Study of Catalyst Coke Distribution Based on Population Balance Theory: Application to Methanol to Olefins Process

Li, Hua; Yuan, Xiaoshuai; Gao, Mingbin; Ye, Mao; Liu, Zhongmin

doi:10.1002/aic.16518

Cited by 12 publications

(2 citation statements)

References 15 publications

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“…The simulation results show that the current model can provide a generic and robust way to well predict the methanol conversion and product distribution from laboratory scale reactor to industrial reactor. The details about model development and simulations of these reactors are the subject of a parallel publication …”

Section: Modelingmentioning

confidence: 99%

Kinetic modeling of methanol to olefins process over SAPO‐34 catalyst based on the dual‐cycle reaction mechanism

Yuan

et al. 2018

AIChE Journal

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A kinetic model for methanol to olefins (MTO) process over SAPO‐34 catalyst was established based on the dual‐cycle reaction mechanism. Simplifications were made by assuming olefins‐based cycle as virtual species S, and aromatics‐based cycle as R, where the former mainly accounts for the production of higher olefins, while the latter for lower olefins. Transformation of S to R was considered with the participation of methanol and olefins. Meanwhile, a phenomenological deactivation model was developed to account for the deactivation process. With the proposed model, the evolution of methanol conversion and product selectivity with time on stream could be predicted, and key reaction characteristics, such as the autocatalytic nature of the reaction, could also be captured due to its mechanism‐based nature. Further simulations of MTO reactors at different scales validated the robustness and applicability of the current model in MTO process development and optimization. © 2018 American Institute of Chemical Engineers AIChE J, 65: 662–674, 2019

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Section: Modelingmentioning

confidence: 99%

Kinetic modeling of methanol to olefins process over SAPO‐34 catalyst based on the dual‐cycle reaction mechanism

Yuan

et al. 2018

AIChE Journal

Self Cite

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“…There are also recent studies based e.g. on (i) lattice Boltzmann simulations of multicomponent reaction-diffusion and coke formation in a catalyst with hierarchical pore structure [33], (ii) DFT-backed molecular dynamics method [34], and (iii) population balance theory [35]. Taken together, such models allow one to describe reactions running in various reaction regimes.…”

Section: Specifics Of Coke Formation and Removalmentioning

confidence: 99%

Kinetics and percolation: coke in heterogeneous catalysts

Zhdanov

2022

J. Phys. A: Math. Theor.

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In the conventional lattice percolation models, bonds or sites are open at random, whereas in reality there is often interplay of percolation and the kinetics under consideration. An interesting and practically important example is hydrocarbon conversion occurring in a reactor containing $\sim 1$ mm-sized porous pellets with catalytic nanoparticles deposited at walls of the nanopores. Such catalytic heterogeneous reactions are often accompanied by coke formation deactivating catalytic nanoparticles and blocking pores for reactant diffusion, so that one needs to remove coke from time to time e.g. via reaction with oxygen. Herein, I first present generic coarse-grained Monte Carlo simulations of coke formation in a single pellet with the emphasis on the reaction regime influenced by reactant diffusion in pores. Then, the obtained coke distributions are used for similar simulations of coke removal. This combination of the models has allowed me to illustrate qualitatively new spatio-temporal regimes of the processes under consideration. For example, the removal of coke can be slow in the beginning, due to blocking of oxygen diffusion near the external pellet-gas interface and preventing its penetration to the central part of a pellet, and then fast when the pathways for diffusion to the center become to be open.

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Catalytic Conversion of Hydrocarbons and Formation of Carbon Nanofilaments in Porous Pellets

Zhdanov

2022

Catal Lett

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Catalytic conversion of hydrocarbons occurring at metal nanoparticles in porous pellets is often accompanied by the formation of coke in the form of growing heterogeneous film-like aggregates or carbon nanofilaments. The latter processes result in deactivation of metal nanoparticles. The corresponding kinetic models imply the formation and growth of film-like coke aggregates. Herein, I present an alternative generic kinetic model focused on the formation and growth of carbon nanofilaments. These processes are considered to deactivate metal nanoparticles and reduce the rate of reactant diffusion in pores. In this framework, the kinetically limited reaction regime is described by simple analytical expressions. The diffusion-limited regime can be described as well but only numerically. The model presented can be used for interpretation of experimental results. Graphical Abstract

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Study of Catalyst Coke Distribution Based on Population Balance Theory: Application to Methanol to Olefins Process

Cited by 12 publications

References 15 publications

Kinetic modeling of methanol to olefins process over SAPO‐34 catalyst based on the dual‐cycle reaction mechanism

Kinetic modeling of methanol to olefins process over SAPO‐34 catalyst based on the dual‐cycle reaction mechanism

Kinetics and percolation: coke in heterogeneous catalysts

Catalytic Conversion of Hydrocarbons and Formation of Carbon Nanofilaments in Porous Pellets

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