Linden
Schrecker
a,
Joachim
Dickhaut
b,
Christian
Holtze
b,
Philipp
Staehle
b,
Marcel
Vranceanu
b,
Klaus
Hellgardt
c and
King Kuok (Mimi)
Hii
*a
aDepartment of Chemistry, Imperial College London, Molecular Sciences Research Hub, 82 Wood Lane, London W12 0BZ, UK. E-mail: mimi.hii@imperial.ac.uk
bBASF SE, 38 Carl-Bosch-Straße, 67056, Ludwigshafen/Rhein, Germany
cDepartment of Chemical Engineering, Imperial College London, South Kensington, London SW7 2AZ, UK
First published on 12th September 2022
Kinetic data for reactions between phenyl hydrazine and 1,3-diketones (Knorr pyrazole synthesis) were acquired by using transient flow methods. Supported by further spectroscopic and mass spectrometry data, a microkinetic model was subsequently constructed, which provided new insights into the mechanism, including autocatalysis and the involvement of an unexpected reaction intermediate. During this work, a novel reactant stoichiometry transient flow methodology was demonstrated, allowing the robustness of these models to be asserted.
In contrast, in a flow reactor, the reaction progresses spatially, along the length of the reactor with increasing residence time. Provided good mixing at the point of contact, the measurement of reaction rates can be much more precise, as residence times can be accurately defined. Kinetic data can be collected by changing the flow rate (% conversion vs. residence time, τ). This can be achieved in a stepwise manner, where each data point is collected at a specific flow rate under ‘steady state’ conditions (Fig. 1a). This method of data collection is slow and requires a large amount of material. Alternatively, time-series data collection can also be performed continuously in ‘transient flow’, whereby a step change to the flow rate is introduced to the system, with simultaneous collection of the data during the produced residence time gradient (Fig. 1b). First introduced by Littlejohn et al. in 2011,2 the method greatly facilitates the data acquisition while using less material emulating batch experiments. In the ensuing decade, the concept was further explored by others to determine technical best practice,3 and to acquire kinetic data for different chemistries.4,5 More recently, it has been extended to changes in other reaction parameters, such as temperature6 and the effect of additives (Table 1).7 Collection of data over this change in conditions affords means to access data series that are otherwise time-consuming to collect using batch reactors.
The data collection can be enhanced even further beyond the capability of a batch reactor, by the application of multi-variable ramps simultaneously. Recently, both mono- and bi-variable transient flow ramps were combined with model-based design of experiments (MBDoE) to elucidate kinetic parameters.8 The approach has also been extended successfully to automatically distinguish between predefined kinetic models in simple chemical systems.9
Scheme 1 The Knorr pyrazole synthesis of an unsymmetric 1,3-diketone 1 and mono substituted hydrazine 2via the widely accepted mechanism to form pyrazoles 4 and 4′. |
Previous mechanistic studies have established a correlation between the regioselectivity with several reaction parameters; including: pH, solvent, as well as the electronic and steric characteristics of the substituents (R1 and R2).11–13 These studies were largely based on empirical observations of product distributions under different reaction conditions. Often, a hydroxylpyrazolidine intermediate 3 was observed,12,14 and can be isolated in certain cases.13,15 Thus, the dehydration of 3 to form the pyrazole is generally accepted to be the rate-determining step under pH neutral conditions. To date, there had been only one reported kinetic study of the Knorr pyrazole synthesis, where the reactions between arylhydrazine (R3 = Ar) with trifluoromethyl-substituted diketones (where R1 = CF3)16 were found to be first order in both reactants at pH > 1.6 (eqn (1)).
Rate = k[diketone][phenylhydrazine] | (1) |
Multiple flow rate step changes can be implemented semi-automatically to deliver reactants 1a and 2 with a cumulative flow rate between 5 to 0.2 mL min−1, while the product formation was monitored in-line by infrared spectroscopy. Adopting the transient flow methodology, a number of kinetic experiments were initially performed at different concentrations and reaction stoichiometries, to delineate the reaction order of each reactant, as well as product and by-products (Table 2).
The ‘different excess’ experiments (Fig. 2, experiments A–C) confirmed that the kinetic model was more complex than initially thought: experiments B and C were not superimposable, implying that the effect of changing the concentration of diketone 1a and phenyl hydrazine 2 is not the same, as will be the case if the rate equation (eqn (1)) is true. Interestingly, while the presence of extraneous water had no effect on the reaction rate (Fig. 2, experiments F and G), product autocatalysis was occurring (Fig. 2, experiments E and F).
Fig. 2 Time series data collected for the reaction of diketone 1a and phenyl hydrazine 2 using residence time ramps over a range of experiments, described in Table 2. |
To interrogate this further, a new transient flow method was also developed: by varying flow rate of each pump, but maintaining the same cumulative flow rate, to provide independent data to verify the results of different excess experiments obtained by varying cumulative flow rates. By varying reactant stoichiometry at a fixed residence time (τ), a data series of different initial reactant stoichiometries can easily be produced (Fig. 3a). With a simple linear kinetic model, we would expect the data to overlap when plotted against [1a]/[2] and [2]/[1a], as within such a kinetic model [1a] and [2] are interchangeable (eqn (1)). However, we observed considerable discrepancy between the two plots (Fig. 3b), further verifying our previous observations that the simple rate law does not apply to this reaction.
Fig. 3 (a) Pump method for 20 minute residence time reactant stoichiometry ramp; (b) reactant stoichiometry ramp at a 20 minute residence time, 70 °C and using 0.4 M stock solutions of 1a and 2 between ratios of [1a]/[2] of 0.16 M:0.24 M to 0.24 M:0.16 M plotted against [1a]/[2] and [2]/[1a] demonstrating clear conflict with the simple rate law (eqn (1)). The fitted 3° lines are as a visual aid. |
Interestingly, the HPLC-MS data of the reaction mixtures revealed the presence of two reaction intermediates: the hydroxylpyrazolidine 3a, and another that results from the di-addition of phenylhydrazine, 5a (Scheme 2). Both of these intermediates can also be generated by the addition of 1a to 2 in ethanol, which slowly converts into the pyrazole product when left at ambient conditions.
Scheme 2 The possible forms of the mono-addition intermediate (3a/6a) and di-addition intermediate (5a/7a). |
Both intermediates can exist either in a closed (3a and 5a) or open form (6a and 7a), although the former is presumably more stable thermodynamically. While the observation of 3a is somewhat expected,12,14 the involvement of 5a is not, although there is some precedent for similar molecules, which are unable to eliminate and aromatise.17 Attempts to verify the structures of these intermediates by NMR spectroscopy led only to the observation of intractable complex mixtures (Fig. S13 and S14†).
The complexity of the model means there are multiple equivalent optimal solutions that can be fitted to the available data. Nevertheless, after a few iterations, we were able to arrive at a set of kinetic rate constants (Table 3) that appear to fit most consistently across the reactions of both 1a and 1b (Table 2, experiments A–G for 1a and A–E for 1b). The key features of the model are highlighted below:
R | Me | Et |
---|---|---|
k 1f | 2.23589 | 6.22879 |
k 1r | 0 | 0 |
k 2f | 1753.989 | 81.44262 |
k 2r | 0.25614 | 0.01174 |
k 3f | 13860.73 | 551.6668 |
k 3r | 0 | 0 |
k 4 | 0.63061 | 0.74228 |
k 5 | 0 | 0 |
k 6 | 0.0399 | 0.44781 |
k 7 | 11.87965 | 3.26931 |
k 8 | 0 | 0 |
k 9 | 3.69715 | 4.97573 |
RMSE | 0.01755 | 0.01801 |
1. The initial nucleophilic attack (k1f) of the phenyl hydrazine appear to be faster with the diethyl-substituted diketone (R = Et, 1b) than acetylacetone (R = Me, 1a). This can be rationalised by taking into account the two geometrical forms of the hydrazone intermediate 6: where only the Z-form can proceed to form the ring-closed intermediates 3 or 5, and the unproductive E-form dissociating back to 1 and 2. Presumably, the formation of E-6b is more facile than that for E-6a, due to unfavourable 1,3-(aza)allylic strain present in its Z-isomer.19
2. As may be expected, the formation of the hydroxypyrazolidine intermediate 3 is kinetically favoured, with similar K2 values (k2f/k2r ∼ 7000). In contrast, the formation of hydrazidopyrazolidine 5a (R = Me, k3f) proceeds 25 times faster than 5b (R = Et), which is attributed to steric strain at the highly substituted carbon.
3. Neither aromatisation of 3 nor 5 proceed in any appreciable amount (k5/8 ≈ 0) unless catalysed by the product 4 (k6/9) or diketone 1 (k4/7). The role of the diketone (pKa 9) is presumably to provide an acid-catalysed pathway. We speculate that 1 could be acting as a base/proton-acceptor to promote the elimination. NMR studies confirmed there is no significant ion pair effects between the product and the diketone, and hence it is plausible that both pathways can occur concurrently.
4. Overall, the aromatisation of 5 is considerably faster than that of 3, by orders of magnitude (k7/9 ≫ k4/6), consistent with our earlier postulation of the higher steric strain of 5.
Subsequently, the addition of phenyl hydrazine to a number of symmetric diketone substrates (1b–e, where R = Et, i-Pr, i-Bu and t-Bu, respectively) was performed, to confirm the presence of different intermediates by HPLC-MS. Apart from 1e (which did not react under these conditions), mono-addition intermediates 3 (or E-6) were detected. However, the presence of 5 was only observed with 5b (R = Et) and 5d (R = i-Bu), suggesting its formation is strongly dictated by steric effects.
Subsequently, the reaction of the unsymmetrical hexan-2,4-dione (R1 = Me, R2 = Et, 1f) and phenyl hydrazine were performed under different excess conditions (Scheme 4). Although neither excess experiment produced regioselectivity, we found that the ratio of regioisomeric pyrazole products (4f:4f′) does indeed vary, depending on which reactant was in excess. Pyrazole 4f was identified as the major product in both cases, however the ratio of products was more equal with an excess of phenyl hydrazine (1.7:1), compared to when diketone 1f was present in excess (2.5:1). This is contrary to that expected from the reactant stoichiometry ramps for the symmetric substrates, which showed a greater difference in the relative rates with an excess of phenyl hydrazine. This suggests a more complex interplay between the two R groups may be occurring.
Scheme 4 The reaction of unsymmetrical diketone 1f and phenyl hydrazine to form regioisomeric pyrazole products 4f and 4f′. |
Last but not least, the microkinetic model was further validated by the construction of a response surface generated in MATLAB. This was compared with the experimental data obtained from reactant stoichiometry ramps, different excess experiments and bi-variable transient ramps (Fig. 5). The good overlay between the experimental data to the model response surface confirms the accuracy and robustness of the model: the extra transient experiments, as well as steady state flow data points, acted as independent verification for the model and the different transient flow methods through repeated points. These surface comparisons allowed us to visually discard models which, despite good RMSE scores, did not compare well for the rest of the independent data due to overfitting.
Microkinetic modelling revealed autocatalysis and the prominence of unusual kinetic pathways via an unexpected di-addition intermediate 5. Surprisingly, different kinetic pathways dominate between acetyl acetone 1a and heptane-2,4-dione 1b, despite only a small change of the R substituent from a methyl to an ethyl group. DFT studies are currently underway to study the prominence of different reaction pathways between the reaction with 1a and 1b, and will be reported elsewhere.
Development of novel reactant stoichiometry ramps allowed us to better investigate this mechanistic change and suggested that the regioisomeric outcome of the reaction of the corresponding unsymmetric diketone 1f could be perturbed by reactant stoichiometry, subsequently confirmed by further experimentation.
Orthogonal transient flow methods, including novel reactant stoichiometry ramps and multivariate ramps, allowed quick access to data which would take much more time, material and effort to emulate with batch methods. The robustness of the microkinetic model, and of our novel transient flow methods, was further validated by comparison of the microkinetic model response surface with independent transient experimentation. It is envisaged that this approach could be applied to other challenging kinetic elucidation problems in the future.
Footnote |
† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d2re00271j |
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