(694f) Co-Oligomerization of Ethylene and Propylene on Acidic Zeolites: A Microkinetic Model

1. Introduction

Light hydrocarbons with relatively low fuel value, particularly ethane and propane, are abundant by-products from refinery units and petrochemical plants and components of abundant shale gas. One potential route for their utilization is conversion to the corresponding alkenes, followed by oligomerization, which has been an active field of research in the last few decades, due to its importance in the upgrading of hydrocarbon streams. Conversion of these light hydrocarbon gases to liquid products would greatly reduce their transportation costs and open up new opportunities for their use as chemicals and fuels [1].

Oligomerization of light alkenes can be carried out on solid Brønsted acid catalysts such as proton-exchanged zeolite H-ZSM-5. The pore geometry of this catalyst imposes restrictions on the degree of branching of the products and influences the product distributions of low temperature (250-300 °C) alkene oligomerization [2].

A typical approach applied to study these complex reacting systems is “pathways-level modelling”, consisting of the lumping of several reactions in a single one describing the conversion of a reagent into a product and disregarding any reaction intermediate(s). However, due to the crude lumping by carbon number, these models are not detailed enough to predict the complex product distribution and the process selectivity. Furthermore, the multicomponent nature of each lump obscures the detailed molecular information. This affects the “predictive power” of the model and thus its ability to be applied beyond the range of conditions for which it was specifically developed.

The alternative proposed in this work is based on the construction of a microkinetic model composed of elementary steps obeying the law of microscopic reversibility. In a microkinetic model, all elementary steps in the reaction mechanism are considered explicitly, with no assumption about the rate-determining step. These mechanistic models have been demonstrated to be effective in elucidating reaction mechanisms and quantifying competing reaction pathways for complex networks.

2. Methods

The co-oligomerization process of ethylene and propylene is characterized by an extremely complex product distribution. Computational methods are, for this reason, essential to develop a reaction mechanism and solve the corresponding reactor models.

Despite the large dimension of the network, the number of reactions that occur with similar chemistry can be considered relatively small. For this reason, the chemistry of the system was organized into reaction families (e.g., protonation/deprotonation, oligomerization/β-scission), and a mathematical operator was specified for each family [3]. The species identified in the reacting system were represented using bond and electron (BE) matrices based on graph theory. The reaction mechanism was then created automatically by applying the operators to all the different reactants and their progeny.

In order to develop a mechanistic model that is of reasonable size, a rate-based termination algorithm was additionally introduced [4]. The rate constants are estimated as the mechanism is generated, allowing the partial mechanisms to be solved to estimate the yield profiles of the species involved in the system. The decision to allow a certain species to react is based on its specific rate of formation. If its rate of formation is higher than a minimal rate, the algorithm generates the reactions where the current species is a reactant and includes them in the network. Otherwise, the current scheme is considered adequate, and the program terminates.

The rate coefficients for the elementary steps were expressed in Arrhenius form. The Evans-Polanyí relationship was used to relate the activation energy to the heats of reaction of each reaction step. The heats of reactions were calculated based on the heats of formation of the reacting species. The frequency factors were estimated directly from transition state theory.

3. Results and discussion

The reaction network is initiated via formation of carbenium ions by protonation of the double bond of ethylene and propylene. Note that the intermediates are termed carbenium ions for bookkeeping purposes, but parameters governing their stability are derived from literature that characterizes them more aptly as alkoxide species. The reverse reaction, deprotonation, is a termination step that desorbs the alkenes from the surface of the catalyst returning a proton to the acid site. Oligomerization proceeds through addition of an alkene to a carbenium ion and consequent formation of a new sigma bond. β-scission breaks the bond between the carbon atom in the β-position with respect to the charged carbon atom, representing the reverse step of oligomerization. Cyclization reactions for molecules with carbon atoms higher than 4 were also included in the network. The application of these reaction families was restricted to a limited number of reactants to generate molecular species with relatively low carbon number (≤ 12) to control the growth of the oligomerization mechanism.

The developed reaction network and the estimated kinetic coefficients were coupled with the design equations of a PFR to build a continuum kinetic model. The resulting system of differential equations was then integrated using a numerical solver to simulate reaction kinetics, product yields and selectivity. The proposed mathematical model was validated to confirm its reliability using the results of experimental runs conducted in a PFR under varying operating conditions.

4. Conclusions

The microkinetic analysis presented in this paper unravels mechanistic details of acid-catalyzed oligomerization chemistry of alkenes with high industrial relevance. The developed mathematical model represents a powerful tool to reproduce and predict the product distribution obtained from experimental activities.

References

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