Modeling of Supported Ionic Liquid Catalysts Systems—From Idea to

Aug 29, 2017 - Modeling of Supported Ionic Liquid Catalysts Systems—From Idea to Applications. Pasi Virtanen† , Eero Salminen†, and Jyri-Pekka M...
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Modeling of Supported Ionic Liquid Catalysts SystemsFrom Idea to Applications Pasi Virtanen,*,† Eero Salminen,† and Jyri-Pekka Mikkola†,‡ †

Industrial Chemistry & Reaction Engineering, Johan Gadolin Process Chemistry Centre, Åbo Akademi University, Biskopsgatan 8, FI-20500, Åbo-Turku, Finland ‡ Technical Chemistry, Department of Chemistry, Chemical-Biological Centre, Umeå University, SE-90187, Umeå, Sweden S Supporting Information *

ABSTRACT: The modeling of chemical reactions studied in small scale, often carried out in Academia, is very important since it gives more information about the system and better possibilities to scale-up the processes in the future. Supported ionic liquid catalysts (SILCAs) have been studied in a number of different processes. However, the modeling of these processes have been studied only in a few cases. In this paper the sample cases are reviewed. These processes include hydrogenation of unsaturated aldehydes as well as isomerization of terpenes, α- and β-pinene oxides.

1. INTRODUCTION Ionic liquids have several distinct typical characteristics that can be assigned to many of them. For instance, some of the most common ones are regularly very minor vapor pressure (∼10−8 bar), large temperature window of molten state, unique solvation properties, broad electrochemical window, and decent ion conductivity.1−3 However, one must take into account that these characteristics are not shared with all ionic liquids as has been clearly declared in 2003 by Deetlefs and Seddon.2 Among other applications, ionic liquids have performed well in different kinds of catalytic conversions and in the formulation of nanostructured substances as well as nanoparticles for catalysis.4−7 In fact, catalytic application is definitely one of the fields, in which ionic liquids represent a substantial promise. Hence, supported ionic liquid catalysts containing a small amounts of an ionic liquid or molten salt immobilized on a solid carrier material give rise to interesting industrial alternatives of tomorrow.8−14 An example of the influences of an ionic liquid layer on the catalyst surface was studied by Virtanen et al. and compared against a traditional type catalyst containing Pd on active carbon cloth. It was discovered that the catalysts comprising the ionic liquid layer outperformed the Pd/ACC catalyst in citral hydrogenation.15 Therefore, also the modeling of the reactions is very important.16−18 Some successful examples of modeling ionic liquid systems by molecular dynamic simulations, ab initio simulations or COSMO RS can be found in the literature.19−25 However, here we concentrate specifically on kinetic modeling of reactions over supported ionic liquid catalysts. © XXXX American Chemical Society

Immobilization or sustaining of ionic liquids can be carried out by numerous distinct methods, such as straightforward impregnation, grafting, polymerization, sol−gel method, encapsulation, or pore trapping.8−11,26−28 A technically simple and elegant preparation method is characterized by impregnation of the support material with an ionic liquid which is diluted with a (low boiling) molecular solvent, for example, acetone or alcohols. The impregnation and subsequent vaporization of the molecular solvent lead to an even and slim ionic liquid film deposited on the support matter. However, if SILCA catalysts formulated by simple impregantion are employed in a liquidphase procedure, a bulk solvent that is immiscible with the ionic liquid must be chosen. During the ionic liquid immobilization it is also possible to include other species such as transition metal ions or complexes into the ionic liquid film. Consequently, also organometallic compounds can additionally be reduced to metallic nanoparticles formed via decomposition of the salt. Catalytic valorization of biomass extractives and their derivatives (e.g., citral, cinnamaldehyde, and α- and β-pinenes) to fine chemicals and pharmaceuticals has for several years been of interest to Special Issue: Tapio Salmi Festschrift Received: Revised: Accepted: Published: A

June 1, 2017 August 28, 2017 August 29, 2017 August 29, 2017 DOI: 10.1021/acs.iecr.7b02266 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research Scheme 1. Suggested Citral Hydrogenation Reaction Scheme

Scheme 2. Suggested Cinnamaldehyde Hydrogenation Reaction Scheme

Isomerization of α-pinene oxide, indorsed by Lewis acid, produces campholenic aldehyde that is an important intermediate in the production of fragrances, for example santalol.29 Isomerization of α-pinene oxide which is indorsed by Brønsted acids gives primarily trans-carveol that is similarly applied by the perfume industry (Scheme 3).30−32 Homogenous Lewis acid catalysts, for example ZnBr or ZnCl, promotes formation of campholenic aldehyde in isomerization of α-pinene oxide. Refined chemicals, for example myrtanal, myrtenol, and perillyl alcohol, that also have usage in perfumery as well as medicinal industry can be obtained via isomerization of β-pinene oxide.33 Myrtanal, an antiseptic compound, can be obtained via isomerization of β-pinene oxide and is indorsed by Lewis acidic compounds, whereas Brønsted acids primarily promote the formation of perillyl alcohol and myrtenol (Scheme 4).34−36

chemical engineers. Citral and cinnamaldehyde are α,β-unsaturated aldehydes and building blocks used in the fine chemical industry for production of flavors and fragrances. In general, selective hydrogenation of α,β-unsaturated aldehydes, ketones, and esters, is a common technique to achieve several different kinds of products which can be utilized in the fragrance industry, hardening of fats, synthesis of pharmaceuticals, and preparation of organic chemical intermediates. Selective hydrogenations of α,β-unsaturated aldehydes and ketones are demanding, since the compounds include three dissimilar double bonds: isolated and conjugated carbon− carbon double bonds and a carbonyl group. Therefore, several rivaling and sequential reactions may take place during hydrogenation. Complete reaction sequences for hydrogenation of citral and cinnamaldehyde are displayed in Schemes 1 and 2, respectively. B

DOI: 10.1021/acs.iecr.7b02266 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research Scheme 3. Suggested α-Pinene Oxide Isomerization Reaction Scheme

2. REACTION KINETICS

adsorption. Consequently, just one model that was found to the best one is presented hereit was proper to quantitatively describe the experimental results for each experiment. The adsorption and desorption steps are reviwed in Tables 1 and 2, respectively. The total site balance can be formulated for the fractional coverages (θ) of all compounds similar way in both cases. In case of citral,

15,16

2.1. Hydrogenation of Citral and Cinnamaldehyde. In the case of unsaturated aldehydes, the kinetic modeling was founded on a Langmuir−Hinshelwood−Hougen−Watson theory for hydrogenation, and the reaction schemes are displayed in Schemes 1 and 2, respectively. The only exception was that in the case of citral, the path from citral to nerol or geraniol was disregarded since mole fractions less than 0.01% were found throughout experimental work. As a rational approach, hydrogenation reactions on the catalyst surface were presumed to be ratedetermining steps (RDS), while adsorption and desorption steps were presumed to be fast in comparison to the hydrogenation reactions. Hydrogen adsorption was presumed to be dissociative while adsorption of all organic compounds was presumed as competitive. Also, a model based on noncompetitive adsorption of organic species as well as hydrogen and nondissociative hydrogen adsorption were investigated during the process of the modeling research. Still, the most suitable outcome was achieved with competitive adsorption of all t he compounds with dissociative hydrogen

θC + θCAL + θCOL + θDCAL + θTHG + θ2OCT + θH + θfree = 1

(1)

,wherein θfree represents the amount of vacant surface sites. From Table 1, which presents the adsorption quasi-equilibria, the coverages of absorbed compounds can be formulated with the help of the fraction of vacant sites, Ki =

θi ⇔ θi = K iCiθfree , Ciθfree

(i = C, CAL, DCAL, 2OCT, COL, THG) C

(2)

DOI: 10.1021/acs.iecr.7b02266 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research KH =

θH2 2 pH θfree 2

⇔ θH =

The coverage of vacant sites can be obtained by merging site equations.

KHpH θfree 2

(3)

θfree = 1/(1 + K CCC + K CALCCAL + KDCALC DCAL

Scheme 4. Suggested β-Pinene Oxide Isomerization Reaction Scheme

+ K COLCCOL + K 2OCTC 2OCT + KTHGC THG KHpH )

+

(4)

2

The denominator will be expressed by D = 1 + K CCC + K CALCCAL + KDCALC DCAL + K COLCCOL + K 2OCTC2OCT + KTHGC THG +

KHpH

(5)

2

Site balances can be rewritten: θi =

K iCi , D

(i = C, CAL, DCAL, 2OCT, COL, THG) (6)

, θH =

KHpH

2

(7)

D

The surface reactions were deemed to take place on the surface sites as stated by Tables 1 and 2. Hence, the succeeding rate equations can be derived (Schemes 1 and 2): R i = k rds, jθkθH2 =

k rds, jKkCkKHpH fDA 2

D

3

=

k′rds, j CkKHpH fDA 2

D3

(k′rds, j = k rds, jKk)

(8)

,where i denotes a reaction number (R1a−R7a or R1b−R4b), j denotes a hydrogenation product (CAL, DCAL, 2OCT, COL, THG) or (HCNAL, CNOL, HCNOL), k denotes an adsorbed reactant (C, CAL, DCAL, 2OCT, COL) or (CNAL, HCNAL, Table 1. Adsorption and Desorption of Citral, Hydrogen, and Hydrogenation Products as Well as Hydrogenation Steps aAdsorption/desorption steps:

hydrogenation:

KC

1.

C+∗ ← → C*

2.

H 2 + 2* ← → 2(H*)

3.

CAL* ←⎯⎯→ CAL + ∗

4.

2OCT* ←⎯⎯⎯→ 2OCT + ∗

5.

DCAL* ←⎯⎯⎯⎯→ DCAL + ∗

6.

COL* ←⎯⎯→ COL + ∗

7.

THG* ←⎯⎯→ THG + ∗

k rds,CAL

R1a

C* + 2(H*) ⎯⎯⎯⎯⎯⎯⎯⎯→ CAL* + 2*

R2a

C* + 2(H*) ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯→ 2OCT* + 2*

R3a

CAL* + 2(H*) ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯→ DCAL* + 2*

K2OCT

R4a

CAL* + 2(H*) ⎯⎯⎯⎯⎯⎯⎯⎯→ COL* + 2*

KDCAL

R5a

2OCT* + 2(H*) ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯→ DCAL* + 2*

KCOL

R6a

COL* + 2(H*) ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯→ THG* + 2*

KTHG

R7a

DCAL* + 2(H*) ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯→ THG* + 2*

KH

KCAL

k rds,2OCT

k rds,DCAL, I

k rds,COL

k rds,DCAL,II

k rds,THG, I

k rds,THG,II

Table 2. Adsorption and Desorption of Cinnamaldehyde, Hydrogen, And Hydrogenation Products as Well as Hydrogenation Steps adsorption/desorption steps:

hydrogenation:

KCNAL

1.

CNAL* ←⎯⎯⎯⎯→ CNAL + ∗

2.

H 2 + 2* ← → 2(H*)

3.

HCNAL* ←⎯⎯⎯⎯⎯⎯→ HCNAL + ∗

4.

CNOL* ←⎯⎯⎯⎯→ CNOL + ∗

5.

HCNOL* ←⎯⎯⎯⎯⎯⎯→ HCNOL + ∗

KH

KHCNAL

KCNOL

k rds,HCAL

R1b

CNAL* + 2(H*) ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯→ HCNAL* + 2*

R2b

HCNAL* + 2(H*) ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯→ HCNOL* + 2*

R3b

CNAL* + 2(H*) ⎯⎯⎯⎯⎯⎯⎯⎯→ CNOL* + 2*

R4b

CNOL* + 2(H*) ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯→ HCNOL* + 2*

k rds,HCOL,I

k rds,COL

k rds,HCOL,II

KHCNOL

D

DOI: 10.1021/acs.iecr.7b02266 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Plotting the −ln(1 − X) as a function of time evidently yields straight lines for every hydrogenation experiment (Figure 1), implying first order kinetics for citral consumption. More simplifications could be made, since the mole fractions of citronellol, 3,7-dimethyl-2-octenal, and tetrahydrogeraniol were low and during the course of parameter estimation the values of KCAL as well as KDCAL were found out to be significantly smaller than the value of KH. Consequently, eq 5 can be condensed into eq 21, which was applied in further modeling.

CNOL), f DA denotes an empirical deactivation term defined as follows: fDA = e−kdeacttcumu

(9)

where tcumu denotes the collective time the catalyst has been subjected to the reaction mixture. The rate constants were deemed to depend on temperature according to the Arrhenius equation, ′ i = k 0,rds, ′ i e−Ea,i / RT k rds,

(10)

D=1+

Hence, the generation rates of citral hydrogenation products can be obtained from the rate equations (Scheme 1),

Ri =

(11)

Citronellal generation: rcal = R1a − R3a − R 4a

3,7-Dimethyl-2-octenal generation: (13)

rcol = R3a − R 6a

KHpH )3

(22)

2

rCNAL = −R1b − R3b

(14)

rdcal = R 4a + R 5a − R 7a

rHCNAL = R1b − R 2b

(15)

Tetrahydrogeraniol generation:

(24)

Cinnamylalcohol generation:

rthg = R 6a + R 7a

(16)

rCNOL = R3b − R 4b

A classical batch model running within kinetic regime was utilized for the organic components,

(25)

Hydrocinnamylalcohol generation: rHCNOL = R 2b + R 4b

dni dci = rm = riρB i cat ⇔ dt dt

(17)

,where ρB denotes the catalyst bulk density, ρB =

k rds,2OCTK CCCKHpH fDA ⎞ dcC ⎛ k rds,CALK CCCKHpH2 fDA 2 ⎟⎟ρ = ⎜⎜− − B 3 dt D D3 ⎠ ⎝ (18)

A straightforward way to illustrate the kinetics was to combine the catalyst deactivation and other constant parameters in a single experiment. With constant hydrogen pressure, eq 19 can be derived. ( −k rds,CAL − k rds,2OCT)K CKHpH fDA 2

rCNOL = R3b − R 4b ≈ 0, ⇒

ρB

k″ < 0

= (19)

R3b ≈ R 4b

k rds,CNOLK CNALCCNALKHpH fDA 2

D3 k rds,HCNOL,IIK CNOLCCNOLKHpH fDA 2

D3

from which the concentration of CNOL is obtained

The integration of eq 19 yields, ⎛C ⎞ −ln⎜ C ⎟ = −ln(1 − X ) = k″t ⎝ CC0 ⎠

(26)

The same reactor model that was applied in citral hydrogenation (eq 17), was also applied in the hydrogenation of cinnamaldehyde. During the course of experimental runs, cinnamylalcohol (CNOL) was never observed from the reaction mixture. Still, it is necessary from the modeling point to involve also the reaction route from cinnamaldehyde to cinnamylalcohol and further to hydrocinnamylalcohol in the model. When looking at the kinetics, it is obvious that hydrocinnamaldehyde (HCNAL) and hydrocinnamylalcohol (HCNOL) are mainly generated separately. The quasi-steady state hypothesis was employed to CNOL formation.

mcat . VL

By inserting the equations obtained from eq 8 to eq 11 and further to eq 17, eq 18 for citral consumption rate can be derived.

D3

(23)

Hydrocinnamaldehyde generation:

Dihydrocitronellal generation:

dc → C = k ″C C , dt

2

(1 +

Cinnamaldehyde consumption:

Citronellol generation:

k″ =

k′rds, j CkKHpH fDA

Even the chemical structure of cinnamaldehyde is quite similar to citral, the modeling of the hydrogenation went a bit differently. Generation rates for cinnamaldehyde hydrogenation can be obtained from the rate eqs 8 by applying the reaction stoichiometry (Scheme 2.),

(12)

r2oct = R 2a − R 5a

(21)

2

Hence, the rate equations can be described by eq 22

Citral consumption: rc = −R1a − R 2a

KHpH

⇒CCNOL = (20)

k rds,CNOLK CNALCCNAL k rds,HCNOL,IIK CNOL

(27)

The concentration was introduced in the equations for R4b, eq 8, and in the denominators D of all equations,

,where conversion of citral is represented by X. E

DOI: 10.1021/acs.iecr.7b02266 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Figure 1. Graphs of −ln(1 − X) vs time for consecutive batches over the catalyst Pd/[NB4MPy][BF4]/ACC. Reaction conditions are illustrated in the figure. Adapted from ref 16. Copyright American Chemical Society 2009.

D = 1 + K CNALCCNAL + KHCNALC HCNAL k rds,CNOLK CNALCCNAL + + KHCNOLC HCNOL + k rds,HCNOL,II

KHpH

The influence of hydrogen pressure to the reaction order in citral hydrogenation depends on the ionic liquid immobilized on the catalyst.16 Hydrogen pressure-dependent reaction orders over different catalysts are enlisted in Table 3. In the case of catalysts containing ionic liquids [BMIM][PF6] as well as [A336][PF6] and the classical heterogeneous catalyst, which did not contain any ionic liquid, the rise of hydrogen pressure resulted in an increase in reaction rate. On the contrary, in the case of catalysts containing ionic liquids [NB4MPy][BF4] and [A336][HSO4], the reaction rate seemed not to depend on the hydrogen pressure. In addition, in the case of the catalyst containing [BMIM][BF4], an increase in hydrogen pressure resulted in a lower reaction rate. The detected occurrences can be explained by variations in hydrogen solubility in the ionic liquid layer and the variations in adsorption coefficients for the ionic liquids applied. Equation 22 gives a possibility to possess various reaction orders with respect to hydrogen pressure in this example case. In the case of cinnamaldehyde hydrogenation, the influence of hydrogen pressure was assessed in a similar way.17 There was a clear difference in studied cases when reaction order was compared against the hydrogen pressure. When [BMIM][PF6] was applied as ionic liquid on the catalyst, almost zero order reaction rate was observed, under studied circumstances. It means that the effect of hydrogen pressure to the reaction rate was not signifficant. Nevertheless, [NB4MPy][BF4] was applied as ionic liquid, the reaction order with respect to the hydrogen pressure was around 0.7. Thus, higher hydrogen pressures resulted in higher reaction rates. 2.2. Isomerization of α,β-Pinene Oxides. A,β-Pinene oxides isomerization was studied at the temperatures varying from 25 to 120 °C.18 Varying pressure from 1 to 10 bar had no effect on reaction rates and product selectivities. The catalysts studied for α-pinene oxide isomerization were SnCl2/[N(3OH-Pr)Py][NTf2]/ACC and SnCl2/[NB4MPy][BF4]/ACC. The catalysts studied for β-pinene oxide isomerization, ZnCl2/[N(3-OH-Pr)Py][NTf2]/ACC and ZnCl2/[NB4MPy][BF4]/ACC, were applied as catalysts. Moreover, the molar

2

(28)

A straighforward method to simplify the model is to check if the reaction is of the first order with respect to reactant consumption as was earlier observed in citral hydrogenation.16 By introducing the expressions for R1b and R3b, which were obtained from eq 8, to eq 23, and eq 23 further to eq 28, eq 29 for cinnamaldehyde consumption is obtained. ⎛ k rds,HCNALK CNALCCNALKHpH fDA dCCNAL 2 = ⎜⎜ − dt D3 ⎝ −

k rds,CNOLK CNALCCNALKHpH fDA ⎞ 2 ⎟⎟ρ B D3 ⎠

(29)

Consequently, combining the catalyst deactivation in a single experiment with other constant parameters and with constant hydrogenation pressure, eq 30 could be obtained. ⎡ ( −k rds,HCNAL − k rds,CNOL)K CNALKHp f ⎤ H 2 DA ⎥ρ k″ = ⎢ 3 ⎢⎣ ⎥⎦ B D ⇒

dCCNAL = k″CCNAL dt

(30)

Integration of eq 30 gives ⎛C ⎞ −ln⎜ CNAL ⎟ = −ln(1 − X ) = k″t ⎝ CCNAL0 ⎠

(31)

where conversion of cinnamaldehyde is marked with X. Still, when the −ln(1 − X) is plotted as a function of time t, the graphs are not linear (Figure 2) indicating that the reaction kinetics is not of first order with respect to cinnamaldehyde concentration and, thus, this way to simplify the model was not applicable. F

DOI: 10.1021/acs.iecr.7b02266 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Figure 2. Graphs of −ln(1 − X) vs time for consecutive batches over the catalyst Pd/[BMIM][PF6]/ACC. Reaction conditions are illustrated in the figure. Adapted from ref 17. Copyright American Chemical Society 2009.

Scheme 5. α-Pinene Oxide Isomerization Steps

Table 3. Reaction Orders with Respect to Hydrogen Pressure for Various Pd/IL/ACC Catalysts upon Citral Hydrogenation catalyst

reaction ordera

T (°C)

Pd/[NB4MPy][BF4]/ACC

0 0 0 0 0.5 0.5 1 −0.7

80 100 120 100 80 100 100 100

Pd/[A336][HSO4]/ACC Pd/[A336][PF6]/ACC Pd/[BMIM][PF6]/ACC Pd/[BMIM][BF4]/ACC a

where the reaction numbers (1C−5C) are denoted with i, and j refers to an isomerization product (CA, FA, CAR, IP, PC). The rate constants were deemed to depend on temperature according to the Arrhenius equation,

Respected to hydrogen pressure.

ratio of Lewis acids and ionic liquids was 2:1 for the zinc chloride catalysts and SnCl2/[N(3-OH-Pr)Py][NTf2]/ ACC catalyst. In the case of the catalyst SnCl2/[NB4MPy][BF4]/ACC, the molar ratio of ionic liquid and Lewis acid was 1:1. Kinetic modeling of the reactions were based on the hypothesis that homogeneous reactions occur in the immobilized ionic liquid layer. The reactor model that was utilized for the isomerization reactions was the same conventional batch model as for hydrogenations working inside the intrinsic kinetic regime. Therefore, eq 17 can be applied. 2.2.1. Isomerization of α-Pinene Oxide. The basis of the model was constructed on the reaction scheme shown in Scheme 3. The reaction route from α-pinene oxide to p-cymene was abadoned because a mole fraction less than 2% for p-cymene was noticed throughout the experimental work. Scheme 5 displays reaction steps for isomerization of α-pinene oxide. The adsorption effect on the solid surface was assumed to be weak; hence, straightforward first-order rate equations can be derived: ri = kjCAPO

kj = k 0, je−Ea,j / RT

(33)

The rates for generation or consumption of all compounds can be obtained via reaction stoichiometry: α-PO consumption: rAPO = −r1 − r2 − r3 − r4 − r5 (34)

(32) G

Campholenic aldehyde formation: rCA = r1

(35)

Fencolenic aldehyde formation: rFA = r2

(36)

t-Carveol formation: rCAR = r3

(37)

Isopinocamphone formation: rIP = r4

(38)

Pinocarveol formation: rTP = r5

(39) DOI: 10.1021/acs.iecr.7b02266 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research The consumption rate for α-pinene oxide can be obtained by combining eqs 17, 32, and 34 implying the kinetics with respect to APO is of first order, expecting that when making a graph of −ln(1 − X) vs time, it should be a straight line (X = conversion of APO) which was later verified.18 dcAPO = ( −k CA − kFA − kIP − kPC − k CAR )CAPOρB dt

applied for parameter estimations. A standard PC was applied for all calculations. 3.1. Citral Hydrogenation.16 Different adsorption models, that is, noncompetitive adsorption between hydrogen and organic compounds as well as nondissociative hydrogen adsorption, were also evaluated throughout the parameter estimation. Values from 0 to 3 were also tested as the denominator power in eqs 8 or 22. Still, the best fitting was accomplished with the models shown here. The values of different parameters over every catalyst are presented in the Supporting Information (S1). The experimental concentrations were satisfactorily predicted by the model. The degree of explanation for every catalyst was between 97.01% and 98.40%. An example model fit for Pd/[NB4MPy][BF4]/ACC catalyst is presented in Figure 3.

(40)

2.2.2. Isomerization of β-Pinene Oxide. The basis of the model was constructed on the reaction scheme showed in Scheme 4. The reaction steps are illustrated in Scheme 6 where a side reaction to form other products was noticed too. Scheme 6. β-Pinene Oxide Isomerization Steps

Hence, the rate equations can be derived:

ri = kjC BPO

(41)

where the reaction numbers (1D−4D) are denoted with i, and j refers to an isomerization product (MAL, PER, MOL, OTH). The rate constants were deemed to depend on temperature according to the Arrhenius equation (eq 33). Thus, the rates for generation or consumption of all compounds can be obtained: β-PO consumption: rBPO = −r1 − r2 − r3 − r4

(42)

Myrtanal formation: rMAL = r1

(43)

Perillyl alcohol formation: rPER = r2

(44)

Myrtenol formation rMOL = r3

(45)

Formation of other products rOTH = r4

(46)

Figure 3. Fitting of the model with the experimental data over Pd/[NB4MPy][BF4]/ACC catalyst. The experimental conditions: T = 100 °C, p(H2) = 20 bar. The lines illustrate the calculated model, and the symbols are values from experiments.

Comparing the values achieved for all estimated model parameters cannot be made directly. Still, one prominent point can be noticed for the catalysts containing ionic liquid: the values for hydrogen adsorption coefficients are lower for every catalyst containing an ionic liquid with a [PF6−] anion. This possibly explains the fact that the main product, for the catalyst containing [BMIM][PF6], in experimental conditions, and for the catalyst containing [A336][PF6], provided by low hydrogen pressure, was citronellal. It is possible to verify the main reaction paths from the values illustrated in Supporting Information S1. The main reaction path is from citral to 3,7-dimethyl-2-octenal and further to dihydrocitronellal for catalysts supported with [NB4MPy][BF4] and [BMIM][BF4] ionic liquids and for the catalyst containing only palladium on ACC. A reaction path from citral to citronellal and further to dihydrocitronellal can be concluded as a secondary reaction path. The two reaction paths were practically equal, for the catalysts containing ionic liquids based on Aliquat 336. Conversely, in the case of the catalyst containing [BMIM][PF6] as ionic liquid, the main reaction path is from citral to citronellal and further gradually to dihydrocitronellal. Observations during experimental work support these results, because citronellal was detected as the main product only with the catalyst containing ionic liquid [BMIM][PF6] in every experimental condition. 3.2. Cinnamaldehyde Hydrogenation. Also in the case of cinnamaldehyde hydrogenation,17 the model presented

Consumption rate for β-pinene oxide can be derived dc BPO = ( −kMAL − kPER − kMOL − k OTH)C BPOρB dt

(47)

When making a graph of −ln(1 − X) vs time, straight lines were achieved. Evidently, β-pinene oxide isomerization follows the first order kinetics with respect to the β-pinene oxide.

3. PARAMETER ESTIMATION In all cases, the graphs of mole fraction vs time was plotted for every compound and were the basis for regression analysis. During the analysis all components were equally valuated. The values for every parameter and their approximated errors were calculated. The software applied to calculate parameter estimations was Modest 6.1.37 ODESSA; an inbuilt ODE solver was applied for solving ordinary differential equations. A combined Simplex-Levenberg−Marquardt method was H

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satisfactorily.18 The degree of explanation varied from 98.64% for the catalyst SnCl2/([N(3-OH-Pr)Py][NTf2] to 96.46% for the catalyst SnCl2/([NB4MPy][BF4]. The values of estimated parameters for the two catalysts applied can be found in the Supporting Information (S3). A sample model fit in the case of catalyst SnCl2/([N(3-OH-Pr)Py][NTf2]/ACC is presented in Figure 5. In this case, the molar fractions of isopinocamphone

above predicted the experimental concentrations satisfactorily. The degree of explanation for the two catalysts was between 98.7% and 99.3%. The values of estimated parameters for the two catalysts applied can be found in the Supporting Information (S2). A sample fit in the case of Pd/[BMIM][PF6]/ACC catalyst is shown in Figure 4. The kinetic model proposed, containing the quasi-steady state theory for cinnamylalcohol, explains very well the conversion and selectivity, as can be seen from the figure. Also a simpler model where reaction R2B was neglected (Scheme 2) was evaluated. This model was not able to explain the further decrease of hydrocinnamaldehyde concentration. Moreover, when the influences of reactant and product adsorption are considered, a pseudo-first-order rate model is achieved with respect to the reactants. Moreover, this model could not explain the kinetics satisfactorily. It is actually logical, since the kinetic graphs in Figure 4 suggest a value for reaction order from 0 to 1 with respect to the reactants.

Figure 5. Fitting of the model with the experimental data over catalyst SnCl2/[N(3-OH-Pr)Py][NTf2]/ACC during a single batch at 70 °C. The lines illustrate the calculated model, and the symbols are values from experiments.18

rose from 5% at 25 °C to 26% at 120 °C. Obviously higher temperature favors the generation of bicyclic species (e.g., isopinocamphone), whereas lower temperature gives a higher amount of monocyclic derivatives (e.g., campholenic aldehyde). The calculated activation energy for isopinocamphone was higher than for campholenic aldehyde. Campholenic aldehyde is supposed to be the kinetic product and is therefore favored under kinetic regime, that is, when temperature is low. Thus, isopinocamphone is supposed to be a thermodynamic product that is favored at higher temperature. 3.4. Isomerization of β-Pinene Oxide. The model was able to predict experimental data of β-pinene oxide isomerization18 satisfactorily, giving rise to degrees of explanation of 96.54% in case of ZnCl2/[N(3-OH-Pr)Py][NTf2]/ACC and 97.42% for ZnCl2/[NB4MPy][BF4]/ACC. The values of estimated parameters for the two catalysts applied can be found in the Supporting Information (S4). A sample model fit in the case of catalyst SnCl2/([N(3-OH-Pr)Py][NTf2]/ACC is presented in Figure 6.

Figure 4. Fitting of the model with the experimental data over Pd/[BMIM][PF6]/ACC catalyst during a single batch. Experimental conditions: T = 120 °C, P(H2) = 20 bar. The lines illustrate the calculated model and the symbols are values from experiments.

Comparing the values achieved for all estimated model parameters cannot be made directly. Still, one prominent point can be noticed. The calculated value for the hydrogen adsorption coefficient is a lot lower for the catalyst containing [BMIM][PF6] as ionic liquid, indicating lower hydrogen solubility in this ionic liquid. This result can explain the activity differences of the studied catalysts. It is possible to verify the main reaction paths from the values illustrated in Supporting Information S2. In the case of both catalysts, the main reaction route clearly follows a route from cinnamaldehyde to hydrocinnamaldehyde. With the catalyst containing [NB4MPy][BF4] ionic liquid, hydrocinnamylalcohol is generated both via hydrocinnamaldehyde and cinnamylalcohol, but mostly via cinnamylalcohol. Nevertheless, with the catalyst containing [BMIM][PF6] ionic liquid, hydrocinnamylalcohol is generated via cinnamylalcohol only. Since the values for activation energies were quite similar and KCNAL≈ KHCNAL, the simplification of the model was estimated by setting activation energies and adsorption coefficients as equal. Still, the model with every parameter evaluated separately explained better experimental results. 3.3. Isomerization of α-Pinene Oxide. The model was able to predict experimental data of α-pinene oxide isomerization

Figure 6. Fitting of the model with the experimental data over catalyst ZnCl2/[N(3-OH-Pr)Py][NTf2]/ACC during a single batch at 70 °C. The lines illustrate the calculated model, and the symbols are values from experiments.18 I

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(2) Rogers, R. D.; Seddon, K. R. Ionic Liquids − Solvents of the Future? Science 2003, 302, 792. (3) Seddon, K. R. Ionic Liquids a Taste of the Future. Nat. Mater. 2003, 2, 363. (4) Wilkes, J. S. Properties of Ionic Liquids for Catalysis. J. Mol. Catal. A: Chem. 2004, 214, 11. (5) Dupont, J.; Fonseca, G. S.; Umpierre, A. P.; Fichtner, P. F. P.; Teixeira, S. R. Transition-metal Nanoparticles in Imidazolium Ionic Liquids: Recyclable Catalysts for Biphasic Hydrogenation Reactions. J. Am. Chem. Soc. 2002, 124, 4228. (6) Sheldon, R. Catalytic reactions in Ionic Liquids. Chem. Commun. 2001, 2399. (7) Gordon, C. M. New developments in catalysis Using Ionic Liquids. Appl. Catal., A 2001, 222, 101. (8) Valkenberg, M. H.; deCastro, C.; Hölderich, W. F. Immobilisation of Ionic Liquids on Solid Supports. Green Chem. 2002, 4, 88. (9) Breitenlechner, S.; Fleck, M.; Mueller, T. E.; Suppan, A. Solid Catalysts on the Basis of Supported Ionic Liquids and Their Use in Hydroamination Reactions. J. Mol. Catal. A: Chem. 2004, 214, 175. (10) Kim, D. W.; Chi, D. Y. Polymer Supported Ionic Liquids: Imidazolium Salts as Catalysts for Nucleophilic Substitution Reactions Including Fluorinations. Angew. Chem., Int. Ed. 2004, 43, 483. (11) Riisager, A.; Fehrmann, R.; Flicker, S.; van Hal, R.; Haumann, M.; Wasserscheid, P. Very Stable and Highly Regioselective Supported Ionic-Liquid-Phase (SILP) Catalysis: Continuous-Flow Fixed-Bed Hydroformylation of Propene. Angew. Chem., Int. Ed. 2005, 44, 815. (12) Hagiwara, H.; Sugawara, Y.; Isobe, K.; Hoshi, T.; Suzuki, T. Immobilization of Pd(OAc)2 in Ionic Liquid on Silica: Application to Sustainable Mizoroki-Heck Reaction. Org. Lett. 2004, 6, 2325. (13) Huang, J.; Jiang, T.; Gao, H.; Han, B.; Liu, Z.; Wu, W.; Chang, Y.; Zhao, G. Pd Nanoparticles Immobilized on molecular Sieves by Ionic Liquids: Heterogeneous Catalysts for Solvent-Free Hydrogenation. Angew. Chem., Int. Ed. 2004, 43, 1397. (14) Mehnert, C. P.; Mozeleski, E. J.; Cook, R. A. Supported ionic liquid catalysis investigated for hydrogenation reactions. Chem. Commun. 2002, 3010. (15) Virtanen, P.; Karhu, H.; Kordas, K.; Mikkola, J.-P. Chem. Eng. Sci. 2007, 62, 3660. (16) Virtanen, P.; Mikkola, J.-P.; Salmi, T. Kinetics of Citral Hydrogenation by Supported Ionic Liquid Catalysts (SILCA) for Fine Chemicals. Ind. Eng. Chem. Res. 2007, 46, 9022. (17) Virtanen, P.; Mikkola, J.-P; Salmi, T. Kinetics of Cinnamaldehyde Hydrogenation by Supported Ionic Liquid Catalysts. Ind. Eng. Chem. Res. 2009, 48, 10335. (18) Salminen, E.; Mäki-Arvela, P.; Virtanen, P.; Salmi, T.; Wärnå, J.; Mikkola, J.-P. Kinetics upon isomerization of α,β-pinene oxides over supported ionic liquid catalysts containing Lewis acids. Ind. Eng. Chem. Res. 2014, 53, 20107. (19) Yan, T.; Burnham, C. J.; Del Pópolo, M. G.; Voth, G. A. Molecular Dynamics Simulation of Ionic Liquids: The Effect of Electronic Polarizability. J. Phys. Chem. B 2004, 32, 11877. (20) Wang, Y.; Jiang, W.; Yan, T.; Voth, G. A. Understanding Ionic Liquids through Atomistic and Coarse-Gained Molecular Dynamics Simulations. Acc. Chem. Res. 2007, 40, 1193. (21) Micaêlo, N. M.; Soares, C. M. Protein Structure and Dynamics in Ionic Liquids. Insights from Molecular Dynamics Simulation Studies. J. Phys. Chem. B 2008, 112, 2566. (22) Logotheti, G.-E.; Ramos, J.; Economou, I. G. Molecular Modeling of Imidazolium-Based [Tf2N−] Ionic Liquids: Microscopic Structure. Thermodynamic and Dynamic Properties, and Segmental Dynamics. J. Phys. Chem. B 2009, 113, 7211. (23) Vega, L. F.; Vilaseca, O.; Llovell, F.; Andreu, J. S. Modeling ionic liquids and the solubility of gases in them: Recent advances and perspectives. Fluid Phase Equilib. 2010, 294, 15. (24) Buchele, A.Modeling of the Supported Ionic Liquid Phase Catalysis. Ph.D. Thesis, Erlangen, 2013. (25) Huang, Y.; Zhang, X.; Zhang, X.; Dong, H.; Zhang, S. Thermodynamic Modeling and Assessment of Ionic Liquid-Based CO2 Capture Processes. Ind. Eng. Chem. Res. 2014, 53, 11805.

4. CONCLUSIONS The presented sample cases have shown that it is possible to derive a kinetic model based on surface reactions as ratedetermining steps for the hydrogenation of α,β-unsaturated over supported ionic liquid catalysts (SILCAs). The models were successfully employed in several catalysts containing ionic liquid and Pd nanoparticles on active carbon cloth. The models were able to predict the experimental results including differences in activities and selectivities of various catalysts. Also in the cases of α- and β-pinene oxide isomerization, the kinetic modeling was instrumental in explaining the experimental results. The influence of the ionic liquid layer on the catalyst was revealed. Ionic liquids clearly affected both to reaction rate as well as to selectivity of the products. A plausible reason for this phenomenom is that the choice of ionic liquid has a significant influence on the concentrations of reactants and products on the catalyst surface and ionic liquid might also function as catalyst.38 Furthermore, it was possible to model and explain the temperature effect for α-pinene oxide isomerization. In this case, lowering the temperature favors the generation of campholenic aldehyde (monocyclic compound), while raising the temperature enhances the formation of isopinocamphone, an example of bicyclic compounds. Same kind of behavior was observed in isomerization of β-pinene oxide. Rising the temperature favors the production of myrtanal (bicyclic compound), while with low temperatures myrtanal yield is dampened. As demonstrated herein, it is obvious that a thin layer of ionic liquid layer immobilized on a heterogeneous support can improve the reaction rate and influence the selectivity profile of the reaction of the catalytic material. Hence, the catalyst performance can be enhanced in an economic and elegant way. It is evident that this kind of concept has a potential in different chemical reactions including transformations of other similar compounds.



ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.iecr.7b02266. Tables with values for estimated parameters in all cases (PDF)



AUTHOR INFORMATION

Corresponding Author

*E-mail: pasi.virtanen@abo.fi. ORCID

Pasi Virtanen: 0000-0002-4588-6832 Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS Prof. Tapio Salmi is gratefully recognized for his pioneering efforts in the modelling of supported ionic liquid catalyst (SILCA) systems.



REFERENCES

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DOI: 10.1021/acs.iecr.7b02266 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX