DFT benchmark studies on representative species and poisons of methane steam reforming on Ni(111)

Ni catalysts used in methane steam reforming (MSR) are highly susceptible to poisoning by carbon-based species, which poses a major impediment to the productivity of industrial operations. These species encompass graphitic carbon-like formations that are typically modelled as graphene. First principles-based approaches, such as density functional theory (DFT) calculations, can provide valuable insight into the mechanism of graphene growth in the MSR reaction. It is, however, critical that a DFT model of this reaction can accurately describe the interactions of Ni(111) with the MSR intermediates as well as graphene. In this work, a systematic benchmark study has been carried out to identify a suitable DFT functional for the graphene–MSR system. The binding energies of graphene and important MSR species, as well as the reaction energies of methane dissociation and carbon oxidation, were computed on Ni(111) using GGA functionals, DFT-D and van der Waals density functionals (vdW-DF). It is well-established that the GGA functionals are inadequate for describing graphene–Ni(111) interactions. In the case of vdW-DF, the optPBE-vdW functional predicts the binding energies of graphene and several important MSR species with reasonable accuracy; however, it provides poor estimates of CO and O binding energies. Among the DFT-D functionals, PBE-D3 and PBE-dDsC have been found to exhibit acceptable accuracy for graphene and most MSR species (excluding adsorbed CO), and therefore, both functionals are promising for elucidating carbon-based catalytic poisoning in the MSR reaction. Overall, no single DFT functional could estimate the binding energies of all the species with equally high accuracy.