Presenting a new kinetic model for methanol to light olefins reactions over a hierarchical SAPO-34 catalyst using the Langmuir-Hinshelwood-Hougen-Watson mechanism

Urease production using corn steep liquor as a low-cost nutrient source by Sporosarcina pasteurii: biocementation and process optimization via artificial intelligence approaches

To commercialize the biocementation through microbial induced carbonate precipitation (MICP), the current study aimed at replacing the costly standard nutrient medium with corn steep liquor (CSL), an inexpensive bio-industrial by-product, on the production of urease enzyme by Sporosarcina pasteurii (PTC 1845). Multiple linear regression (MLR) in linear and quadratic forms, adaptive neuro-fuzzy inference system (ANFIS), and genetic programming (GP) were used for modeling of process based on the experimental data for improving the urease activity (UA). In these models, CSL concentration, urea concentration, nickel supplementation, and incubation time as independent variables and UA as target function were considered. The results of modeling showed that the GP model had the best performance to predict the extent of urease, compared to other ones. The GP model had higher R² as well as lower RSME in comparison with the models derived from ANFIS and MLR. Under the optimum conditions optimized by GP method, the maximum UA value of 3.6 Mm min^-1 was also obtained for 5%v/v CSL concentration, 4.5 g L^-1 urea concentration, 0 μM nickel supplementation, and 60 h incubation time. A good agreement between the outputs of GP model for the optimal UA and experimental result was obtained. Finally, a series of laboratory experiments were undertaken to evaluate the influence of biological cementation on the strengthening behavior of treated soil. The maximum shear stress improvement between bio-treated and untreated samples was 292% under normal stress of 55.5 kN as a result of an increase in interparticle cohesion parameters.

Presenting a Four-Lump Dynamic Kinetic Model for Methanol to Light Olefins Process Over the Hierarchical SAPO-34 Catalyst Using Power Law Models

OBJECTIVES

A four-lump dynamic kinetic model on the hierarchical SAPO-34 catalyst in the methanol to light olefins (MTO) process has been presented using the power law models. Since decreased catalyst activity in the MTO process is common, for the applicability of the proposed model, the function of catalyst activity was computed as a function of the coke percentage deposited on the catalyst.

MATERIALS AND METHODS

The reactant and products were divided into four lumps, including methanol and dimethyl ether (DME), light olefins (ethylene and propylene), light paraffin (methane, ethane, and propane) and heavier hydrocarbons from C4. The one-dimensional ideal plug reactor was used for the simulation of the MTO reactor. The kinetic parameters and the catalyst activity function were predicted using the particle swarm optimization (PSO) algorithm.

RESULTS

The comparison of product distribution in the experimental model and the results of the kinetic model indicated the high accuracy of the presented model. The effect of operational parameters such as temperature and weight hourly space velocity (WHSV) on the mole percent of light olefins was investigated using the proposed kinetic model. The optimized value of temperature and WHSV to reach the maximum yield of light olefins was respectively 460 ˚C and 4.2 h^-1.

CONCLUSION

The passive kinetic coefficients were estimated in the reaction rate constant and catalyst activity function with the help of the PSO optimization algorithm. The mole fraction of different products and the reactant arising from modeling at the reactor outlet was compared with experimental results, which indicated the high accuracy of the presented kinetic model. The results also revealed that the selection of high and low temperatures and WHSV decreases the yield of light olefins and the lifetime of the catalyst.

Positive Role of Synthesis Method and Hard Template on the Catalytic Performance of SAPO-34 in Methanol to Olefin Reaction

In the present study, SAPO-34 particles were synthesized using hydrothermal (HT) and dry gel (DG) conversion methods in the presence of diethyl amine (DEA) as an organic structure directing agent (SDA). Carbon nanotubes (CNT) were used as a hard template in the synthesis procedure to introduce transport pores into the structures of the synthesized samples. The synthesized samples were characterized with different methods to reveal the effects of synthesis method and using hard template on their structure and catalytic performance in methanol to olefin reaction (MTO). DG conversion method results in smaller particle size in comparison with hydrothermal method, resulting in enhancing catalytic performance. On the other side, using CNT in the synthesis procedure with DG method results in more reduction in particle size and formation of hierarchical structure, which drastically improves catalytic performance.

Kinetic Modeling of Catalytic Olefin Cracking and Methanol-to-Olefins (MTO) over Zeolites: A Review

The increasing demand for lower olefins requires new production routes besides steam cracking and fluid catalytic cracking (FCC). Furthermore, less energy consumption, more flexibility in feed and a higher influence on the product distribution are necessary. In this context, catalytic olefin cracking and methanol-to-olefins (MTO) gain in importance. Here, the undesired higher olefins can be catalytically converted and, for methanol, the possibility of a green synthesis route exists. Kinetic modeling of these processes is a helpful tool in understanding the reactivity and finding optimum operating points; however, it is also challenging because reaction networks for hydrocarbon interconversion are rather complex. This review analyzes different deterministic kinetic models published in the literature since 2000. After a presentation of the underlying chemistry and thermodynamics, the models are compared in terms of catalysts, reaction setups and operating conditions. Furthermore, the modeling methodology is shown; both lumped and microkinetic approaches can be found. Despite ZSM-5 being the most widely used catalyst for these processes, other catalysts such as SAPO-34, SAPO-18 and ZSM-23 are also discussed here. Finally, some general as well as reaction-specific recommendations for future work on modeling of complex reaction networks are given.