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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Volatile Tracer Dispersion in Multi-Phase Packed Beds

by Marquez, Castaño, Makkee, Moulijn, Kreutzer
Chem. Eng. Sci. Year: 2010

Abstract

This paper describes the effect of volatility on residence time distribution and conversion in multiphase reactors. This is relevant for the many processes where substantial vaporization of the liquid feed occurs. The typical situation is that the evaporated molecules not only lower the concentration in the liquid phase but also travel faster through the reactor. Our complete model uses two mobile zones, one for the liquid phase and one for the gas phase, with dispersion in each zone and mutual mass transfer. In short, this work can be thought of as extending the popular Piston-Dispersion-Exchange model by adding mobility and dispersion to the second zone. We explore the entire parameter space for our model numerically. We describe quantitatively how the mean residence time of a component decreases when it significantly evaporates to a faster-moving gas phase. We explore how slow mass transfer contributes to the broadening of the residence time distribution. Experimentally, we validated the model in a more limited parameter space in a gas–liquid micro-packed bed with volatile compounds (isopentane, pentane, and 2,2 dimethylbutane) and non-volatile compounds (1-methylethyl benzene) in different solvents (tetradecane and 1-nonanol). The effect of volatility on conversion was analyzed for an -order liquid-phase reaction at different mass-transfer rates. Wherever possible, we extract from the detailed numerical model practical engineering correlations for average residence time and conversion. The results presented in this work teach whether reactant volatility should be considered in a reactor design.

Keywords

CRE MKM