Publication | Open Access
Assessment of the Accuracy of Density Functionals for Calculating Oxygen\n Reduction Reaction on Nitrogen Doped Graphene
15
Citations
80
References
2021
Year
Experimental studies of the oxygen reduction reaction (ORR) at nitrogen doped\ngraphene electrodes have reported a remarkably low overpotential, on the order\nof 0.5 V, similar to Pt based electrodes. Theoretical calculations using\ndensity functional theory have lent support for this claim. However, other\nmeasurements have indicated that transition metal impurities are actually\nresponsible for the ORR activity, thereby raising questions about the\nreliability of both the experiments and the calculations. In order to assess\nthe accuracy of the theoretical calculations, various generalized gradient\napproximation (GGA), meta-GGA and hybrid functionals are employed here and\ncalibrated against high-level wave function based coupled cluster calculations\n(CCSD(T)) of the overpotential as well as self-interaction corrected density\nfunctional calculations and published quantum Monte Carlo calculations of O\nadatom binding to graphene. The PBE0 and HSE06 hybrid functionals are found to\ngive more accurate results than the GGA and meta-GGA functionals, as would be\nexpected, and for low dopant concentration, 3.1%, the overpotential is\ncalculated to be 1.0 V. The GGA and meta-GGA functionals give a lower estimate\nby as much as 0.4 V. When the dopant concentration is doubled, the\noverpotential calculated with hybrid functionals drops, while it increases in\nGGA functional calculations. The opposite trends result from different\npotential determining steps, the *OOH species being of central importance in\nthe hybrid functional calculations while the reduction of *O determines the\noverpotential obtained in GGA and meta-GGA calculations. The results presented\nhere are mainly based on calculations of periodic representations of the\nsystem, but a comparison is also made with molecular flake models which are\nfound to give erratic results.\n
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