Extend ethylene aromatization single-event kinetic modeling with physical and chemical descriptor based on ZSM-5 catalyst

Abstract

The ethylene aromatization is critical for the methanol to aromatics and light alkane dehydroaromatization process. The single-event microkinetic (SEMK) model combining the linear free energy theory and solid acid distribution concept were established and extend for the ethylene aromatization process, which can reduce the kinetic parameters and simplify the reaction network by comparison with the SEMK model including subtype elementary steps based on the type of carbenium ions. Further introducing deactivation parameters φ into the model and applying the linear free energy model to the deactivation experimental data, the obtained deactivation parameters φ indicate that the carbon deposition precursors have the greatest impact on reducing the reaction rate of single-molecular reactions and the smallest impact on the hydrogen transfer reaction. Meanwhile, according to the change of reaction enthalpy, effect of carbenium ion structure on methylation, ethylation, cyclization and endo-β scission was investigated by introducing linear free energy concept into the SEMK model. The effect of different acid strengths on elementary steps was investigated based on the acid strength distribution model, it was found that the methylation and oligomerization reactions, the ali-β scission reaction, endo-β scission reaction and the cyclization reaction were more sensitive to strong acidity sites. The physisorption and chemisorption heat are separated from the protonation heat in the linear free energy kinetic model and the acid strength distribution kinetic model, and the absolute values of the obtained physisorption and chemisorption heat increase with the carbon number of carbenium ions. Furthermore, the parameters of the acid strength distribution kinetic model were applied to propane dehydroaromatization on H-ZSM-5 and the ethane dehydroaromatization on Zn/ZSM-5 to confirm the independence of parameters in the SEMK model with the similar reaction network.