Toward the Identification of Intensified Reaction Conditions Using

Oct 30, 2018 - Artie McFerrin Department of Chemical Engineering, Texas A&M University , 3122 TAMU, ... Industrial & Engineering Chemistry Research...
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Toward the Identification of Intensified Reaction Conditions Using Response Surface Methodology: A Case Study on 3‑Methylpyridine N‑Oxide Synthesis Jingyao Wang,†,‡ Yanyan Huang,§,∥ Benjamin A. Wilhite,*,†,‡ Maria Papadaki,‡,⊥ and M. Sam Mannan†,‡

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Artie McFerrin Department of Chemical Engineering, Texas A&M University, 3122 TAMU, College Station, Texas 77843-3122, United States ‡ Mary Kay O’Connor Process Safety Center, Texas A&M University, 3122 TAMU, College Station, Texas 77843-3122, United States § Department of Chemistry, Texas A&M University, College Station, Texas United States ∥ CAS Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190 China ⊥ Department of Environmental and Natural Resources Management, School of Engineering, University of Patras, Seferi 2, Agrinio 30100, Greece ABSTRACT: Identification of inherently safer and intensified reaction conditions is a vital step for transformation of traditional batch/semibatch synthesis to continuous operation. Accelerating reactions is challenged by several safety and efficiency issues including thermal runaway risk, side reactions, final product degradation, and reactor overpressure. This work demonstrates the use of response surface methodology to identify inherently safer and more efficient intensified reaction conditions for 3-methylpyridine N-oxidation performed in a semibatch pressure-resistant isothermal calorimeter. The experimental conditions were selected to screen various operating-variable combinations using Box−Behnken design of experiments. Regression models were developed correlating the catalyst amount, oxidizer dosing-rate, and reaction temperature with reactor pressure and N-oxide yield; good agreement with experimental data obtained in the present study and from literature was achieved. Results indicate that, even when conducted in a semibatch mode, the reaction is inherently safer and more efficient under intensified conditions. investigation of reaction mechanism or kinetics.9−16 RSM utilizes design of experiment approaches based upon identification of key variable (inputs) to generate an optimal number of experiments to fit a general-form empirical model relating reactor output (e.g., yield, pressure) to input variables. The least-square method (LSM) is then employed to calculate the empirical model coefficients. Finally, several statistical evaluation strategies are used to evaluate the credibility of the resulting empirical regression model in predicting the system response.17 In this work, the authors employ the RSM approach to identify inherently safer and intensified reaction

1. INTRODUCTION Many fine chemical synthesis reactions are fast and highly exothermic, and therefore subject to significant risk of thermal runaway.1 Limited by heat removal capacity, most industrial batch-wise processes must limit reaction rates via low temperature, concentrations, and/or controlled dosing of reactants via a semibatch approach.2 Pharmaceutical agrochemical and fine chemical industrial reactions are often performed in such reactors following kinetic-free scale-up and optimization methods.3−6 In contrast, the concept of Novel Process Window proposed by Hessel et al. employs intensified reaction conditions that are far from conventional batch practices including elevated temperature, catalyst amount, and/or reactant concentrations.2,7,8 However, implementation of Novel Process Window requires an understanding of how these intensified conditions impact reaction behavior. Response surface methodology (RSM) provides an efficient means of identifying the interaction between multiple system input parameters and output response, in lieu of detailed © XXXX American Chemical Society

Special Issue: Frameworks for Process Intensification and Modularization Received: Revised: Accepted: Published: A

August 10, 2018 October 22, 2018 October 30, 2018 October 30, 2018 DOI: 10.1021/acs.iecr.8b03773 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research

increase the bubble point of the reaction mixture with a suitable range of temperatures and catalyst concentrations experimentally identified at reaction pressure of 4−6 bar.27,28,38 In this work, RSM was employed to rapidly search this novel intensified operating window for inherently safer and more efficient operation conditions as compared to current ambient pressure/low temperature conditions used in industry. Reaction temperature, catalyst amount, and oxidizer feeding rate were selected as key variables affecting reactor efficiency. Final reactor pressure (reflecting the extent of hydrogen peroxide decomposition) and N-oxide yield were used as measures of both process safety and efficiency. The final products were analyzed using HPLC and GC/MS, thus quantifying the yield to N-oxide. The single factor analysis of catalyst, temperature, and dosing rate on the reaction pressure and final yield is presented, and a regression model correlating the three input and two output variables is developed. Finally, the synergistic effects among input variables are mapped via response surface analysis and are schematically shown in this work.

conditions for the industrially relevant case of 3-methylpyridine N-oxide synthesis. Alkylpyridine N-oxides are commercially important as specialty chemical intermediates used to synthesize pharmaceuticals, insecticides, herbicides, textile adhesives, solvents, catalysts, and polymers with unique physical properties.18−25 Alkylpyridine N-oxide synthesis is a highly exothermic process conventionally performed isothermally open to the atmosphere in a semibatch reactor using hydrogen peroxide as oxidant and phosphotungstic acid as homogeneous catalyst.26,27 Under these conditions, the desired N-oxidation reaction (I) competes with the decomposition of hydrogen peroxide (II) to water and noncondensable oxygen gas. Thus, the primary operating hazards involve overpressure and fire due to the flammability of the primary organic reactant in an oxygen rich environment.28,29 Additionally, the product alkylpyridine Noxide can decompose at temperatures of the order of 200 °CC depending on the kind of the N-oxide. Conventional operating conditions are thus selected to enable escape of generated oxygen while maintaining low rates of reaction with up to 12 h residence time such that runaway can be prevented.30−32 Alkylpyridine N-oxide was the major raw material in the Corden Pharmachem batch runaway incident,33 in which the addition of solvent was omitted by the operator; as a result the reaction was conducted under abnormally high concentration of pyridine N-oxide. The cooling system and pressure relief in the batch reactor were insufficient to handle such intensified reaction conditions, and thus, thermal runaway of pyridine Noxide decomposition occurred, causing 1 fatality and reactor rupture.

2. METHODOLOGY 2.1. Experimental and Analytical. 2.1.1. Reagents. 3Methylpyridine (99%, Sigma-Aldrich, P42053), hydrogen peroxide (35 w.t.%, Sigma-Aldrich, 349887), and phosophotungstic acid (Sigma-Aldrich, P4006) were used as supplied. 2.1.2. Calorimeter. The schematic representation of the experimental apparatus RC1e Mettler-Toledo system is shown in Figure 1. The reactions were performed in a closed 1.2 L pressure resistant (10 bar-g) glass reactor. The reactor is equipped with vertical and horizontal heat flux sensors for heat flow measurement. The reactor is equipped with a pressure gauge (analog AISI316, digital HC-22) and a rupture disc, set to 10 bar. The semibatch dosing of hydrogen peroxide is achieved using a ProMinent solenoid metering pump, with a safety interlock program met to terminate dosing operation if reactor temperature or pressure exceed 140 °CC or 6 bar-g, respectively. A ReactIR 15 infrared spectrometer consisting of a Mercury Cadmium (MCT) detector and a diamondcomposite in situ FTIR sensor probe was used for monitoring the reaction species in real time. While industrial-scale reactors require a turbine-type stirrer, an anchor stirrer was used to

The N-oxidation of alkylpyridines has been used as a model for the development of calorimetric methods for studying complex highly exothermic reactions since the late 1990s.26−28,31,32,34−37 Previous research has demonstrated the importance of elevated temperature in inhibiting H2O2 decomposition, in turn requiring a pressurized reactor to

Figure 1. Schematic of RC1e Mettler-Toledo heat-flow calorimeter. B

DOI: 10.1021/acs.iecr.8b03773 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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The actual compounds contained in the postreaction solution were also qualitatively identified through an Agilent 7890B GC coupled with an Agilent 5977A mass. Samples taken from the reactor were appropriately diluted (1 μL of sample in 1 mL of water) and injected directly without any pretreatment. The injection temperature was 190 °C. The temperature ramp was as follows: initial temperature to 50 °C; hold for 3 min. Then a ramp of 10 °C/min to reach 180 °C; hold for 3 min. The temperature of the ion source and the interface were set at 235 °C and 280 °C, respectively. A split ratio of 100:1 was used. The carrier gas was ultrahigh pure helium (Praxair) with a pressure of 7.89 psi and a flow rate of 1 mL/min. The column used was HP-5MS (30 m × 0.25 mm i.d., 0.25 μm film thickness) coated with (5%-phenyl)methylpolysiloxane. The MS was operated in electron ionization mode with a potential of 70 eV, and the spectra were obtained in a full scan mode of 50−550 amu. The scan time was 3 min. 2.2. Response Surface Methodology. To investigate the relationship between important operating variables and efficiency/safety parameters, the response surface methodology was utilized. The key stages involved in the method are variables selection, design and performance of experiments, mathematical/statistical treatment of the results, and finally model evaluation. Previous studies have indicated that the selectivity of the N-oxidation is strongly affected by the amount of catalyst,35 the reaction temperature,37,38 and the accumulation of H2O2 in the reactor, here expressed directly by the dosing rate.26 For each variable, three value levels were selected specifically: catalyst amounts of 4 g, 8 g, and 12 g, dosing rates of 2, 4, and 6 g/min, and temperatures of 85 °C, 107.5 °C, and 130 °C, respectively. The selection of these values was based on preliminary experiments on the physical properties of the reacting mixture and on the findings of previous studies on alkylpyridines.26−28 The minimum temperature was selected based on previous studies which showed that at 85 °C and low amounts of catalyst (a) hydrogen peroxide decomposition was excessive and (b) N-oxidation could not proceed beyond a catalyst dependent conversion, as practically most hydrogen peroxide added was decomposing, leaving little for the N-oxidation.35 The range of dosing rates was defined by the capacity of the instrument and the need for an uninterrupted continuous addition. Dosing rates higher than 6 g/min were exceeding the reactor capability to handle the oxygen produced at 85 °C. Maximum catalyst concentration was selected based on previously observed solubility limits.39 In light of a maximum operating jacket temperature of 160 °C for the RC1 apparatus, a maximum temperature of 130 °C was selected. For three-level, three variable full factorial design, 27 experimental measurements at specified conditions are required if all possible combinations were to be considered.17 To reduce the number of experimental tests without losing the capability of capturing system characteristics, Box−Behnken design of experiment was applied to identify a set of 13 experimental conditions sufficient to calculate the coefficients of an empirical model and evaluate its significance of regression.40 An additional 5 repeat tests were also performed to enable model validation via lack-of-fit test.17 Operating conditions and final reactor pressure/reaction yield for each experimental trial are listed in Table 1. A polynomial regression model was developed to quantify the relationship of process input variables and responses. The generic formula employed is shown in eq 1.

provide enough space for the inserted measurement probes (temperature sensors, calibration heater, FTIR probes). Anchor stirrer, calibration heater, and pressure/temperature sensors inserted inside the vessel were all made of Hastelloy. Reactor temperature was controlled by high performance a thermostat RTCal Box connected to a Julabo temperaturecontrolled batch. Energy balance and data analysis was conducted by iControl software in real time. 2.1.3. Experimental Procedure. Initially, 240 g (2.6 mol) of 3-picoline were manually loaded into the reactor. The appropriate amount of catalyst was dissolved in 10 g of deionized water and added to the reactor; the catalyst container was then rinsed with 10 g of water which was also added to the reactor. The stir-rate of the anchor stirrer was set at 400 rpm, which was previously shown to be sufficient for removing heat and mass transfer resistances for this reaction and apparatus.28 The reactor was then heated-up to the desired temperature and allowed to stabilize, such that all measurements were obtained isothermally under heat-flow mode (wherein the heat of reaction is measured via heat flow through the reactor wall). The heat transfer coefficient and baseline heat losses to ambient were then determined, employing the calibration heater, and the reactor temperature was allowed to stabilize again. Reaction was initiated by adding 250.44 g of 35 wt % H2O2 solution at a constant dosing rate. Throughout the reaction, reactor temperature, jacket temperature, stirring rate, reaction heat-flow, balance reading, dosing material temperature, and reactor pressure were recorded. If the reactor pressure approached 6 bar, the pressure was manually released to reach a value at least 1 bar-g higher than the vapor pressure of water at the reactor temperature, so as to have a minimal impact on the vapor−liquid equilibrium of the system. This pressure drop was then added to all subsequent measured pressure values to obtain the final total generated pressure profile. All pressure profiles exceeding 6 bar-g follow a smooth curve after correcting for venting, similar to those where venting was not necessary. Additionally, continuous in situ FTIR monitoring of 3-methylpyridine and 3-methlypyridine Noxide concentrations confirmed that venting did not measurably affect their quantities in the liquid-phase. This indicates that the error associated with venting does not affect the validity of the results shown in this study. Once the dosing process was completed, the reactor was left to stabilize. After reaction had reached equilibrium, a second calibration of heat transfer coefficient was performed. The reactor was then left to cool down to ambient temperature and final pressure was recorded prior to venting. Liquid product was analyzed via gaschromatography coupled with mass spectrometry (GC/MS) and high-performance liquid chromatography (HPLC). 2.1.4. Analytical Procedure. Reaction yield was quantified using a Shimadzu (Kyoto, Japan) HPLC equipped with an LCAD pump, degasser, autosampler, PDA detector (SPD-M20A, Shimadzu), and a system controller. A Welch Ultimate XBC18 column (250 mm × 4.6 mm) with pore size of 120 Å and particle size of 10 μm was used. One μL of diluted sample (0.1 g sample in 100 mL water) was injected. Ιsocratic phase 25% acetonitrile and 75% water was set at 1 mL/min at a pressure of 46 bar. The chromatograms were monitored at 254 nm. A calibration curve was established using external standards at different concentrations and was used for quantification. For each of the samples, at least two measurements were performed. The measurement reproducibility was better than 1%. C

DOI: 10.1021/acs.iecr.8b03773 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research Table 1. Box−Behnken Design of Experiment for the Study of Temperature, Catalyst, and Dosing Rate Variables Impact on Reactor Pressure and 3-Methylpyridine N-Oxide Yielda Run

Temperature (°C)

Catalyst (g)

Dosing rate (g/min)

N-oxide Yield (%)

Pressure (bar)

1 2 3 4 5 6 7 8 9 10 11 12 13* 14* 15* 16 17* 18*

107.5 85 85 107.5 130 130 107.5 107.5 107.5 85 130 85 85 85 107.5 130 130 130

8 8 8 4 12 8 4 12 12 4 4 12 8 8 4 8 8 12

4 2 6 6 4 2 2 2 6 4 4 4 2 6 6 6 6 4

96.78% 91.52% 85.02% 87.56% 99.29% 98.35% 96.34% 99.09% 98.64% 77.03% 97.38% 92.14% 92.55% 87.10% 92.19% 98.17% 96.68% 99.30%

5.16 11.64 18.97 16.35 4.28 4.68 6.30 3.25 3.30 27.94 4.63 12.16 13.72 16.70 13.97 4.64 5.18 5.43

Figure 2. Measured experimental data trends for isothermal 3methypyridine semibatch N-oxidation reaction at 107.5 °C with 12 g of catalyst and 2 g/min 35 wt % hydrogen peroxide dosing. Reaction power (gray); Reaction power curve after moving average treatment (red); pressure (green); jacket temperature (blue); reactor temperature (orange); H2O2 solutions dosing rate (black).

the set point, reflecting a step up in reaction heat duty. The reactor pressure increased throughout hydrogen peroxide dosing, owing to the generation of oxygen via hydrogen peroxide decomposition, increased vapor pressure arising from introduction of water, and reduced overhead space. Overall, the reaction heat duty was constant during dosing, indicating the reaction was rate limited by the dosing rate of the hydrogen peroxide. After dosing ceased, any accumulated hydrogen peroxide rapidly depleted causing a small pressure rise indicating decomposition, and subsequently reaction heat duty quickly returned to baseline. The maximum reactor pressure reached under these conditions was 3.2 bar which was well below the design pressure of the RC1. The pressure of noncondensable gases at ambient temperature, measured after the reactor was cooled down, was 1.96 bar. After the reactor was cooled-down samples were collected for analysis using HPLC and GC/MS. 3.2. Final Product Analysis. Typical HPLC results of products synthesized corresponding to conditions for multiple reactions are shown in Figure 3. In all tests results, only two

a

Additional repeat tests are marked by asterisk.

y = β0 + βA XA + βBXB + βC XC + βAA XA 2 + βBBXB2 + βCC XC 2 + βABXAXB + βAC XAXC + βBC XBXC

(1)

where y represents the pressure or yield, βi represents the coefficients for linear/quadratic/interaction terms XA (temperature), XB (catalyst mass), and XC (hydrogen peroxide dosing rate). The statistical significance of each term in eq 1 was quantified and evaluated via the P-value (probability of the occurrence) of a given event, and P ≤ 0.05 was selected as the criterion for statistical significance. Coefficients with P > 0.05 were considered as likely to satisfy the null hypothesis (the coefficient equals to zero), and as such they were ignored. Once the final forms of eq 1 were obtained for both pressure and yield, best-fit values of all retained βi parameters were determined via least-squares regression. Finally, the resulting model expressions were validated using a lack-of-fit (LOF) test applying a Plof value of 0.05 sufficient to confirm statistical significance in fitting the experimental data. All data analysis was performed using Minitab software (version 18, Minitab Inc., USA). Coefficients were determined using the leastsquares minimization method, and the regression model statistical significance was tested using analysis of variance (ANOVA) through Minitab software.

3. RESULTS AND DISSCUSSION 3.1. Calorimetry Data Analysis. Reactor pressure, reaction heat duty, reactor temperature, and dosing rate for a representative isothermal calorimetry experiment at 107.5 °C, with 12 g catalyst and 2 g/min dosing rate, are presented in Figure 2. Initially, the reactor was heated up to 107.5 °C until t = 60 min. After the calibration and stabilization stage from 75 to 100 min, the dosification of the hydrogen peroxide (from t = 210 min to t = 345 min) started at a constant rate. As can be seen in Figure 2, the reactor temperature increased slightly once dosing begins while jacket temperature decreased by approximately 10 °C to maintain the reactor temperature at

Figure 3. HPLC results of different end-samples. Reaction conditions: 85 °C/8 g catalyst/6 g min−1 (blue); 130 °C/8 g catalyst/2 g min−1 (red); 107.5 °C/4 g catalyst/6 g min−1 (gray); 85 °C/4 g catalyst/4 g min−1 (yellow); 107.5 °C/8 g catalyst/4 g min−1 (green). D

DOI: 10.1021/acs.iecr.8b03773 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Figure 4. GC chromatograms of final product at 85 °C, 4 g of catalyst, and 4 g/min hydrogen peroxide dosing rate.

Figure 5. Mass spectra: (a) mass spectrum comparison of NIST standard 3-methylpyridine (blue) with sample collected from HPLC peak at 5.0 min (red); (b) mass spectrum comparison of NIST standard 3-methylpyridine N-oxide (blue) with sample collected from HPLC peak at 13 min (red).

Figure 6. Comparison of reactor pressure profile with 4 g (red) and 12 g (black) of catalyst at (a) 85 °C and 4 g/min dosing rate; (b) 107.5 °C and 6 g/min dosing rate; (c) 107.5 °C and 2 g/min dosing rate; and (d) 130 °C and 4 g/min. (The pressure profile in Figure 6(a) and 107.5 °C, 4 g catalyst with 6 g/min dosing rate in Figure 6(b) were corrected for venting as described in 2.1.3.)

peaks were identified, the final product 3-methypyridine Noxide with residence time from 3.8 to 5.1 min and the original reactant, 3-methypyridine with a residence time of 8 to 10 min. The GC chromatograms of the end solution obtained at 85 °C, at 4 g catalyst and 4 g/min hydrogen peroxide dosing rate,

are shown in Figure 4. Similar to HPLC results, only two major peaks were identified at residence times (RT) of 5 and 13 min, respectively; their mass spectra are shown in Figure 5(a) and (b). The peaks at RT of 5 and 13 min match with NIST standard 3-methylpyridine and 3-methylpyridine N-oxide, E

DOI: 10.1021/acs.iecr.8b03773 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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higher the N-oxide yield in all cases. It can be observed that the impact of catalyst on N-oxide yield decreases as temperature increases and dosing rate decreases. 3.3.2. Impact of Temperature. As discussed above, increasing temperature reduces the impact of catalyst amount on pressure increase and N-oxide yield. To further study the independent effects of temperature, two groups of three controlled experiments were performed. Figure 8(a) shows the pressure profile of three measurements performed with 4 g of catalyst and 4 g/min of dosing rate at the selected “high”, “medium”, and “low” temperatures (130 °C, 107.5 °C, and 85 °C, respectively). Significant hydrogen peroxide decomposition occurred at 85 °C resulting in a reactor pressure of almost 30 bar-g corresponding to 0.34 mol of H2O2. At 107.5 °C, approximately 0.13 mol of hydrogen peroxide decomposed, as indicated by an increase of 16 bar-g. At 130 °C, the reaction reached completion within 5 bar-g of reactor pressure and 1.86 bar-g (0.07 mol of hydrogen peroxide decomposition) at ambient temperature. Figure 8(b) shows the reactor pressurehistory at the same temperature and dosing rate but with 12 g of catalyst. As can be seen in Figure 8, this has an important impact on hydrogen peroxide decomposition at 85 °C, less at 107.5 °C, and negligible at 130 °C. This indicates that there is an optimal amount of catalyst for each temperature; for the conditions of those measurements, it is about equal or less than 4 g for 130 °C. Figure 9 shows the impact of temperature on the N-oxide yield for this set of experiments. Overall, it is shown that increasing the temperature from 85 °C to 130 °C can dramatically increase the N-oxide yield. This verifies the observations that operation at higher temperature results in lower final reactor pressure due to increased N-oxidation selectivity and suppressed hydrogen peroxide decomposition. Similar to pressure, the impact of temperature upon yield was more pronounced than catalyst amount. This indicates that higher catalyst amount and higher temperature can both enhance the main reaction and the synergistic effect exits among those two variables. Higher temperature can reduce the amount of catalyst required for reaching high yield. Moreover, the dosing rate of 4 g/min seems fast enough to practically ensure reaction completion at about 65 min for the measurements performed at 130 °C. A faster dosing rate may allow reaction completion (>98% N-oxide yield) at an even shorter time without a measurable increase of hydrogen peroxide decomposition; a slower dosing rate after 40 min of dosing, on the other hand, may result in less hydrogen peroxide decomposition and higher (>99.5% N-oxide yield). To complement the above observations of synergetic effects between the catalyst amount and reaction temperature, Figure 10 presents the reactor pressure and yield response at the three selected temperatures under the same 4 g/min dosing rate for three different catalyst amounts. 3.3.3. Impact of Dosing Rate. The impact of dosing rate was studied in four pairs of controlled experiments. Figure 11 and Figure 12 present the pressure profile and the N-oxide yield, respectively, when different dosing rates but the same catalyst concentrations and temperatures are employed. It is worth comparing the pressure profile of the reactor both during and after dosing. In each case, specifically, rising pressure before dosing ends was mainly because of the oxygen generation from hydrogen peroxide decomposition and the increased vapor pressure of water, while pressure increase after the end of dosing is exclusively owed to hydrogen peroxide

respectively, with over 95% of confidence. The samples collected from other reaction conditions also yield similar GC/MS results indicating the N-oxidation of 3-methylpyridine is highly selective and only 3-methylpyridine N-oxide is synthesized. 3.3. Single Factor Analysis. Before analyzing the synergistic effects among the three independent variables (temperature, dosing rate, and catalyst amount) to reactor pressure and 3-methylpyridine N-oxide yield, it is necessary to first investigate the impact of each by single factor analysis. Thus, the impact of catalyst, dosing rate, and catalyst amount was investigated as follows. 3.3.1. Impact of Catalyst. To identify the impact of catalyst amount on the reaction safety (pressure) and efficiency (yield), experiments were performed employing both low (4 g) and high (12 g) catalyst loading at four different combinations of temperature and dosing rate. The total generated reactor pressure during the reaction stage is shown in Figure 6 where td indicates the end of dosing. Figure 6(a) shows the measured reactor gauge-pressure during an experiment performed at 85 °C and 4 g/min with the high and low catalyst amounts. The reactor pressure reached 28.1 bar when 12 g of catalyst were used as opposed to 12.2 bar when 4 g were used. In those experiments, the pressure still increased by almost 5 bar after the end of dosing. This indicates that a significant amount of hydrogen peroxide had accumulated in the reactor after dosing and overpressure hazard in this scenario is significant. Similarly, in Figure 6(b), performed at 107.5 °C and 6 g/ min dosing rate, the reactor gauge-pressure reached 13.2 bar with 4 g of catalyst as opposed to 3.2 bar with 12 g of catalyst. The reactor pressure increase after the end of dosing was 2 bar in the first case versus 0.5 bar in the latter. This indicated that accumulation of H2O2 in the reactor was higher when less catalyst was used with the impact of the catalyst quantity on hydrogen peroxide accumulation increasing as reactor temperature decreased. At 130 °C with 4 g/min dosing rate, seen in Figure 6(d), the catalyst amount had minor impact on reactor pressure, with the reactor pressure changing only slightly after dosing stopped, indicating negligible accumulation of hydrogen peroxide. Overall, increasing the catalyst amount significantly reduced the reactor pressure at most reactor temperatures and dosing rates employed in this study. However, the impact of catalyst amount on reactor pressure reduces with higher reactor temperature (due to increased catalyst activity) and lower dosing rates (due to increase of selectivity of Noxidation). Similar phenomena were also observed experimentally by Pineda-Solano et al. and Papadaki et al.26,28 Figure 7 shows a comparison of the N-oxide yield at four controlled-experiment groups employing different amounts of catalyst while keeping the same temperature and dosing rate. As can be clearly seen, the higher the catalyst amount, the

Figure 7. Impact of catalyst amounts on N-oxide yield. F

DOI: 10.1021/acs.iecr.8b03773 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Figure 8. Pressure profile comparison of measurements performed at 85 °C (black line), 107.5 °C (blue line), and 130 °C (red line) with (a) 4 g catalyst and 4 g/min dosing rate; (b) 12 g catalyst and 4g/min dosing rate. (Pressure profiles of 107.5 °C/85 °C, 4 g catalyst with 4 g/min dosing rate in Figure 8(a) and 85 °C, 12 g catalyst with 4 g/min dosing rate in Figure 8(b) were corrected for venting as described in section 2.1.3.)

rates increased the product yield. The impact of dosing rate on product yield was more pronounced at low temperature (85 °C and 8 g catalyst) or low catalyst concentrations (107.5 °C and 4 g catalyst). 3.4. Response Surface Analysis. The single factor analysis showed that higher temperature and catalyst amount increases the N-oxidation selectivity and suppresses hydrogen peroxide decomposition, while dosing rate does the opposite. It was also found that the impact of each variable was strongly affected by other operating variables. Particularly, the variation of a single factor is most effective when the other two factors are held at low value. For example, the change of catalyst amount has the most significant effect on the pressure/yield when high dosing rate and low temperature exists. To further study the synergistic effects of three variables to system response, response surface methodology was applied. Both Noxide yield and pressure were selected to measure the system response. Response regression models were developed to correlate its dependence on the three input variables through appropriate mathematical and statistical treatment. Schematic surface-response contours are presented to visualize the impact of each variable on the system. 3.4.1. Regression Model Development. As mentioned in section 2.2, the terms of eq 1 which were statistically significant (the null hypothesis can be rejected and the respective term should be kept, P < 5%) and which were insignificant (and likely to satisfy the null hypothesis P > 5%) were tested using the analysis of variance (ANOVA). Table 2 and Table 3 present the ANOVA results for eq 1 for pressure and product yield. The P-values of the regression model and each coefficient are shown in the column P-value. As shown in Table 2 and Table 3, the P-value for yield and pressure regression model are 4.53 × 10−4 and 4.39 × 10−5, respectively, and both of which are much smaller than 0.05. This means the models fit the experimental data very well. The Plof values (“lof” stands for lack of fit) for the two models are 0.17 and 0.11, which are greater than 0.05. Therefore, both the yield and pressure polynomial regression model are satisfactory. R2 of each regression model was 0.943 and 0.969, respectively. As can be seen in Table 2 and Table 3, the single factor coefficients for temperature (T), dosing rate (d), and catalyst mass (m) are all statistical significant in both regression models, which is consistent with single-factor studies reported above. After removing the statistically insignificant terms, the polynomial regression models for the yield and pressure

Figure 9. Impact of temperature and catalyst mass on the N-oxide yield.

Figure 10. Synergistic effects of temperature and catalyst under 4 g/ min dosing rate on (a) N-oxide yield; (b) pressure (hydrogen peroxide decomposition).

decomposition and thus it is a measure of accumulation in the reactor of hydrogen peroxide at the end of dosing. As seen in Figure 11, the hydrogen peroxide accumulation due to increased dosing rate was most significant at 85 °C, less significant at 107 °C with low catalyst amount, and negligible at 130 °C and 107 °C under high catalyst amount. Therefore, the dosing rate is a dominant factor on reactor pressure only under either low catalyst or low temperature conditions. As shown in Figure 11(a) decomposition of hydrogen peroxide at 85 °C and 8 g catalyst is not significant for the first 17 min when dosing rate is 6 g/min and for the first 58 min when dosing rate is 2 g/min. Similarly, for Figure 11 (b), significant hydrogen peroxide decomposition at 107.5 °C and 4 g catalyst did not practically occur for 82 min when dosing rate was set at 2 g/min. Evidently accumulation of hydrogen peroxide in the reactor can be minimized if dosing rate is programmed to decrease as conversion advances. The impact of hydrogen peroxide dosing rate on final product yield is presented in Figure 12. Overall, lower dosing G

DOI: 10.1021/acs.iecr.8b03773 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Figure 11. Reactor pressure profile at different dosing rates (a) 85 °C and 8 g catalyst; (b) 107.5 °C and 4 g catalyst; (c) 107.5 °C and 12 g catalyst; (d) 130 °C and 8 g catalyst. (The pressure profile in Figure 11(a) and 107.5 °C, 4 g catalyst with 6 g/min dosing rate in Figure 11(b) were corrected for venting as described in section 2.1.3.)

Pressure = 159.60 − 2.31T − 4.64m + 3.23d + 7.78 × 10−3T 2 + 0.045T ·m − 0.29m ·d (3)

where T, m, and d are the temperature (°C), catalyst initial mass (g), and 35% hydrogen peroxide addition rate (g/min). The unit of pressure is bar, and the yield is dimensionless. In both equations, the single factor dosing rate term has opposite sign with catalyst mass and temperature terms, and this indicates that the dosing rate has inverse effect; that is, increasing the dosing rate results in decreased reaction yield and increase of pressure as opposed to the effects that the catalyst and temperature have. For that reason, the interaction terms involving dosing rate (d·m and d·T) are statistically less relevant to pressure and yield response model. The catalyst temperature interaction term (T·m) however, is statistically significant in both models because of the synergistic effects

Figure 12. N-oxide yield at different dosing rates.

response were developed and they are shown in eqs 2 and 3, respectively. Yield = −0.33 + 0.018T + 0.048m − 9.70 × 10−3d − 6.00 × 10−5T 2 − 3.56 × 10−4T ·m

(2)

Table 2. Analysis of Variance for the Final Product Yield Response Regression Modela Source

DF

Model Temperature Catalyst Dosing rate Temperature·Temperature Catalyst·Catalyst Dosing rate·Dosing rate Temperature·Catalyst Temperature·Dosing rate Catalyst·Dosing rate Error Lack-of-Fit Pure Error Total

9 1 1 1 1 1 1 1 1 1 8 3 5 17

Adjusted Sum of Squares 0.061 0.033 0.012 3.6 × 3.5 × 4.0 × 9.2 × 4.1 × 7.6 × 8.7 × 3.7 × 2.2 × 1.5 × 0.064

Adjusted Mean Squares 6.7 × 0.033 0.012 3.6 × 3.5 × 4.0 × 9.2 × 4.1 × 7.6 × 8.7 × 4.6 × 7.4 × 2.9 ×

10−3 10−3 10−4 10−5 10−3 10−4 10−4 10−3 10−3 10−3

10−3

10−3 10−3 10−4 10−5 10−3 10−4 10−4 10−4 10−4 10−4

F-Value

P-Value

Statistical Significance

14.68 72.78 27.08 7.91 7.70 0.87 0.20 9.01 1.66 1.90

4.53 × 10−4 2.74 × 10−5 8.18 × 10−4 0.020 0.020 0.38 0.67 0.02 0.23 0.21

* * * * *

2.54

*

0.17

a

Asterisk (*) indicates that the term is statistically significant. H

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Industrial & Engineering Chemistry Research Table 3. Analysis of Variance for the Reactor Pressure Response Regression Modela Source

DF

Adjusted Sum of Square

Adjusted Mean Square

F-Value

P-Value

Statistical Significance

Model Temperature Catalyst Dosing rate Temperature·Temperature Catalyst·Catalyst Dosing rate·Dosing rate Temperature·Catalyst Temperature·Dosing rate Catalyst·Dosing rate Error Lack-of-Fit Pure Error Total

9 1 1 1 1 1 1 1 1 1 8 3 5 17

788.89 438.72 143.08 36.85 60.34 11.64 0.18 66.97 6.29 23.35 25.45 17.06 8.39 814.35

87.66 438.72 143.08 36.85 60.34 11.64 0.18 66.97 6.29 23.35 3.18 5.69 1.68

27.55 137.90 44.98 11.58 18.97 3.66 0.060 21.05 1.98 7.34

4.39 × 10−5 2.53 × 10−6 1.52 × 10−4 9.3 × 10−3 2.4 × 10−3 0.092 0.82 1.8 × 10−3 0.20 0.027

* * * * *

3.39

* *

0.11

a

Asterisk (*) indicates that the term is statistically significant.

Figure 13. Reactor pressure and N-oxide yield response contour: (a) pressure response at different catalyst amounts and temperatures at 4 g/min; (b) pressure response at different catalyst amounts and dosing rates at 107.5 °C; (c) pressure response at different temperatures and dosing rates with 8 g of catalyst; (d) yield response contour with different catalyst amounts and different temperatures at 4 g/min dosing rate; (e) yield response contour with different catalyst amounts and dosing rates at 95 °C; (f) yield response contour at different temperatures and dosing rates with 8 g of catalyst.

among the catalyst amount and reaction temperature as discussed in the previous section. Thus, increasing the catalyst and temperature together can significantly decrease the final reaction pressure while increasing the N-oxide yield. To visualize the relationship between the input variables and output response, the developed response regression models are plotted in 2D contour and presented in the following section. 3.4.2. Pressure and Yield Response Contour Analysis. The reactor pressure contours are shown in Figure 13(a−c). As

three input variables are involved, the plot was divided into three contours involving the pressure response in terms of catalyst and temperature at 4 g/min dosing rate, catalyst and dosing rate at 107.5 °C, and temperature and dosing rate at 6 g of catalyst. As seen in Figure 13(a), when the dosing rate is fixed at 4 g/min, the reactor pressure is lower at higher catalyst and temperature. As discussed in the single factor analysis, the N-oxidation reaction is favored by high temperature and catalyst amount. Temperature seems to have the greatest I

DOI: 10.1021/acs.iecr.8b03773 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research Table 4. Experimental Validation of Inherently Safer and Efficient Operation Conditions Pressure (bar) Run

Temperature (°C)

Catalyst (g)

dosing rate (g/min)

1a 2a 3b 4b 5b

107.5 130 110 125 117.5

12 8 10 10 5.5

4 4 4 4 2.25

experiment 3.3 5.7 3.6 4.5 4.0

± ± ± ± ±

0.1 0.1 0.4 0.3 0.3

Yield

predictionc 2.9 4.5 4.4 3.9 3.1

± ± ± ± ±

2.7 2.0 2.2 1.8 3.0

experiment 96.7% 97.8% 97.1% 97.5% 97.2%

± ± ± ± ±

2.2% 1.5% 0.7% 0.4% 0.5%

predictionc 99.7% 98.4% 98.3% 99.0% 98.1%

± ± ± ± ±

2.8% 2.1% 2.3% 1.9% 2.7%

a

Experimental results applying new reaction conditions other than those of 18 tests used for model development. bExperimental results obtained from the literature.28 cPrediction error representing 95% confidence interval.

temperatures and catalyst concentrations. The dosing rate, however, shows an adverse effect on the product yield, because as discussed above, at higher temperature selectivity is greatly enhanced, so that decomposition practically occurs only when dosing rate becomes faster than the N-oxidation rate, while at lower temperatures decomposition becomes more competitive and thus, depending on the specific conditions, can occur throughout the reaction to a rate that is proportional to the square of hydrogen peroxide concentration. 3.4.3. Experimental Validation of Inherently Safer and More Efficient Operating Conditions. As demonstrated in the previous section, the inherently safer and more efficient operating conditions were identified through response surface methodology. To validate those operating regions, two experiments were performed in addition to the 18 runs used for model development. The operating conditions of those measurements were selected to lie in the optimal range identified by RSM. They were then compared with model predictions. The results of the comparison are shown in Table 4. Furthermore, three experimental results from past work reported in the literature are also presented in Table 4, where similar measurements were performed in the same calorimeter in Table 4.28 The results show that the developed model is in good agreement with present and past measurements.

impact on the reactor pressure. For instance, when the reactor temperature is as low as 85 °C, even addition of 12 g cannot help maintaining the reactor pressure below 6 bar. On the other hand, at 130 °C, only 4 g of catalyst suffice to keep the reactor pressure below 6 bar. The temperature range between 100 °C to 120 °C can be identified as the catalyst sensitive zone, where the reactor pressure can be greatly reduced below 6 bar by addition of more catalyst. The reactor pressure can be kept below 4 bar in the range of 100 °C to 125 °C if sufficiently high amount of catalyst is used. At higher temperatures water vapor pressure increases exponentially, thus affecting the overall reactor pressure. Figure 13(b) shows the impact of catalyst and dosing rate on the reactor pressure at 107.5 °C. As can be seen high dosing rate and low catalyst amount can result in significantly increased reactor pressure. On the other hand, when the catalyst amount is above 10 g, the reactor pressure becomes insensitive to dosing rate and is maintained below 4 bar. This is because the high catalyst amount significantly favors the Noxidation. Furthermore, when low catalyst amount is employed, the reactor pressure is very sensitive to dosing rate. Higher concentration of hydrogen peroxide significantly increases the side decomposition reaction selectivity under low catalyst amount, because H2O2 decomposition is second order in respect to its concentration, as opposed to N-oxidation, the rate of which is only first order in respect to H 2 O 2 concentration.36 The relationship between temperature and dosing rate at 4 g of catalyst amount (low) is shown in Figure 13(c). The reactor pressure can be significantly reduced from over 22 bar to below 5 bar by increasing temperature and reducing dosing rate. As reported in Pineda-Solano et al., 2011, and in Papadaki and Gao, 2006, high temperature dramatically favors the Noxidation.37,38 As can be seen in the kinetic models of the reaction,26,36 catalyst concentration affects similarly (second order) both reactions. At high temperatures hydrogen peroxide is essentially consumed by the N-oxidation reaction until Noxidation rate becomes almost equal to dosing rate. As such, the decomposition reaction has a measurable effect only after that point. At lower temperatures, where selectivity toward Noxidation drops, dosing has an effect throughout hydrogen peroxide addition time. The yield response contours in terms of three operating variables are presented in Figure 13(d), (e), and (f). As can be seen in Figure 13, the regions of low reactor pressure and high yield are highly overlapping. This is because the reactor overpressure is mainly generated by decomposition of hydrogen peroxide. Low reaction yield not only compromises the reaction efficiency but also increases the risk of reactor overpressure. The reaction yield significantly depends on reaction selectivity which as discussed earlier is favored by high

4. CONCLUSION The impact of catalyst, hydrogen peroxide dosing rate, and reactor temperature on the final reaction pressure and product yield of isothermal 3-methylpyridine N-oxidation reaction was examined using response surface methodology. Under the conditions of the measurements, the maximum product yield of 0.993 was found when 12 g of catalyst was used at 130 °C reaction temperature with 4 g/min dosing rate. At high temperatures, hydrogen peroxide decomposition is practically totally suppressed until more than 90% of the alkylpyridine is consumed, while at low temperatures it is significant throughout the reaction. The impact of catalyst amount and dosing rate were more significant at lower temperatures. The use of response surface methodology was proved to be useful for revealing ranges of intensified reaction conditions where optimal operation of batch/semibatch reaction is most likely to lie.



AUTHOR INFORMATION

Corresponding Author

*Benjamin Wilhite, phone +1 (979)-845-0406, e-mail [email protected]. ORCID

Yanyan Huang: 0000-0002-2930-6471 Benjamin A. Wilhite: 0000-0003-2595-2094 J

DOI: 10.1021/acs.iecr.8b03773 Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX

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Industrial & Engineering Chemistry Research

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M. Sam Mannan: 0000-0002-4058-2119 Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS This research was sponsored by the Mary Kay O’Connor Process Safety Center, Texas A&M University. This work is dedicated to the memory of process safety and chemical engineering pioneer, Dr. M. Sam Mannan.



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L

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