Kinetic Monte Carlo Simulations of Methanol Synthesis from Carbon Dioxide and Hydrogen on Cu(111) Catalysts: Statistical Uncertainty Study
2017
Kopač, Drejc | Huš, Matej | Ogrizek, Mitja | Likozar, Blaž
An optimal multiscale linking and integration of atom-scale density functional theory (DFT) computations with mesoscopic kinetic Monte Carlo (KMC) is gaining in importance, particularly upon considering the engineering and intensification of unconventional feedstock processing, as well as the design of emerging catalysis routes. Carbon dioxide activation for methanol synthesis reactions on Cu(111) catalysts was studied using first-principles calculations and KMC modeling simulations. The CO₂ hydrogenation pathway model was applied, consisting of the formate and the reverse water–gas shift (RWGS) mechanistic steps. The dependence of conversion, selectivity, and the rate of desorbed bulk CH₃OH production upon operating process conditions, primarily temperature and pressure, was examined. Catalytic performance results are qualitatively well comparable with the available literature data for heterogeneous copper-based materials. Furthermore, the numerical stability analysis of KMC simulations was statistically assessed with respect to random seed parameters and activation energy barriers. Surface product distribution was found to be particularly sensitive to the smallest perturbations of the activation standard Gibbs energy. The effects of binding site size, crystal lattice dimensions, packed-bed influx composition (gaseous phase reactant partial pressures), and input randomized numbers were, however, less pronounced. This demonstrates that an accurate evaluation of ab initio theoretical research is crucial, especially upon paralleling them to experimental reactor concentrations.
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