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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Dual experimental and computational approach to elucidate the effect of Ga on Cu/CeO2–ZrO2 catalyst for CO2 hydrogenation

by Yerrayya, Velisoju, Mohamed, Ramirez, Castaño
J. CO2 Util. Year: 2022 DOI: https://doi.org/10.1016/j.jcou.2022.102251

Abstract

Cu–Ga catalysts are potential candidates for activating the selective and stable hydrogenation of carbon dioxide to methanol and dimethyl ether. This work explores the structure–function relationship in specific Cu–Ga/CeO2–ZrO2 catalysts with different Ga loadings. Combining experiments with density functional theory calculations, we find the most well-balanced Cu–Ga interphase (structure) and promote specific mechanistic pathways of the reaction (function). The experiments yielded the highest selectivity of the desired products when the Cu and Ga amounts were equal. The experimental work and density functional theory calculations demonstrated that methanol is formed through the carboxyl pathway on the Cu catalyst, while Ga promotes the formate pathway. Consequently, the productivities of both methanol and dimethyl ether are enhanced. The experimental results match well with the theoretical calculations. Comparing our results with other Ga-promoting systems, we also prove that Cu achieves better balance than Ni and Co

Keywords

CO2 HCE MKM