Multiscale kinetic modeling in catalysis ⇒ from microkinetics to computational fluid dynamics and process simulations

Problem statement

We envision multiscale modeling as critical enablers of reaction understanding, catalyst and reactor design, scale-up, and process optimization. The framework includes predicting the molecular reaction mechanism at the molecular level to the process optimization stage. As catalytic processes occur at the multiscale, we address these issues individually and collectively.

At the microkinetic level, our models resolve the rates of the individual elementary steps, rate-determining step (RDS), adsorption, and desorption mechanisms. We use quantum chemical calculations (density functional theory, DFT) to support our assumed kinetic pathways, original parameter estimations, and adsorption-desorption energies.

We incorporate thermodynamic constraints into our models. Once developed, the microkinetic model could guide the catalyst and reactor design. We also have experience developing Langmuir-Hinshelwood and Eley-Rideal types of kinetic models.

At the macrokineitc level, we develop lump-based and empirical models which, in some cases, are very robust and, together with other models, can be used to extract information such as mechanism change, optimize conditions, or for reactor pre-design.

We couple hydrodynamics, heat transfer, and reaction kinetics at the reactor level in computational fluid dynamic (CFD) simulations. Together with optimization algorithms, we aim to improve operating scenarios, develop innovative reactor prototypes, and predict process behaviors at the industrial scale.

Goals

  • Microkinetics I ⇒ key thermodynamic relationships
  • Microkinetics II ⇒ fitting, training, and optimization
  • Microkinetics III ⇒ ab initio kinetic modeling
  • Macrokinetics ⇒ complex reaction networks and population balances
  • CPFD ⇒ reactor modeling and scale-up
  • CFD ⇒ reactor modeling and optimization
  • CFD II ⇒ modeling operando reactors
  • Process system engineering ⇒ gPROMS

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Related Publications

Streamlining the estimation of kinetic parameters using periodic reaction conditions: The methanol-to-hydrocarbon reaction as a case study

by Vicente, Gayubo, Aguayo, Castaño
Chem. Eng. J. Year: 2022 DOI: https://doi.org/10.1016/j.cej.2022.134800

Abstract

Reducing the experimental time required to obtain a robust kinetic model with reliable kinetic parameters has been a long-standing objective in reaction engineering. In the present study, we compare the kinetic modeling of two sets of data obtained using periodic reaction conditions (PRC) and stationary reaction conditions (SRC). As a case study, we use the well-known methanol-to-hydrocarbon reaction on HZSM-5 zeolite. The SRC experiments are conducted with a temperature of 425–475 °C, a total pressure of 2.5 bar, a partial pressure for methanol of 1.125 bar, a space time of 0.1–1.5 gcat h molC−1, a initial molar ratio water:methanol of 0–0.66 and 16 h on stream. The PRC experiments involve sinusoidal variation in the methanol and water flowrates of 135 ± 88 µL min−1 and 20 ± 20 µL min−1, respectively, with a period of 16 h or sinusoidal variation in the temperature of 450 ± 25 °C with periods of 8 and 16 h. Several strategies are then used in fitting the kinetic parameters of five models. We obtain relatively similar results in terms of model discrimination, the parameters, and confidence intervals with a cumulative experimental time of 64 h on stream under the PRC compared with 192 h on stream under the SRC, a reduction of 67% in the experimental time.

Keywords

OLG MKM CRE