Quantifying the Impact of Parametric Uncertainty on Automatic Mechanism Generation for CO2 Hydrogenation on Ni(111)

Automatic mechanism generation is used to determine mechanisms for the CO2 hydrogenation on Ni(111) in a two-stage process while considering the correlated uncertainty in DFT-based energetic parameters systematically. In a coarse stage, all the possible chemistry is explored with gas-phase products down to the ppb level, while a refined stage discovers the core methanation submechanism. Five thousand unique mechanisms were generated, which contain minor perturbations in all parameters. Global uncertainty assessment, global sensitivity analysis, and degree of rate control analysis are performed to study the effect of this parametric uncertainty on the microkinetic model predictions. Comparison of the model predictions with experimental data on a Ni/SiO2 catalyst find a feasible set of microkinetic mechanisms within the correlated uncertainty space that are in quantitative agreement with the measured data, without relying on explicit parameter optimization. Global uncertainty and sensitivity analyses provide tools to determine the pathways and key factors that control the methanation activity within the parameter space. Together, these methods reveal that the degree of rate control approach can be misleading if parametric uncertainty is not considered. The procedure of considering uncertainties in the automated mechanism generation is not unique to CO2 methanation and can be easily extended to other challenging heterogeneously catalyzed reactions.

Spray-Dried Ni Catalysts with Tailored Properties for CO2 Methanation

A catalyst production method that enables the independent tailoring of the structural properties of the catalyst, such as pore size, metal particle size, metal loading or surface area, allows to increase the efficiency of a catalytic process. Such tailoring can help to make the valorization of CO2 into synthetic fuels on Ni catalysts competitive to conventional fossil fuel production. In this work, a new spray-drying method was used to produce Ni catalysts supported on SiO2 and Al2O3 nanoparticles with tunable properties. The influence of the primary particle size of the support, different metal loadings, and heat treatments were applied to investigate the potential to tailor the properties of catalysts. The catalysts were examined with physical and chemical characterization methods, including X-ray diffraction, temperature-programmed reduction, and chemisorption. A temperature-scanning technique was applied to screen the catalysts for CO2 methanation. With the spray-drying method presented here, well-organized porous spherical nanoparticles of highly dispersed NiO nanoparticles supported on silica with tunable properties were produced and characterized. Moreover, the pore size, metal particle size, and metal loading can be controlled independently, which allows to produce catalyst particles with the desired properties. Ni/SiO2 catalysts with surface areas of up to 40 m2 g−1 with Ni crystals in the range of 4 nm were produced, which exhibited a high activity for the CO2 methanation.