Lumped Kinetic Model Research Articles

A lumped kinetic model and experimental investigation of poly(ethylene terephthalate) condensed-phase pyrolysis

In a circular economy perspective, plastic waste (PW) is a valuable source of chemicals and energy vectors. Understanding the effect of poly(ethylene terephthalate) (PET) in thermochemical valorisation of complex and contaminated PW mixtures requires definition of suitable kinetic models. This work proposes a condensed-phase semi-detailed kinetic model for PET pyrolysis based on a consolidated functional group approach already validated for other polymers. The reaction network is built considering studies on thermal degradation of PET, model compounds, and small gas-phase esters. Reaction pathways proposed in the scientific literature are critically assessed through analogy with high accuracy gas-phase calculation and are complemented by new proposed pathways. The resulting model couples molecular and radical mechanism and consists of 85 gas and liquid species with 700 liquid-phase reactions, being suitable for CFD simulations of PW pyrolysis upon further reduction. This work also presents new experimental data including TG analysis coupled with GC × GC speciation measurements and elemental characterization of the solid residue. The model is validated by comparison with the new experimental data and a comprehensive set of literature data in terms of characteristic degradation times and detailed product yields. The present work expands the relevant data available for chemistry models development and extends the CRECK kinetic framework for thermochemical recycling of PW mixtures. The proposed kinetic model is attached as Supplementary material and freely available as an open GitHub repository.

Mechanistic modeling of minute virus of mice surrogate removal by anion exchange chromatography in micro scale

Biopharmaceutical products are often produced in Chinese hamster ovary (CHO) cell cultures that are vulnerable to virus infections. Therefore, it is a regulatory requirement that downstream purification steps for biopharmaceuticals can remove viruses from feedstocks. Anion exchange chromatography (AEX) is one of the downstream unit operations that is most frequently used for this purpose and claimed for its capability to remove viruses. However, the impact of various process parameters on virus removal by AEX is still not fully understood. Mechanistic modeling could be a promising way to approach this gap, as these models require comparatively few experiments for calibration. This makes them a valuable tool to improve understanding of viral clearance, especially since virus spiking studies are costly and time consuming.In this study, we present how the virus clearance of a MVM mock virus particle by Q Sepharose FF resin can be described by mechanistic modeling. A lumped kinetic model was combined with a steric mass action model and calibrated at micro scale using three linear gradient experiments and an incremental step elution gradient. The model was subsequently verified for its capability to predict the effect of different sodium chloride concentrations, as well as residence times, on virus clearance and was in good agreement with the LRVs of the verification runs. Overall, models like this could enhance the mechanistic understanding of viral clearance mechanisms and thereby contribute to the development of more efficient and safer biopharmaceutical downstream processes.

Unravelling the complexity of hemicellulose pyrolysis: Quantitative and detailed product speciation for xylan and glucomannan in TGA and fixed bed reactor

For the first time, the complete characterization of the pyrolysis of key biomass components – xylan (representative of pentose-based hardwood hemicellulose) and glucomannan (representative of hexose-based softwood hemicellulose) – is herein obtained by applying a novel methodology based on TGA (thermogravimetric analysis), previously developed for cellulose. Data on devolatilization rates, onset temperatures and detailed quantification of the mass yield of ∼ 50 products in the gas, liquid, solid phase were achieved simultaneously, with closure of mass balance, thus providing unique kinetic information. Pyrolysis tests were also carried out in a fixed bed reactor to explore larger scales and validate the TGA-based approach. At both scales, combinations of different analytical techniques (online MS, offline GC-FID/MS, Karl Fischer titration) and sampling protocols (cold condenser, sorbent traps, vapour syringes, gas bags) were tuned to achieve closure of mass balances and rigorous product speciation.While the pyrolysis of cellulose – chosen as reference system − maximized the bio-oil production (mostly levoglucosan), the pyrolysis of xylan resulted into an even distribution among solid, liquid and gas phases, with condensable oxygenates spanning homogeneously in the C1-C9 range. Interestingly, glucomannan showed an intermediate behaviour between cellulose and xylan, mirroring its intermediate chemical structure. Raman and oxidation analyses on the collected char samples showed that the solid residuals from hemicelluloses were less ordered and richer in ashes than those from cellulose.The predictions of recent lumped kinetic models were used to benchmark the new datasets against the prior art on hemicellulose pyrolysis; the richness and comprehensiveness of the new information clearly emerge and pave the pathway to the de-bottlenecking of kinetic modelling.

Gasoline production by oligomerization of 1-butene at low pressure: Kinetic model and reactor simulation

A five lump kinetic model (C4=, C8=, C12=, C1-C4 and C5-C12) has been established for 1-butene (C4=) oligomerization at low pressure (1.5 bar) and 275 °C on an HZSM-5 zeolite catalyst agglomerated in a γ-Al2O3 mesoporous matrix. The kinetic parameters have been calculated based on the results obtained in a packed-bed reactor for different concentrations of 1-butene in the feed (with N2 as diluent) and different values of space time (0.5–9.5 gcatalyst h molC-1). The model quantifies the evolution with time on stream of the concentrations of the lumps, considering the selective deactivation of the catalyst for the oligomerization, cracking and pool of secondary reactions. Furthermore, it allows to calculate the remnant activity of the catalyst in the pseudo-steady state (>5h on stream) for the different reaction groups, as well as the corresponding product distribution. The kinetic model has been used in the simulation of the packed-bed reactor to study the effect of space time and 1-butene partial pressure variables. At the conditions range studied experimentally, 39.4 % gasoline yield (C5-C12 fraction, mainly composed of olefins) and a 1-butene conversion of 45 % are achieved in the pseudo-steady state of the catalyst, at a space time of 9.5 gcatalyst h molC-1 and a partial pressure of 1-butene of 0.8 bar. Additionally, for values exceeding those studied experimentally, the model predicts at the pseudo-steady state a gasoline yield of 60 % at a space time of 30 gcatalyst h molC-1 and a partial pressure of 1-butene of ∼ 0.5 bar.

Combining experiment and theory to study the mechanism of lignin supercritical water gasification

Supercritical water gasification (SCWG) presents notable advantages in biomass energy utilization. The exploration of the reaction mechanism of lignin in supercritical water holds significance in advancing and refining the biomass SCWG process. In this work, syringol was selected as a lignin model compound to study the SCWG mechanism of lignin through a combination of molecular simulation and experiments. The results show that the ether bond is rapidly cleaved in the reaction initial stages. While the phenolics dearomatization has a slower rate and temperature exerts a considerable influence on the dearomatization process. Four degradation pathways are proposed based on the molecular simulations. In the context of the dearomatization reaction, DFT calculations are performed to determine the energy barriers associated with each of the four pathways. Notably, the energy barrier for the most favorable pathway is found to be 291.96 kJ/mol. A lumped kinetic model is constructed based on the reaction pathway, and the reliability of the model is verified by both experiments and DFT calculations. This paper offers valuable assistance in optimizing reaction pathways.

The effect of the unsaturation degree on the gas-phase autoignition of methyl oleate and methyl linoleate: Experimental and modeling study

As the product of transesterification between various oils and alcohols, biodiesel exhibits characteristics of renewability and a wide range of raw materials. The ignition delay times (IDTs) of methyl oleate (MEOLE) and methyl linoleate (MLINO), the primary constituents of biodiesels, were measured in a heated rapid compression machine (RCM) to investigate the impact of CC double bond on the reactivity and autoignition characteristics. The experiment was conducted under two pressures of 8 bar and 10 bar at an equivalence ratio of 0.3–0.8 and a temperature range of 800–1000 K. The qualitative investigation unveiled the influence of compressed pressure, equivalence ratio, and oxygen mole fraction on the IDT of MEOLE and MLINO under varying compressed temperatures. Besides, a comparison of the IDTs for two fuels with different unsaturation degrees under identical conditions revealed that MEOLE exhibited greater reactivity at low temperatures compared to MLINO, while the increase in unsaturation degree can moderate and enhance reactivity at high temperatures. Moreover, three kinetic models in the literature were validated against the newly measured IDTs. The results indicate that the detailed lumped kinetic model exhibits better predictive capacity compared to other models, but it still underestimates the reactivity of MEOLE and MLINO within the investigated temperature range. Subsequently, the detailed kinetic model was optimized based on sensitivity analysis, resulting in excellent agreement between the predicted values of the optimized model and experimental data. Furthermore, accurate predictions were made regarding the relative reactivity changes of MEOLE and MLINO with temperature. Finally, different types of experimental data in the literature were employed to validate the optimized model, yielding satisfactory results.

Dual-cycle-based lumped kinetic model for methanol-to-aromatics (MTA) reaction over H-ZSM-5 zeolites of different Si/Al ratio

In this work we developed a 7-lump kinetic model for the methanol-to-aromatics (MTA) reaction based on the dual-cycle mechanism, with consideration of deactivation of the catalyst by coke formation and applicable to H-ZSM-5 zeolite-based catalysts of different acidity. The model developed is suitable to be implemented at an industrial scale, as the intrinsic kinetic aspect fits the experimental data in a wide range of operating conditions. Moreover, the model is validated for two catalysts (prepared from two H-ZSM-5 zeolites of Si/Al ratio = 15 and 40), and considers a combined formation of coke from both unreacted oxygenates and reaction products (specifically, aromatics and light olefins). The final model comprises 10 reaction steps, and considers the effect of water co-feeding. The kinetic parameters of best fitting are obtained in the simultaneous fitting of the zero time and the deactivation kinetics. We compared the kinetic parameters of the best-fitting model for the two catalysts and related the differences obtained between both sets of parameters to catalyst properties.

Effect of feedstock properties on the kinetics of hydrocracking of heavy oils

The ability to predict changes in selectivity and quality of products of catalytic hydrocracking reaction is essential for the performance and economics of the process due to the variation in properties of the fractions derived from heavy crude oils. The influence of different hydrocarbon feedstocks on hydrocracking reaction kinetics was analyzed using detailed experimental data reported in the literature. A six–lump kinetic model in the presence and absence of diverse catalysts was used. For the predictions of the pseudocomponent yields using the estimated kinetic parameters, global average absolute error values less than 4.3 % concerning the experimental data were obtained. Clear trends are observed between the values of some reaction rate coefficients and properties of the diverse feedstocks. The analysis of the effect of feedstock properties on the kinetic parameters indicated that streams with high API and low H/C ratio have higher global reaction rate coefficients of vacuum residue conversion, observing an increase of up to three–fold the coefficient values concerning the rise of asphaltene content. The contents of carbon residue and sulfur influence the performance of certain reaction pathways and the production of coke for the different feedstocks studied and types of catalysts.

Coupling chemical lumping to data-driven optimization for the kinetic modeling of dimethoxymethane (DMM) combustion

The kinetic mechanisms describing the combustion of longer-chain fuels often have limited applicability due to the high number of species involved in their oxidation and decomposition paths. This work proposes a combined methodology for developing compact but accurate kinetic mechanisms of these fuels and applies it to dimethoxymethane (DMM), or oxymethylene ether 1 (OME1). An automatic chemical lumping procedure, performed by grouping structural isomers into pseudospecies, was proposed and applied to a detailed kinetic model of DMM pyrolysis and oxidation, built from state-of-the-art kinetic sub-models. Such a methodology proved particularly efficient in delivering a compact kinetic mechanism, requiring only 11 species instead of 35 to describe DMM sub-chemistry. The obtained lumped kinetic model was then improved through a data-driven optimization procedure, targeting data artificially generated by the reference detailed mechanism. The optimization was performed on the physically-constrained parameters of the modified-Arrhenius rate constants of the controlling reaction steps, identified via local sensitivity analyses. The dissimilarities between the predictions of the detailed and lumped models were minimized using a Curve Matching objective function for a comprehensive and quantitative characterization. Above all, the optimized mechanism was found to behave comparably to the starting detailed one, throughout most of the operating space and target properties (ignition delay times in shock tubes, laminar flame speeds, and speciations in stirred and flow reactors). The successful application of the proposed methodology to the DMM chemistry paves the way for its extensive use in the kinetic modeling of longer OMEs as well as heavier fuels, for which the computational advantages are expected to be even higher.

Modeling and simulation of microwave assisted catalytic pyrolysis system of waste plastics polymer for fuel production

Pyrolysis is a promising method of chemically recycling plastic waste, as it allows for the recovery of both energy and materials. In this work, a comprehensive mathematical model has been developed to predict the pyrolysis of plastic wastes over ZSM-5 catalyst in microwave-assisted pyrolysis (MAP) system for fuel production. To conduct a transient numerical analysis of the underlying processes, a lumped kinetic model that takes into account three lumped pyrolysis products (olefins, paraffins, and aromatics) is coupled with the equations that govern the microwave field, heat transfer, mass transfer, and fluid flow (Darcy's law). The distributions of electric field, temperature, and pyrolysis products within MAP are presented. The study investigated the effects of several factors on the rate of production and consumption in the pyrolysis reactions of a waste plastic mixture when using MAP. These factors include the microwave power input, the inlet velocity of the fluidizing gas, as well as the mass and particle size of the catalyst used. Increasing the input power leads to a higher intensity of the electric field, which causes a greater increase in temperature within the same time frame. The mass and particle size of the catalyst used also have a significant impact on the yield of olefins, paraffins, and aromatics. Reducing the particle size of the catalyst generally increases the reaction rate, but particle sizes smaller than 50 μm are not ideal for fluidization due to increased intermolecular forces. Increasing the inlet velocity of the fluidizing gas may result in an incomplete consumption of intermediates and a low yield of products. All in all, The MAP system is a highly efficient and effective design for using plastic waste as a source of energy, due to its superior energy efficiency and lower processing temperature compared to traditional fluidized-bed reactors.

4-lump kinetic model for non-catalytic oil shale upgrading at sub- and supercritical water conditions

The kinetics of non-catalytic oil shale conversion at sub- and supercritical water conditions was studied. All experiments were carried out in a batch reactor at 300–400 °C and 1–48 h. A four-lump reaction scheme is proposed, where oil shale produces synthetic oil, gas and coke, and some other reactions take place between products (coke to gas, synthetic oil to gas and synthetic oil to coke). Low average absolute error (<6.5%) was obtained, which corroborates the accuracy of estimated parameters of the developed kinetic model. The reaction rate was found to depend more on synthetic oil yield than on oil shale conversion according to the calculated reaction orders. The sensitivity analysis of the kinetic parameters showed that all values of the obtained reaction rate coefficients are the optimal. At temperatures near the critical point of water (350 and 400 °C), lowest values for asphaltenes and highest light fractions contents in synthetic oil were obtained.

Experimental and CFD simulation of glyphosate removal by a filter-press electrocoagulation reactor

The present communication proposes a lumped kinetic and phenomenological model for glyphosate removal in synthetic agro-industrial wastewater using an electrocoagulation process (EC). A traditional filter press-cell electrochemical reactor is used for the EC experimental process. The outcomes of the current density, electrode material, and electrolysis process time were analyzed. The experimental results evidence a better removal performance for the aluminum than the carbon steel, and stationary removal conditions were reached at 40 min with a removal efficiency > 40% considering an input flow of 2 L min−1 and operational cost of 0.172 USD m−3 at 7.5 mA cm−2. The XRD analysis evidenced the interaction between the aluminum ion and the pesticide. The residual aluminum in the supernatant was < 10 mg L−1 at stationary removal conditions. The species distribution inside the reactor is described by the theoretical analysis, which takes into account the simultaneous solution of the Reynolds averaged Navier-Stokes (RANS) and kinetic-based mass conservation equation. Under full electrokinetic control (secondary current distribution), the electrode kinetics characterizing the flux generation of Al3+ on the anode is also taken into consideration. The model proposed here can explain the experimental COD removal attributed to the glyphosate concentration as a function of the aluminum dose due to the applied current density. The model is fitted to experimental data to calculate the kinetic and transport parameters.

Physics-informed neural networks to solve lumped kinetic model for chromatography process

Numerical method is widely used for solving the mechanistic models of chromatography process, but it is time-consuming and hard to response in real-time. Physics-informed neural network (PINN) as an emerging technology combines the structure of neural network with physics laws, and is getting noticed for solving physics problems with a balanced accuracy and calculation speed. In this research, a proof-of-concept study was carried out to apply PINN to chromatography process simulation. The PINN model structure was designed for the lumped kinetic model (LKM) with all LKM parameters. The PINN structure, training data and model complexity were optimized, and an optimal mode was obtained by adopting an in-series structure with a nonuniform training data set focusing on the breakthrough transition region. A PINN for LKM (LKM-PINN) consisting of four neural networks, 12 layers and 606 neurons was then used for the simulation of breakthrough curves of chromatography processes. The LKM parameters were estimated with two breakthrough curves and used to infer the breakthrough curves at different residence times, loading concentrations and column sizes. The results were comparable to that obtained with numerical methods. With the same raw data and constraints, the average fitting error for LKM-PINN model was 0.075, which was 0.081 for numerical method. With the same initial guess, the LKM-PINN model took 160 s to complete the fitting, while the numerical method took 7 to 72 min, depending on the fitting settings. The fitting speed of LKM-PINN model was further improved to 30 s with random initial guess. Thus, the LKM-PINN model developed in this study is capable to be applied to real-time simulation for digital twin.

Degradative solvent extraction of cyanobacteria: From reaction kinetics to potential organic matter evolution mechanism

This study proposed a new continuous lumped reaction kinetics model to accurately reveal the control mechanism of cyanobacteria at each stage of degradative solvent extraction and discussed the potential evolution mechanism of organic matter. Results showed that degradation solvent extraction successfully separated nitrogen and phosphorus from cyanobacteria. The solute has high carbon and volatile contents, is almost ash-free, and forms a phosphorus-rich residue. The lowest fitting degree of the continuous lumped reaction model kinetics was 94.5%, suggesting that this model worked well. The depolymerization of the residue dominated between 200 and 350 °C, whereas solute decomposition dominated at 400 °C. Nitrogen-containing compounds, which originate from protein decarboxylation or deamination to generate amides, are the main components of the solute, and amino acids react with reducing sugars to generate nitrogen heterocyclic compounds, which are useful for preparing nitrogen-containing chemicals.

Treatment of Effluent Containing p-Cresol through an Advanced Oxidation Process in a Batch Reactor: Kinetic Optimization

The present research is related to the study of p-cresol oxidation reaction in aqueous phase. Firstly, the conventional advanced oxidation process (AOP) in a lab-scale batch reactor was used, seeking to identify the most impacting process variables and then to propose an optimization approach for ensuring the complete p-cresol degradation and the highest total organic carbon (TOC) conversion. In the AOP with the use of hydrogen peroxide as the oxidizing agent, the oxidation reaction was optimized with the aid of a factorial design, and a maximum TOC conversion of 63% was obtained. The Lumped Kinetic Model (LKM) was used to describe the profile of residual TOC concentration due to chemical species, which were categorized into two groups (refractory and non-refractory compounds). The model was able to satisfactorily describe the profile of the residual fractions of these two classes of organic compounds and allowed estimating the related kinetic constants (k) at two different temperatures, namely (a) 3.19 × 10−1 and 2.82 × 10−3 min−1 for non-refractory and refractory compounds at 80 °C and (b) 4.73 × 10−1 and 5.09 × 10−3 min−1 for the same compound classes at 90 °C, while the activation energy (Ea) of the process was 42.02 and 62.09 kJ mol−1, respectively. The kinetic modeling of organic pollutants oxidation in liquid effluents would allow to perform in situ seawater treatment on vertical reactors installed in offshore platforms and to properly release treated water into the oceans. In this way, ocean contamination caused by the exploration on offshore platforms of oil and natural gas, the main energy sources and vectors in the current world, may be remarkably reduced, thus favoring a more eco-friendly energy production.

Downscaling Industrial-Scale Syngas Fermentation to Simulate Frequent and Irregular Dissolved Gas Concentration Shocks.

In large-scale syngas fermentation, strong gradients in dissolved gas (CO, H2) concentrations are very likely to occur due to locally varying mass transfer and convection rates. Using Euler-Lagrangian CFD simulations, we analyzed these gradients in an industrial-scale external-loop gas-lift reactor (EL-GLR) for a wide range of biomass concentrations, considering CO inhibition for both CO and H2 uptake. Lifeline analyses showed that micro-organisms are likely to experience frequent (5 to 30 s) oscillations in dissolved gas concentrations with one order of magnitude. From the lifeline analyses, we developed a conceptual scale-down simulator (stirred-tank reactor with varying stirrer speed) to replicate industrial-scale environmental fluctuations at bench scale. The configuration of the scale-down simulator can be adjusted to match a broad range of environmental fluctuations. Our results suggest a preference for industrial operation at high biomass concentrations, as this would strongly reduce inhibitory effects, provide operational flexibility and enhance the product yield. The peaks in dissolved gas concentration were hypothesized to increase the syngas-to-ethanol yield due to the fast uptake mechanisms in C. autoethanogenum. The proposed scale-down simulator can be used to validate such results and to obtain data for parametrizing lumped kinetic metabolic models that describe such short-term responses.

Numerical Simulation of Nonlinear and Non-Isothermal Liquid Chromatography for Studying Thermal Variations in Columns Packed with Core-Shell Particles

A high-resolution flux-limiting semi-discrete finite volume scheme (HR-FVS) is applied in this study to numerically approximate the nonlinear and non-isothermal flow of one-dimensional lumped kinetic model (1D-LKM), for a fixed-bed column loaded with core-shell particles. The developed model comprise a system of convection-dominated partial differential for mass and energy balances in the mobile phases coupled with differential equation and algebraic equation in the stationary phase. The solution of the model equations is obtained by utilizing a HR-FVS, the scheme has second-order accuracy even on the grid coarse and its explicit nature has the potential to resolve the arisen sharp discontinuities in the solution profiles. A second-order total variation diminishing (TVD) Runge-Kutta technique is used to solve the system of ODEs in time. Several forms of a single-solute mixture are produced to investigate the influences of the fractions of core radius on thermal waves and concentration fronts. Moreover, a particular criterion is introduced for analyzing the performance of the underlying process and to identify the optimal parameter values of the fraction of core radius.

Discontinuous Galerkin finite element scheme for solving non-linear lumped kinetic model of non-isothermal reactive liquid chromatography

Discontinuous Galerkin finite element scheme for solving non-linear lumped kinetic model of non-isothermal reactive liquid chromatography

Conversion of light cycle oil to benzene and alkylated monoaromatics over monometallic and bimetallic CoMo catalysts in the presence of hydrogen donor

The conversion of diaromatics and triaromatics present in light cycle oil (LCO) to monoaromatics such as benzene, toluene, and xylene (BTX) is studied under fluid catalytic cracking conditions over zeolite-based monometallic (Co, Mo) and bimetallic (CoMo) bifunctional catalysts. Instead of H2, n-hexadecane (n-HD) is used as the hydrogen donor source at atmospheric pressure, which results in a high yield of the desired products and low coke formation. Additionally, n-HD undergoes cyclization, dehydroaromatization, and cracking as well. The total monoaromatics and BTX yield for various feed compositions follows the order: CoMo/Beta > CoMo/Y > Mo/Beta > Co/Beta > Mo/Y > Co/Y > Beta > Y, with CoMo/Beta resulting in 1-Methylnaphthalene conversion and monoaromatics yield of 84.3 % and 43.9 %, respectively. The monoaromatics and BTX yield over various catalysts is correlated to the coke formation, which is the least over bimetallic catalysts. The presence of rod-type CoMoO4 particles is detected on the bimetallic catalysts, and is supported by XRD, H2-TPR, and Raman analysis. For various feeds and catalysts, the cracking of triaromatics is fast, and the yield of monoaromatics is primarily dependent on the catalytic activity towards the cracking of diaromatics. An inverse correlation between the selectivity for 2-ring monoaromatics and BTX shows the formation of 2-ring monoaromatics as intermediates. Various diaromatic compounds with similar reactivity are identified, which could be used for the development of a lumped kinetic model. Based on a detailed product characterization, reaction pathways for the conversion of 1-Methylnapthalene and anthracene are proposed.

Cumene Hydroperoxide-Induced Epoxidation of Styrene Using Cu2O and PbO as Catalysts

Styrene oxide (STOX), produced by epoxidation of styrene, is a pivotal building block in perfumery chemical and cosmeceutical industries. Catalytic performances of commercially available cuprous oxide (Cu2O) and lead oxide (PbO) are tested for epoxidation of styrene for selective production of styrene oxide (STOX). Cumene hydroperoxide (CHP) is used as the oxygen-inducing reagent in this study. Parametric study by altering the operating conditions indicates that lower temperature and lesser styrene in the feed aid styrene-based STOX selectivity, whereas there exists no significant effect of the catalyst loading on product selectivity. A maximum of ∼42.5% (∼45% STOX selectivity at ∼95% conversion of styrene) and ∼45% (∼50% STOX selectivity at ∼90% conversion of styrene) product yields have been recorded within 6 h of batch operation for Cu2O and PbO, respectively. Detailed deactivation study shows that the loss of catalyst activity upon reuse can be attributed to the combined effect of leaching of active sites and oxidation of the metal oxide catalyst on account of the oxidative nature of the reaction system. A suitable lumped kinetic model is proposed, which satisfactorily explains the trends in product yield and by/coproduct formation. Kinetic parameters are estimated by nonlinear regression along with a 95% confidence interval. The studies presented in this article can be considered useful for designing a technoeconomically feasible hydroperoxide-based route for the production of STOX as an alternative to the conventional chlorohydrin-based process.