278. [14] Tsai, Y.T., Lin, H.M. and Lee, M.J. (2011) Chem. Eng. J., 171,1367.
[15] Geankoplis, C.J. (1993). Transport processes and unit operations. Prentice Hall, New Jersey. [16] Perry, R.H. and Green, D.W. (1997). Perry’s chemical engineer’s hand book. McGraw-Hill, New
York.
[17] Fogler, H.S. (1999) Elements of chemical reaction engineering. Prentice Hall, New Jersey. [18] Mao, W., Wang, X., Wang, H. et al. (2008) Chem. Eng Proc., 47, 761.
[19] Delgado, P., San, M.T. and Beltran, S. (2007) Chem. Eng. J., 126, 111. [20] Titus, M.P., Bausach, M., Tejero, J. et al. (2007) Appl. Catal. A: Gen., 323, 38.
[21] Ali, S.H., Tarakmah, A., Merchant, S.Q. and Al-Sahhaf, T. (2007) Chem. Eng. Sci.,62,3197. [22] Cruz, V.J., Izquierdo, J.F., Cunill, F. et al. (2007) React. Funct. Polym., 67, 210.
[23] Abrams, D.S. and Prausnitz, J.M. (1975). AICHE J., 21,116.
[24] Gemhiling, J. and Onken U (1977). Vapor liquid equilibrium data collection, In DECHEMA