Bimetallic Ru−Co catalysts have been reported as promising NH 3 production catalysts that are better than various Ru−X alloys, including RuFe and pure Ru, under mild conditions; however, a systematic understanding of their superior activity is still lacking. Here, we report a comprehensive theoretical study on NH 3 synthesis of Ru−Co catalysts using density functional theory and microkinetic modeling. Indeed, the RuCo surface enables more facile N 2 dissociation than the Ru surface, which results from the manifested Co-induced spin symmetry breaking of Ru. We also investigated the surface phase diagram of RuCo(0001) with partial pressures of H 2 and N 2 gases and found that the most stable phase of the RuCo surface consists of a fraction of both N and H atoms under experimental Haber−Bosch pressure conditions; however, NH 3 can be readily produced on the surfaces without severe surface poisoning issues. Furthermore, this study shows that the spin-symmetry breaking of nonmagnetic surfaces can enhance the catalytic activity for NH 3 synthesis, which provides an alternative strategy to catalyst design.

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In computational catalysis, density-functional theory (DFT) calculations are usually utilized, although they suffer from high computational costs. Thus, it would be challenging to explicitly predict the catalytic properties of nanoparticles (NPs) at the nanoscale under solvents. Using molecular dynamics (MD) simulations with a reactive force field (ReaxFF), we investigated the catalytic performance of Ni–Pt NPs for the direct synthesis of hydrogen peroxide (H2O2), in which water solvents were explicitly considered along with the effects of the sizes (1.5, 2.0, 3.0, and 3.5 nm) and compositions (Ni90Pt10, Ni80Pt20, and Ni50Pt50) of the NPs. Among the Ni–Pt NPs, 3.0 nm NPs show the highest activity and selectivity for the direct synthesis of H2O2, revealing that the catalytic performance is not well correlated with the surface areas of NPs. The superior catalytic performance results from the high H2 dissociation and low O2 dissociation properties, which are correlated with the numbers of NiNiPt-fcc and NiNi-bridge sites on the surface of Ni–Pt NPs, respectively. The ReaxFF-MD simulations propose the optimum composition (Ni80Pt20) of 3.0 nm Ni–Pt NPs, which is also explained by the numbers of NiNiPt-fcc and NiNi-bridge sites. Furthermore, from the ReaxFF-MD simulations, the direct synthesis of H2O2 for the Ni–Pt NPs can be achieved not only with the Langmuir–Hinshelwood mechanism, which has been conventionally considered, but also with the water-induced mechanism, which is unlikely to occur on pure Pd and Pd-based alloy catalysts; these results are supported by DFT calculations. These results reveal that the ReaxFF-MD method provides significant information for predicting the catalytic properties of NPs, which could be difficult to provide with DFT calculations; thus, it can be a useful framework for the design of nanocatalysts through complementation with a DFT method.