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Atomic hydrogen interaction with transition metal surfaces: A high-throughput computational study

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Hydrogen adatoms are involved in many reactions catalyzed by Transition Metal (TM) surfaces, such as the Haber–Bosch process or the reverse water gas shift reaction, key to our modern society. Any rational improvement on such a catalyst requires an atomistic knowledge of the metal↔hydrogen interaction, only attainable from first-principles calculations on suited, realistic models. The present thorough density functional theory study evaluates such H interaction at a low coverage on most stable surfaces of bcc, fcc, and hcp TMs. These are (001), (011), and (111) for bcc and fcc TMs and (0001), (101̅0), and (112̅0) for hcp, covering 27 TMs and 81 different TM surfaces in total. In general terms, the results validate, while expanding, previous assessments, revealing that TM surfaces can be divided into two main groups, one in the majority where H2 would be thermodynamically driven to dissociate into H adatoms, located at heights of ∼0.5 or ∼1.0 Å, and another for late TMs, generally with a d10 electronic configuration, where H2 adsorption with no dissociation would be preferred. No trends in H adsorption energies are found down the groups, but yes along the d series, with a best linear adjustment found for the d-band center descriptor, especially suited for close-packed fcc and hcp TMs surfaces, with a mean absolute error of 0.15 eV. Gibbs free adsorption energies reveal a theoretical volcano plot where fcc TMs are best suited, but with peak Pt performance displaced due to dispersive force inclusion in the method. Still, the volcano plot with respect to the experimental logarithm of the exchanged current density polycrystalline data is far from being valid for a quantitative assessment, although useful for a qualitative screening and to confirm the trends computationally observed.

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Articles publicats en revistes (Ciència dels Materials i Química Física)

# metadata.dc.title[].value
Atomic hydrogen interaction with transition metal surfaces: A high-throughput computational study