Kinetic Model For Oxidative Coupling Research Articles

High-Throughput Experiments and Kinetic Modeling of Oxidative Coupling of Methane over La2O3/CeO2 Catalyst

Summary A reliable data set covering a parametric space of process conditions is essential for realizing catalyst informatics. A high-throughput screening (HTS) instrument was used to obtain a parametric data set to develop a detailed reaction microkinetic model for the oxidative coupling of methane (OCM) over a La2O3/CeO2 catalyst. The model was combined with well-validated gas-phase kinetics to describe the interactions between homogeneous and heterogeneous reaction chemistry. Methane and oxygen conversions and selectivities of ethylene, ethane, carbon monoxide, and carbon dioxide were measured experimentally in the temperature range of 500 to 800°C, CH4/O2 ratio between 3 and 13, and pressure between 1 bar and 10 bar. The proposed reaction network consists of 52 irreversible elementary steps describing catalytic reactions between 11 surface species and 123 reversible steps describing the contribution of gas phase between 25 species. A packed-bed reactor model was developed based on the dimensions of the experimental setup and catalyst characterization results to account for homogeneous-heterogeneous interactions. The proposed mechanism was tested and validated over a wide range of operating conditions and showed a reasonable fit with an average difference of less than 5% compared to experimentally measured methane conversion and selectivities of ethylene and ethane. Rate of production (ROP) and species sensitivity analyses were performed to identify the main reaction pathways and highlight the important reactions in the OCM.

A chemistry‐inspired neural network kinetic model for oxidative coupling of methane from high‐throughput data

AbstractA neural network kinetic model is developed for oxidative coupling of methane (OCM). The model is designed in cognizance of the underlying chemistry and associated reactor balance equations and trained on publicly available high throughput experimental data spanning a large material space of supported mixed metal oxide catalysts. The resultant model is then used to evaluate one of the most popular catalysts for OCM, viz. MnNa2WO4/SiO2, to understand the reaction kinetics and sensitivity of the catalyst to changing different components of the catalyst. The predicted activation barrier for methane conversion is 251 kJ mol−1, and the rate . Furthermore, the reference catalyst is local optimal as small changes to its composition, for example, by changing the individual metals or the support, did not improve (or often substantially reduced) methane consumption or the C2 formation rate.

Kinetic modeling of oxidative coupling of methane over Li/MgO catalyst by genetic algorithm

A comprehensive kinetic model for oxidative coupling of methane (OCM) on Li/MgO catalyst was developed based on a fixed bed cylindrical reactor data. The methane conversion and ethylene, ethane, carbon monoxide, carbon dioxide, propane and propylene selectivity were obtained in a wide range of operating conditions including 710 < T < 850 °C, 1 < CH4/O2 < 4 and gas hourly space velocity (GHSV) between 35 and 150 h−1 at P = 760 mmHg. A 16-step reaction scheme defined to the description of a reaction network that considers both catalytic and gas-phase as well as primary and consecutive reaction steps to predict the performance of the OCM. The kinetic rates involved Langmuir–Hinshelwood–Hougen–Watson type rate equations, which considered the inhibiting effect of carbon dioxide and oxygen on oxidation reactions and power-law rate equations for remained reactions. The kinetic rate parameters were estimated using genetic algorithm optimization method. Comparing the experimental and model predicted data showed that presented model has a reasonable fit between the experimental data and the predicted values with average absolute relative deviation of ±9.9%.

Kinetic study of oxidative coupling of methane over Mn and/or W promoted Na 2SO 4/SiO 2 catalysts

A comprehensive kinetic model for oxidative coupling of methane (OCM) over Mn and/or W promoted Na 2SO 4/SiO 2 catalysts was developed based on a micro-catalytic reactor data. The methane conversion and ethylene, ethane, carbon monoxide and carbon dioxide selectivities were obtained in a wide operating condition range of 750-825 °C, CH 4/O 2 = 2.5-10 and contact time = 267-472 kg·s·m −3. Reaction networks of six models with different rate equation types were compared together. The kinetic rate parameters of each reaction network were estimated using linear regression or genetic algorithm optimization method (GA). A reaction network suggested by Stansch et al. for OCM was found to be the best one and was further used in this work. The suggested model could predict the experimental results of OCM reaction within a deviation range of ±20%.

Kinetic modeling of oxidative coupling of methane over Mn/Na 2WO 4/SiO 2 catalyst

A comprehensive kinetic model for oxidative coupling of methane (OCM) on Mn/Na 2WO 4/SiO 2 catalyst was developed based on a microcatalytic reactor data. The methane conversion and ethylene, ethane, carbon monoxide and carbon dioxide selectivities were obtained in a wide range of operating conditions including 750 < T < 875 °C, 4 < CH 4/O 2 < 7.5 and space time between 30 and 160 kg · s/m 3 at P = 657 mmHg. The reaction networks of five kinetic models with appropriate rate equation type were compared together. The kinetics rates parameters of each reaction network were estimated using genetic algorithm optimization method. After comparing the reaction networks, the reaction network presented by Stansch et al. was found to best represent the OCM reaction network and was further used in this work. This kinetic network considers both catalytic and gas-phase as well as primary and consecutive reaction steps to predict the performance of the OCM. Comparing the experimental and predicted data showed that presented model has a reasonable fit between the experimental data and the predicted values with average absolute relative deviation of ± 9.1%.

Application of sensitivity analysis to the reduction of a complex kinetic model for the homogeneous oxidative coupling of methane

In this paper, we report the reduction of a complex kinetic model for the oxidative coupling of methane in the gas phase, consisting of 164 elementary reactions and 28 species. The simplified kinetic model contains a total of 31 important reactions, involving 20 species. Based on the common sensitivity analysis, a new algorithm is presented. This can be characterized as a combination of a step-by-step reduction procedure, according to the magnitude of a modified overall sensitivity coefficient, together with a ‘reasonableness’ check of the reduced kinetic model, using the incidence matrix. By comparing the corresponding simulation results of the complete and the reduced model, it can be demonstrated that this algorithm is successful and efficient in developing a simplified kinetic model, valid for a sufficiently wide range of operating conditions.

A mechanistic kinetic model for oxidative coupling of methane over Li/MgO catalysts

A detailed mechanistic model has been developed to describe the methane oxidative coupling network over Li/MgO catalysts. The mechanism assumes that methane and other hydrocarbon species react directly from the gas phase with surface active oxygen centres (Eley- Rideal representation). The surface network comprises parallel and sequential elementary steps describing the following chemical processes: 1] hydrocarbon dehydrogenation, 2] non-selective partial oxidation of hydrocarbon species, 3] catalyst dehydration, 4] gaseous oxygen adsorption and active centre regeneration, 5] catalyst poisoning by carbon oxides, and 6] carbon monoxide oxidation. The surface kinetic parameters were estimated on the basis of scaling arguments and published experimental data. The surface network is combined with a homogeneous methane oxidation mechanism thus resulting in a detailed kinetic model which can account for the observed conversion levels and hydrocarbon product distributions.