Benchmarking the Accuracy of Density Functional Theory against the Random Phase Approximation for the Ethane Dehydrogenation Network on Pt(111).

The Random Phase Approximation (RPA) is conceptually the most accurate Density Functional Approximation method, able to simultaneously predict both adsorbate and surface energies accurately; however, this work questions its superiority over DFT for catalytic application on hydrocarbon systems. This work uses microkinetic modeling to benchmark the accuracy of DFT functionals against that of RPA for the ethane dehydrogenation reaction on Pt(111). Eight different functionals, with and without dispersion corrections, across the GGA, meta-GGA and hybrid classes are evaluated: PBE, PBE-D3, RPBE, RPBE-D3, BEEF-vdW, SCAN, SCAN-rVV10, and HSE06.

Theoretical Investigation of the Electrochemical Oxidation of H and CO Fuels on a Ruddlesden-Popper SrLaFeO Anode.

The electrochemical oxidation of H and CO fuels have been investigated on the Ruddlesden-Popper layered perovskite SrLaFeO (SLF) under anodic solid oxide fuel cell conditions using periodic density functional theory and microkinetic modeling techniques. Two distinct FeO-plane-terminated surface models differing in terms of the underlying rock salt layer (SrO or LaO) are used to identify the active site and limiting factors for the electro-oxidation of H, CO, and syngas fuels. Microkinetic modeling predicted an order of magnitude higher turnover frequency for the electro-oxidation of H compared to CO for SLF at short-circuit conditions.