413843 oxidative coupling of methane: Descriptors for activity and selectivity

Increasing natural gas reserves in the recent years motivate further development of processes to convert methane into value-added products. Since the initial description [1] of catalytic oxidative coupling of methane (OCM) to form C₂ hydrocarbons, various pure/doped metal-oxide catalysts have been examined for their methane conversion and C2 selectivity. This ongoing search to find high performing catalysts has been pre-dominantly empirical, and the relationship between active site properties and catalyst activity and selectivity remains unclear. A known dependence of the OCM activity and selectivity on material property (s) enables us to tune active site properties to optimize catalyst performance. This study uses density functional theory (DFT) methods and the established OCM reaction mechanism [2] to relate activity and selectivity to the surface electronic and structural properties of the catalyst. C-H activation and °nCH₃ radical adsorption determine the activity and selectivity of a catalyst, respectively. Since both of these elementary processes reduce the catalyst surface, we hypothesize that the activity (measured by C-H activation) and selectivity measured by °oCH₃ adsorption) of the catalyst correlate with surface reducibility. C-H activation energy and QCH₃ adsorption energy have been plotted against the oxygen vacancy formation energy AE_vac of various metal-doped CeO₂, doped MgO, doped TiO₂, ZnO and TbO_x. Computational results (Figure 1) show a linear relation of the vacancy formation energy (surface reducibility), with the C-H activation energy and nCH₃ adsorption energy. Ceria has a lower C-H activation energy which suggests that it is highly active and would offer better methane conversion. However, it also binds °nCH₃ strongly leading to over-oxidation of methane and thus gives low C₂ selectivity. Conversely, high C-H activation energy and weak °nCH₃ adsorption imply that pure/doped MgO catalysts will have better C₂ selectivity but low activity. Therefore, a trade-off between activity and selectivity is inherent in the active site. Sub-correlations to that shown in Figure 1 demonstrate that this correlation holds across a single material with increasing state of reduction as well as with change in U parameter used in the DFT+U method. Methods on finding an optimal trade-off in activity and selectivity, as well as potential approaches to breaking this correlation, will be discussed.