Mechanism of regioselective ring-opening reactions of 1, 2

Oct 9, 2018 - ... Raghuraman , Kurt F. Hirsekorn , Justin M Notestein , SonBinh T. Nguyen , and Linda J. Broadbelt ... Kautzky, Wang, Evans, and MacMi...
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Mechanism of regioselective ring-opening reactions of 1,2epoxyoctane catalyzed by tris(pentafluorophenyl)borane: a combined experimental, DFT, and microkinetic study Ying Yu, Youlong Zhu, Mihir N Bhagat, Arjun Raghuraman, Kurt F. Hirsekorn, Justin M Notestein, SonBinh T. Nguyen, and Linda J. Broadbelt ACS Catal., Just Accepted Manuscript • DOI: 10.1021/acscatal.8b02632 • Publication Date (Web): 09 Oct 2018 Downloaded from http://pubs.acs.org on October 9, 2018

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Mechanism of regioselective ring-opening reactions of 1,2epoxyoctane catalyzed by tris(pentafluorophenyl)borane: a combined experimental, DFT, and microkinetic study Ying Yu, a Youlong Zhu, b Mihir N. Bhagat, a Arjun Raghuramanc, Kurt F. Hirsekornc, Justin M. Notestein, a,* SonBinh T. Nguyen, b,* Linda J. Broadbelt a,* aDepartment

of Chemical and Biological Engineering, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA. bDepartment of Chemistry, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA. cThe Dow Chemical Company, Lake Jackson, TX 77566, USA.

ABSTRACT: A non-conventional, water-mediated catalytic mechanism was proposed to explain the effects of residual water on the reactivity and regioselectivity of tris(pentafluorophenyl)borane catalyst in the ringopening reaction of 1,2-epoxyoctane by 2-propanol. This non-conventional mechanism was proposed to operate in parallel with conventional Lewis acid-catalyzed ring-opening. Microkinetic modeling was conducted to validate the proposed reaction mechanism, with all kinetic and thermodynamic parameters derived from density functional theory (DFT) calculations. Experimental data at a variety of temperatures and water contents were captured by the model after adjustments within reasonable limits set by experimental benchmarking and accuracy of theory of a small subset of parameters. In addition, the microkinetic model was able to generate accurate predictions at reaction conditions that were not used for parameter estimation. Detailed analysis of the net reaction rates showed that >95% of the reaction flux passed through conventional Lewis-acid pathways at water levels 400 ppm), while the ring-opening rate under low water levels (≤400 ppm) is overestimated. Possible

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reasons include lower accuracy in the experimental determination of low water contents, and fewer runs with low water levels used in model training. The overall regioselectivity and selectivity to first-generation products from microkinetic modeling are also in excellent agreement with experimental measurements for both model fits and model predictions, as shown in Figure 7 a-d. It is interesting to note that the experimental regioselectivity increased slightly with epoxide conversion in all trials, and the model output captured the same trend. This observation led to a hypothesis that the ring-opened products, P1 and P2, if added in the beginning of reaction, might change the overall regioselectivity. Accordingly, runs 18-21 were designed and conducted with a small amount of P1 or P2 added at time zero. Model predictions of kinetics, regioselectivity, and selectivity to first generation products aligned well with experimental results, as shown in Figure 6c and Figure 7 e,f. Indeed, the overall regioselectivity was influenced by initial addition of P1 or P2. Adding P1 slightly decreased the overall regioselectivity, while adding P2 substantially increased the overall regioselectivity. Interestingly, this catalyst shows aspects of self-regulation, where a buildup of P1 decreases subsequent selectivity to that product. In summary, these results validate the proposed catalytic mechanism and illustrate the strong descriptive and predictive power of microkinetic modeling for various reaction conditions. This validated model allows us to predict experimental reaction profiles under other reaction conditions and conduct more detailed investigations into this mechanism.

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Table 3. Chemical context, original values, adjustable ranges, and optimized values of the nine adjustable parameters for the base case model. All energies are in kcal/mol. Entry #

Adjustable Parameter

Original Value

Adjustable Ranges

Optimized Value

1

ΔHrxn of FAB + H2O → FAB∙OH2

-11.6

±8.0

-12.4

2

Simultaneous adjustment to each ΔHrxn of [FAB∙OH2](HBA) + H2O → [FAB∙OH2](H2O)(HBA) where HBA= 2-propanol, EPX, P1, P2, or None

0.0

±8.0

-8.0

3

ΔHrxn of [FAB∙OH2](H2O) + H2O → [FAB∙OH2](H2O)(H2O)

-7.1

±6.0

-10.2

4

Simultaneous adjustment to Ea of Lewis acid catalysis: FAB∙EPX + 2-propanol → P1 + FAB and FAB∙EPX + 2-propanol → P2 + FAB

0.0

±5.0

3.1

5

Simultaneous adjustment to Ea of water-mediated or 2-propanol-mediated ring-opening reactions

0.0

±5.0

2.7

6

Adjustment to Lewis acid pathway regioselectivity by tuning Ea of FAB∙EPX + 2-propanol → P1 + FAB

0.0

±2.0

1.5

0.0

±2.0

-1.5

1.0

0.25-4.0

1.7

7

8

Adjustment to regioselectivity by simultaneously tuning Ea of water-mediated or 2-propanol-mediated ring-opening reactions that produce P1 Adjustment to the rate constant of FAB∙EPX + P1 → PP1* + FAB relative to that of FAB∙EPX + 2-propanol → P1/P2 + FAB

Adjustment to the rate constant of 1.0 0.25-4.0 2.4 FAB∙EPX + P2 → PP2* + FAB relative to that of FAB∙EPX + 2-propanol → P1/P2 + FAB *In this study, the regioisomers of PP1 and PP2 were not distinguished from each other. EPX denotes epoxide. 9

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(a) 2 1.8

Fitted Model Output (M)

1.6 1.4 1.2 1 0.8 0.6 0.4 Epoxide P1 P2

0.2 0 0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Experimental Measurements (M)

(b) 2 Run 8: 400 ppm, 40°C

1.8

Run 9: 990 ppm, 60°C

1.6

Model Predictions (M)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Run 10: 1180 ppm, 50°C

1.4

Run 11: 25 ppm, 0°C

1.2

Run 12: 290ppm, 40°C

1

Run 13: 710 ppm, 60°C Run 14: 970 ppm, 60°C

0.8

Run 15: 1210 ppm, 50°C

0.6

Run 16: 1930 ppm, 60°C

0.4

Run 17: 890 ppm, 60°C P1

0.2

P2

0 0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Experimental Measurements (M)

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(c

2

1.8 1.6

Model Predictions (M)

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1.4

Run 18: 1290 ppm, 60°C, +P1

1.2

Run 19: 1010 ppm, 60°C, +P2

1

Run 20: 880 ppm, 60°C, +P2 Run 21: 1170 ppm, 60°C, +P1

0.8

P1

0.6

P2

0.4 0.2 0 0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Experimental Measurements (M)

Figure 6. Parity plots for experimental kinetic data versus model output that are (a) fitted against runs 17, (b) predicted base case runs 8-17, and (c) predicted with P1 or P2 addition (see Table 1). Note: among the 10 predicted runs in Figure 6(b), epoxide concentrations are shown in filled circles for accurate predictions, and in empty circles for outliers (see legends). Data points of P1 and P2 concentrations only include runs that were accurately predicted.

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110.0

85.0

100.0 90.0

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(f) Run 20, predicted, +P2 90.0

Regioselectivity (%)

100.0

First-generation selectivity (%)

110.0

80.0

40%

Epoxide Conversion

(e) Run 18, predicted, +P1 85.0

50.0 100%

110.0

Epoxide Conversion

90.0

80%

(d) Run 9, predicted Regioselectivity (%)

Regioselectivity (%)

(c) Run 6, fitted

80.0

60%

Epoxide Conversion First-generation selectivity (%)

Epoxide Conversion

40%

First-generation selectivity (%)

75.0

110.0

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60.0

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55.0 50.0

First-generation selectivity (%)

80.0

90.0

First-generation selectivity (%)

90.0

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(b) Run 4, fitted Regioselectivity (%)

Regioselectivity (%)

(a) Run 1, fitted

Regioselectivity (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

First-generation selectivity (%)

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50.0

0%

20%

Epoxide Conversion

40% 60% 80% Epoxide Conversion

100%

Figure 7. Examples of experimental regioselectivity and mass balance data versus model output that are fitted or predicted (see Table 1). Lines represent model output, and points represent experimental data.

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3.2.2. Flux Analysis and the Effects of Water on Regioselectivity Given the ability of the microkinetic model to both fit and predict the experimental data well, the model was further analyzed to rationalize the effects of water and temperature on the overall regioselectivity. Before going into the detailed analysis of water effects, we first confirmed that the water level was the main factor that influenced regioselectivity, rather than temperature. Model simulation was carried out for a series of reaction conditions that covered a wide range of water levels (10 ppm to 5000 ppm) and temperatures (30°C to 60°C) while all other conditions were fixed. We note that the water levels explored involve extrapolation of the model beyond the conditions explored experimentally, thereby exploiting the predictive nature of microkinetic models, even at conditions that may be too slow to be practical. Figure 8 shows the predicted overall regioselectivity at 40% epoxide conversion, where results of different temperatures are color-coded. For the full mechanism, at a fixed temperature, the overall trend of regioselectivity is to decrease from a high of 78% to 61-64% as water level is increased from 0 to 5000 ppm. At a fixed water level, however, the differences in regioselectivity among various temperatures are much smaller. At water levels below 500 ppm, changing the temperature has a negligible impact on regioselectivity, while at higher water levels, decreasing temperature decreases the regioselectivity by < 3%. It can be concluded that the influence of temperature on regioselectivity is much weaker than that of the water level, and that the water effect on regioselectivity is mainly manifested through water-mediated catalytic pathways. Therefore, the focus of analyzing the dependency of regioselectivity on reaction conditions was on water level.

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ACS Catalysis 90 30°C

85 Regioselectivity (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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40°C

80

50°C

75

60°C

70 65 60 55 50 0

1000

2000

3000

4000

5000

Water level (ppm)

Figure 8. Model predictions of the overall regioselectivity at 40% epoxide conversion for initial conditions of water levels from 10-5000 ppm and temperatures from 30°C to 60°C. Other initial conditions were fixed at: [epoxide]0=1.6 M, [2-propanol]0=6.4 M, [FAB]0=1.6 mM.

To unravel the dependence of regioselectivity on water level, it is necessary to understand the partitioning of reaction flux through all catalytic pathways in the complex mechanism and their individual contributions to the overall regioselectivity. Net rate analysis was conducted to quantify the accumulated reaction flux of each catalytic pathway. Model simulation was carried out for a series of typical reaction conditions that covered water levels from 10 ppm to 5000 ppm with other initial conditions fixed. The partitioning of accumulated reaction flux is reported in Figure 9 in terms of three reaction classes: Lewis acid catalytic pathways (Table 2, entry 1), water-mediated catalytic pathways (Table 2, entries 2-8), and alcohol-mediated catalytic pathways (Table 2, entry 9). Pathway partitioning within the water-mediated reaction family and the overall regioselectivity at 40% epoxide conversion are also included in the same figure. The partitioning results show that for all water levels considered, Lewis acid and water-mediated catalytic pathways are kinetically relevant, while alcohol-mediated pathways are negligible. For water levels ranging from 10-500 ppm, the Lewis acid catalytic pathways are the kinetically dominant pathways which contribute more than 95% of the accumulated reaction flux to ring-opened products. Consequently,

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the overall regioselectivity is largely dependent on the regioselectivity specific to the Lewis acid catalytic pathways. Water-mediated catalytic pathways gained more importance with water levels higher than 1000 ppm. In fact, at a water level of 5000 ppm, more than 78% of the accumulated reaction flux went through water-mediated catalysis. As water level increases, the kinetically dominant pathway among watermediated catalytic pathways changes from the one where HBA is P2 to that where HBA is H2O. To facilitate comparison of the contribution of each pathway to the overall regioselectivity, pathway-specific regioselectivity is plotted in Figure 10, with that of Lewis acid catalytic pathways set as a reference line. Combining the results in Figures 9 and 10, the effect of increasing water level on lowering the overall regioselectivity can be explained by the increasing accumulated reaction flux through the water-mediated catalytic pathways with water being HBA that has lower regioselectivity than Lewis acid catalytic pathways. Another observation, the slightly increasing regioselectivity with conversion, can also be explained by more contribution from the water-mediated catalytic pathways with P2 being the HBA that has much higher

100.00%

90.0

90.00%

85.0

80.00%

80.0

70.00% 60.00%

75.0

50.00%

70.0

40.00%

65.0

30.00%

Overall regioselectivity

regioselectivity than Lewis acid catalytic pathways.

Pathway partitioning

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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60.0

20.00%

55.0

10.00% 0.00%

50.0 50

100

200

500

1000

2000

5000

Water level (ppm) Lewis acid pathways

HBA=Other

HBA=Water

HBA=P1

HBA=P2

Regioselectivity

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Figure 9. Model-predicted percentage of reaction flux through all catalytic pathways and the overall regioselectivity at 40% epoxide conversion. Colored bars with legend “HBA=Other/Water/P1/P2” belong to the water-mediated catalytic reaction family. Only pathways that contribute more than 1% flux are shown individually, the rest are grouped into HBA=Other. Black line represents the overall regioselectivity. Initial conditions of the simulations covered water levels from 10-5000 ppm at 25°C. Other initial concentrations were fixed at: [epoxide]0=1.6 M, [2-propanol]0=6.4 M, [FAB]0=1.6 mM.

Regioselectivity of specific HBA pathway (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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100 90

Lewis acid catalytic pathway

80 70 60 50 40 30 Water

P1

P2

HBA

Figure 10. Pathway-specific regioselectivity of Lewis acid and water-mediated catalytic pathways.

3.2.3. Speciation Analysis and the Effect of Water on Reactivity In addition to elucidating the effects of water on the reaction flux distribution and on regioselectivity, the dramatic retardation effect of water on catalyst reactivity was investigated using the validated microkinetic model. To make sure that the comparison of ring-opening rates was made based on only the difference in the water concentration, a series of simulations was conducted under the same reaction conditions except for different water levels ranging from 10 to 5000 ppm. The concentration of FAB adduct species at 40% epoxide conversion and the reaction time needed to reach 40% epoxide conversion were examined and are reported in Figure 11. The percentage of [FAB∙EPX] species (orange area), which leads to the kinetically dominant Lewis acid catalytic pathways, decreases with higher water level, as expected. The abundance of active species with epoxide anchored on the “second shell” (green area) first increases with water level and

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then remains almost the same. Catalytically inactive species (purple area) gain more weight as water level increases. At low water levels (< 100 ppm), [FAB∙2-propanol] adduct (purple area in Figure 12) is the dominant species among all inactive species, while [FAB∙OH2](H2O)(2-propanol) adduct (green area in Figure 12) takes over at medium water levels (100-1000 ppm). The percentage of [FAB∙OH2](H2O)2 species (orange area in Figure 12) was found to increase dramatically with higher water levels to as much as 76% at 5000 ppm water. The contrast in the availability of species together with the trend in catalyst reactivity suggests a mechanism that ties up the catalyst in an inactive state in which water and/or 2-propanol molecules form a highly stable hydrogen-bond network with FAB catalyst and prevent epoxide molecules from binding to FAB and undergoing ring-opening catalysis.

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Figure 11. Model predictions of catalyst reactivity in terms of reaction time to reach 40% epoxide conversion (black line) and partitioning of FAB adduct species at 40% epoxide conversion (colored areas) for water levels from 10-5000 ppm at 25 °C.

Other inactive species

Figure 12. Model predictions of partitioning of catalytically inactive FAB adduct species at 40 % epoxide conversion (colored areas) for water levels from 10-5000 ppm at 25 °C.

Taking into consideration the dominant pathways and water effects on catalytic reactivity, our model predictions recommend a strict dehydration process for all reactants and very low residual water level (< 50 ppm) to achieve fast ring-opening rates. In such a case, the anticipated overall regioselectivity will remain close to the intrinsic regioselectivity of the kinetically dominant Lewis acid catalytic pathways at such low water levels. To further tune or improve the regioselectivity, it may be possible to utilize the diversity in the water-mediated catalytic pathways, as inspired by effects predicted from products as HBA.

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CONCLUSIONS A comprehensive catalytic mechanism was proposed for regioselective ring-opening reactions of 1,2epoxyoctane by 2-propanol as a nucleophile catalyzed by tris(pentafluorophenyl)borane (FAB), featuring competitive binding reactions, traditional Lewis acid catalysis and non-conventional water-mediated and alcohol-mediated catalysis. DFT calculations were conducted to explore the energetics of each elementary reaction and provide initial model parameters. Microkinetic modeling was used in conjunction with DFT calculations and experiments to investigate and validate the complex reaction mechanism. The base-case mechanism was formulated and validated against experimental kinetic data, followed by detailed analysis to unveil mechanistic insights. By adjusting only 9 parameters within reasonable ranges, the microkinetic model captured experimental data with high accuracy and successfully predicted experimental results at different temperatures and with different initial water levels. It was found that the overall regioselectivity is only subtly affected by temperature, and that the main impact is from changes in the water level. Analysis of net rates demonstrated the kinetically dominant catalytic pathways to be the Lewis acid catalytic pathways at residual water levels lower than 1000 ppm. Water-mediated catalysis became non-negligible at higher water levels (> 1000 ppm) and decreased the overall regioselectivity by increasing the contribution from low-regioselectivity pathways where HBA is water. In contrast, the regioselectivity of the water-mediated pathway where HBA is P2 is found to be the highest among all pathways, which helps explain the slightly increasing trend in regioselectivity with increasing conversion. Speciation analysis revealed the substantial retarding effect of residual water concentration on reactivity through a catalyst inhibition mechanism in which three water molecules occupy all binding positions in the hydrogen-bond network and prevent epoxide molecules from binding to form catalytic intermediates. Model predictions suggest two possible courses of action: use of low water levels to achieve both high regioselectivity and fast kinetics and tuning the overall regioselectivity via modulating the contributions of the water-mediated catalytic pathways. Ultimately, this validated mechanism and microkinetic model provide better

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understanding of ring-opening catalysis with FAB in the presence of residual water and could facilitate future improvement of catalyst regioselectivity and reactivity for ring-opening reactions.

ASSOCIATED CONTENT Supporting Information. Materials, methods, catalysis data. This material is available free of charge via the Internet at http://pubs.acs.org.

AUTHOR INFORMATION Corresponding Author * Email: [email protected]; [email protected]; [email protected]; Tel: +1 847-491-5357; +1 847-467-3347; + 1 847-467-1751.

Author Contributions The manuscript was written through contributions of all authors. / All authors have given approval to the final version of the manuscript. Funding Sources This work was supported by The Dow Chemical Company.

ACKNOWLEDGMENT This work was supported by The Dow Chemical Company. We thank Dr. Jaclyn Murphy of The Dow Chemical Co. for useful discussions.

CONFLICT OF INTEREST The authors declare no competing financial interests.

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For Table of Contents Only

P1 P2

O

O

H

5 HBA FAB

Lewis-acid catalysis FAB

FAB

H 2O

FAB

O

H

O

H H

HBA

Water-mediated H catalysis

5

O

O O P1:

O HO

5

O

5

P2:

H

P1 P2 HBA: Hydrogen Bond Acceptor

O OH

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