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

Related People

Related Covers

Related Publications

Adaptable kinetic model for the transient and pseudo-steady states in the hydrodeoxygenation of raw bio-oil

by Cordero-Lanzac, Hita, Garcia-Mateos, Castaño, Rodriguez-Mirasol, Cordero, Bilbao
Chem. Eng. J. Year: 2020

Abstract

The hydrodeoxygenation (HDO) of raw bio-oil is an attractive route for the production of fuels and chemicals from biomass. For the sake of advancing towards the implantation of HDO at larger scale, an adaptable kinetic model is presented for this process. A CoMo bifunctional catalyst supported on an activated carbon has been used. The P-functionalities of the activated carbon support provide the catalyst with enhanced acidic features. The HDO runs have been carried out in a continuous packed bed reactor at 425–475 °C. Two subsequent reaction stages have been observed during the experimental runs: a transient and a pseudo-steady state. In the former stage, the catalyst is partially deactivated whereas in the latter, an apparent constant activity is reached. The model decodes the complex reaction network of HDO with seven lumps and eleven reaction steps. The proposed model accounts for the evolution with time of the reaction medium composition in the transient state, considering the reactions involved in the gas phase and the ones of solid product deposition and catalyst deactivation. Important contributions of decarboxylation-decarbonylation-decomposition and repolymerization pathways towards CO/CO2/CH4 and thermal lignin are observed. The model also estimates the product distribution in the pseudo-steady state, in which the net deposition of solid products and the catalyst deactivation are negligible. In this state, the catalyst shows a partially inhibited conversion of phenolic compounds and the maximum yield of aromatics, which are the most interesting value-added chemicals. The proposed kinetic model could play a key role in the design of reactors for the HDO process at higher scale.

Keywords

HPC MKM