Descriptor-Based Microkinetic Modeling and Catalyst Screening for CO Hydrogenation

Abstract

CO hydrogenation is one of the most important and complex chemical reactions with various product distributions in which the product formation mechanism is not well understood yet, and the design of active and selective catalysts toward the targeted products is still a major challenge. Herein, descriptor-based microkinetic modeling is employed to analyze the product distribution and favor the catalyst screening of CO hydrogenation, which predicted well industrial catalysts for different product-related processes. The microkinetic analysis demonstrates that CO activation on the close-packed surface is slow and mainly occurs via hydrogen-assisted CO dissociation, with HCO and CH3O as the most critical intermediates. The major C1/C2 chain growth in the microkinetic model used here takes place through the coupling of CH + CO/CH3C + CO pathways. Both methane and C2/C3 olefin/paraffin formation mechanisms are dependent on metal surfaces. The data analysis illustrated similar adsorption energy of the intermediates with similar structures but different carbon numbers. The chain growth in the microkinetic model was extended to higher hydrocarbon formation in CO hydrogenation by assuming the identical adsorption energy of similarly structured intermediates. Moreover, the activity and selectivity maps successfully identify four active and selective bimetallic catalysts toward CO hydrogenation to light olefin production, where Co3Rh is experimentally proven highly active.