The development of microkinetic models allows gaining an understanding of fundamental catalyst surface phenomena in terms of elementary reaction steps without defining a priori a rate-determining step, yielding more meaningful reaction rates. This work aimed at developing such a microkinetic model that accurately describes the Water-Gas Shift (WGS) reaction, i.e., one of the major routes for hydrogen production, over cobalt (Co) catalysts supported on multi-walled carbon nanotubes (MWCNTs). Co is a sulfur-tolerant active phase, and the functionalized MWCNT support has exceptional conductivity properties and defects that facilitate electron transfer on its surface. The model was formulated based on a well-known mechanism for the WGS reaction involving the highly reactive carboxyl (COOH*) intermediate. The kinetic parameters were either estimated or computed from theoretical prediction models (such as the Collision and Transition-State theory). The derived system of differential-algebraic equations was solved using the DDAPLUS package available in AthenaVISUAL Studio. The developed model was capable of simulating the experimental data (R² = 0.96), presenting statistically significant kinetic parameters. Furthermore, some of the catalysts descriptors introduced in the model were experimentally determined by characterization techniques, such as the specific surface area (SP = 22000 m²/kgcat) and the density of active sites (σ = 0.012 molAct.Surf./kgcat). The characterization results along with the model confirm that the COOH* formation reaction (CO* + OH* → COOH* + *) is the rate-determining step and explain the optimal catalyst performance at elevated temperatures (350-450oC) and space times (70-80 kg.s/mol), as indicated by the experimental results.
Many thanks for sharing your kind feedback, we really appreciated it! Indeed, the development of microkinetic models allows a better understanding of the reaction mechanism that occurs on the catalyst surface, resulting in more precise reaction rates. Estimating some kinetic parameters from experimental data and incorporating catalyst descriptors into the model (e.g., its specific surface area and the density of active sites) were essential steps to provide valuable information on the rate-determining step and the catalyst performance.
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