We have developed and implemented an implicit electrolyte model in the Vienna Ab initio Simulation Package (VASP) that includes nonlinear dielectric and ionic responses as well as a nonlocal definition of the cavities defining the spatial regions where these responses can occur. The implementation into the existing VASPsol code is numerically efficient and exhibits robust convergence, requiring computational effort only slightly higher than the original linear polarizable continuum model. The nonlinear + nonlocal model is able to reproduce the characteristic “double hump” shape observed experimentally for the differential capacitance of an electrified metal interface while preventing “leakage” of the electrolyte into regions of space too small to contain a single water molecule or solvated ion. The model also gives a reasonable prediction of molecular solvation free energies as well as the self-ionization free energy of water and the absolute electron chemical potential of the standard hydrogen electrode. All of this, combined with the additional ability to run constant potential density functional theory calculations, should enable the routine computation of activation barriers for electrocatalytic processes.

First-principles screening studies aimed at predicting the catalytic activity of transition metal (TM) catalysts have traditionally been based on mean-field (MF) microkinetic models, which neglect the effect of spatial correlations in the adsorbate layer. Here we critically assess the accuracy of such models for the specific case of CO methanation over stepped metals by comparing to spatially resolved kinetic Monte Carlo (kMC) simulations. We find that the typical low diffusion barriers offered by metal surfaces can be significantly increased at step sites, which results in persisting correlations in the adsorbate layer. As a consequence, MF models may overestimate the catalytic activity of TM catalysts by several orders of magnitude. The potential higher accuracy of kMC models comes at a higher computational cost, which can be especially challenging for surface reactions on metals due to a large disparity in the time scales of different processes. In order to overcome this issue, we implement and test a recently developed algorithm for achieving temporal acceleration of kMC simulations. While the algorithm overall performs quite well, we identify some challenging cases which may lead to a breakdown of acceleration algorithms and discuss possible directions for future algorithm development.

First-principles screening approaches exploiting energy trends in surface adsorption represent an unparalleled success story in recent computational catalysis research. Here we argue that our still limited understanding of the structure of active sites is one of the major bottlenecks towards an ever extended and reliable use of such computational screening for catalyst discovery. For low-index transition metal surfaces, the prevalently chosen high-symmetry (terrace and step) sites offered by the nominal bulk-truncated crystal lattice might be justified. For more complex surfaces and composite catalyst materials, computational screening studies will need to actively embrace a considerable uncertainty with respect to what truly are the active sites. By systematically exploring the space of possible active site motifs, such studies might eventually contribute towards a targeted design of optimized sites in future catalysts.

The total energies of various $\mathrm{Au}∕\mathrm{Pd}\left(111\right)$ alloys are calculated using density functional theory and the results parametrized by a model that includes the energy to exchange gold and palladium atoms within the first and second layers of the alloy, and between the first and second layers. The model is in excellent agreement with the results of density functional theory calculations giving a net repulsive energy between gold and palladium in the first layer, denoted ${\epsilon }_{11}$, of $\sim 0.06\mathrm{eV}$. The effect of the repulsion between gold and palladium is explored using Monte Carlo simulations, where it is found that ordered structures appear only for values of ${\epsilon }_{11}∕kT>1.4$. The results are compared with previously published scanning tunneling microscopy images of gold/Pd(111) alloys, and the measured gold distributions yield good agreement with the results of the Monte Carlo simulations for ${\epsilon }_{11}∕kT\sim 0.64$. This suggests that the experimental value of ${\epsilon }_{11}$ is $\sim 0.02\mathrm{eV}$, in the same range, but slightly lower than predicted by density functional theory.