(433f) Theoretical Studies on Poisoning of Ni Catalyst in Methane Steam Reforming

Poisoning of catalysts due to carbon-based species is a major impediment to the productivity of industrial operations. Chemical industries spend billions of dollars annually to replace or regenerate deactivated catalysts. Ni catalysts used in Methane Steam Reforming (MSR) are highly susceptible to carbon poisoning due to the formation of graphite layers. Although numerous experimental investigations have been carried out, there is a lack of comprehensive understanding on the carbon poisoning of Ni at the molecular level. It is thus imperative to gain deeper insight into poisoning mechanisms to reduce the rate of deactivation of Ni catalysts.

Graphene (a single layer of graphite) is a representative model for carbon-based catalyst poisons. Previous studies have shown that graphene binds on Ni(111) in a commensurate manner under the influence of van der Waals forces. However, the detailed mechanism of graphene formation (within the MSR pathways) is unclear. We aim to develop a computational model that can adequately capture the MSR reaction kinetics including graphene formation and the van der Waals interaction between Ni and graphene.

In this work, spin-polarized Density Functional Theory (DFT) calculations have been employed to understand the formation of graphene in the MSR reaction. The binding energies of graphene and species of MSR – CO, C, H2O, H, O and OH – were computed using different DFT functionals. The latter include PBE and RPBE (GGA functionals), PBE-D3 and RPBE-D3 (GGA functionals with a posteriori dispersion corrections), optB86b-vdW and optB88-vdW (van der Waals DF). The predictions of these functionals have been benchmarked to experimental data in a systematic way. The PBE functional exhibits good agreement with experimental data for most species of MSR; however, it does not capture the van der Waals interactions between graphene and Ni. RPBE and RPBE-D3 predict the binding energy of CO reasonably well compared to other functionals. Overall, PBE-D3 has been found to predict binding energies of MSR species and graphene with acceptable accuracy.

Subsequently, transition state calculations have been performed (using the PBE-D3 functional) to estimate the activation barriers of different MSR reaction pathways. The three main MSR reforming pathways have comparable activation energies at the electronic level. A KMC model can help us discern the dominant reforming pathway at MSR conditions. These computational investigations can provide qualitative insights to control and mitigate the poisoning rate of Ni catalyst at MSR conditions.