Correlating anisotropy and disorder with the surface structure of platinum nanoparticles.

Due to the competition between numerous physicochemical variables during formation and processing, platinum nanocatalysts typically contain a mixture of shapes, distributions of sizes, and a considerable degree of surface imperfection. Structural imperfection and sample polydispersivity are inevitable at scale, but accepting bulk and surface diversity as legitimate design features provides new opportunities for nanoparticle design. In recent years disorder and anisotropy have been embraced as useful design parameters but predicting the impact of uncontrollable imperfection a priori is challenging. In the present work we have created an ensemble of uniquely imperfect nanoparticles extracted from classical molecular dynamics trajectories and applied statistical filters to restrict the ensemble in ways that reflect common industrial design principles. We find that targeting different sizes and size distributions may be an effective way of promoting or suppressing internal disorder or crystallinity (as required), but the degree of anisotropy of the particle as a whole has a greater impact on the population of different types of surface ordering and active sites. These results indicate that tuning of disordered and anisotropic Pt nanoparticles is possible, but it is not as straightforward as geometrically ideal nanoparticles with a high degree of crystallinity. It is unlikely that a synthesis strategy could eliminate this diversity entirely, or ensure this type of structural complexity does not develop post-synthesis under operational conditions, but it may be possible to bias the formation of specific bulk structures and the surface anisotropy.

Ewald Summation for Molecular Simulations.

Ewald summation is an important technique for molecular simulation. In this article, expressions are provided for implementing Ewald summation for any inverse power potential in a range of different simulations. Energies, forces, stresses, and Hessian elements as well as truncation errors are considered. Focus is also given to methods for accelerating Ewald summation in Monte Carlo simulations, particularly in the grand canonical ensemble. Ewald techniques are applied to the simulation of CO2 adsorption and diffusion in the metal-organic framework, MOF-5. These simulations show that optimized Ewald summation can provide increased accuracy at similar computational cost compared to that of pair-based methods.

Gas binding to Au13, Au12Pd, and Au11Pd2 nanoclusters in the context of catalytic oxidation and reduction reactions.

The ability of Au(13), Au(12)Pd, and Au(11)Pd(2) nanoclusters to bind species typically found in the oxidation and reduction of small hydrocarbon has been investigated by means of atom centered density functional theory calculations. Binding energies of CO(2), H(2), CO, O(2), CH(4), H(2)O, *O, *H, *CHO, *CO(2)H, and *OH have been calculated. For pure gold nanoclusters, CO(2), H(2), and CH(4) were found to not bind, and O(2) and H(2)O bound weakly with binding energies less than 15 kcal mol(-1), with the rest binding strongly with binding energies in the range 26-68 kcal mol(-1). Binding additional gas molecules did not greatly reduce the binding energy. Adding palladium to the clusters created binding sites for all of the test gases. Binding to the palladium atom generally increased the binding energy of molecules but decreased the binding energy of radicals.