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Nanoparticles (NPs) make for intriguing heterogeneous catalysts due to their large active surface area and excellent and often size-dependent catalytic properties that emerge from a multitude of chemically different surface reaction sites. NP catalysts are, in principle, also highly tunable: even small changes to the NP size or surface facet composition, doping with heteroatoms, or changes of the supporting material can significantly alter their physicochemical properties. Because synthesis of size- and shape-controlled NP catalysts is challenging, the ability to computationally predict the most favorable NP structures for a catalytic reaction of interest is an in-demand skill that can help accelerate and streamline the material optimization process. Fundamentally, simulations of NP model systems present unique challenges to computational scientists. Not only must considerable methodological hurdles be overcome in performing calculations with hundreds to thousands of atoms while retaining appropriate accuracy to be able to probe the desired properties. Also, the data generated by simulations of NPs are typically more complex than data from simulations of, for example, single crystal surface models, and therefore often requires different data analysis strategies. To this end, the present work aims to review analytical methods and data analysis strategies that have proven useful in extracting thermodynamic trends from NP simulations., Comment: To be submitted to PCCP as a tutorial review

The activity and stability of a platinum nanoparticle (NP) is not only affected by its size but additionally depends on its shape. To this end, simulations can identify structure-property relationships to make a priori decisions on the most promising structures. While activity is routinely probed by electronic structure calculations on simplified surface models, modeling the stability of NP model systems in electrochemical reactions is challenging due to the long timescale of relevant processes such as oxidation beyond the point of reversibility. In this work, a routine for simulating electrocatalyst stability is presented. The procedure is referred to as GREG after its main ingredients - a grand-canonical simulation approach using reactive force fields to model electrochemical reactions as a function of the galvanic cell potential. The GREG routine is applied to study the oxidation of 3 nm octahedral, cubic, dodecahedral, cuboctahedral, spherical, and tetrahexahedral platinum NPs. The oxidation process is analyzed using adsorption isobars as well as interaction energy heat maps that provide the basis for constructing electrochemical phase diagrams. Onset potentials for surface oxidation increase in the sequence cube ~= dodecahedron <= octahedron <= tetrahexahdron < sphere < cuboctahedron, establishing a relationship between oxidation behavior and surface facet structure. The electrochemical results are rationalized using structural and electronic analysis., Comment: Submitted to J. Phys. Chem. C

The interface between liquid water and the Pt(111) metal surface is characterized structurally and thermodynamically via reactive molecular dynamics (MD) simulations within the ReaxFF framework. The formation of a distinct buckled adsorbate layer and subsequent wetting layers is tracked via the course of the waters density as well as the distribution of the H2O molecules with increasing distance to the metal surface. Hereby, also the Two Phase Thermodynamics method (2PT) has been utilized for studying the course of entropy as well as the translational, rotational and vibrational entropic contributions throughout the Pt(111)/H2O interface. A significant reduction of the entropy compared to the bulk value is observed in the adsorbate layer ($S$ = 31.05$\pm$2.48\,J/molK ) along with a density of 3.26$\pm$0.06g/cm$^{3}$. The O-O interlayer distribution allows direct tracing of the water ordering and a quantified comparison to the ideal hexagonal adlayer. While the adsorbate layer at the Pt surface shows the occurrence of hexagonal motifs, this near-order is already weakened in the wetting layers. Bulk behavior is reached at 15$\mathrm{\mathring{A}}$ distance from the Pt(111) metal. Introducing an electric field of 0.1 V/$\mathrm{\mathring{A}}$ prolongs the ordering effect of the metal surface into the liquid water., Comment: 8 pages, 5 figures

In this article we formulate the superperturbation theory for the Anderson impurity model on the real axis. The resulting impurity solver allows to evaluate dynamical quantities without numerical analytical continuation by the maximum entropy method or Pad\'e approximants. This makes the solver well suited to study multiplet effects in solids within the dynamical mean field theory. First examples including multi-orbital problems are discussed.

We present a very efficient solver for the general Anderson impurity problem. It is based on the perturbation around a solution obtained from exact diagonalization using a small number of bath sites. We formulate a perturbation theory which is valid for both weak and strong coupling and interpolates between these limits. Good agreement with numerically exact quantum Monte-Carlo results is found for a single bath site over a wide range of parameters. In particular, the Kondo resonance in the intermediate coupling regime is well reproduced for a single bath site and the lowest order correction. The method is particularly suited for low temperatures and alleviates analytical continuation of imaginary time data due to the absence of statistical noise compared to quantum Monte-Carlo impurity solvers., Comment: 6 pages, 5 figures