The surface topography and local surface work function of ultrathin MgO(001) films on Ag(001) have been studied by noncontact atomic force microscopy (nc-AFM) and Kelvin probe force microscopy (KPFM). First principles calculations have been used to explain the contrast formation of nc-AFM images. In agreement with literature, thin MgO films grow in islands with a quasi rectangular shape. Contrary to alkali halide films supported on metal surfaces, where the island heights can be correctly measured, small MgO islands are either imaged as depressions or elevations depending on the electrostatic potential of the tip apex. Correct island heights therefore cannot be given without knowing the precise contrast formation discussed in this paper. KPFM shows a silver work function which is reduced by the MgO islands. The values for the work function differences for one and two layer thin films are -1.1 and -1.4 eV, respectively, in good agreement with recent calculations and experiments.

We present the first application of hybrid density functional theory (DFT) methods to larger transition-metal clusters. To assess such functionals for this class of systems, we compare the performance of three modern hybrid DFT methods (PBE0, TPSSh, M06) and their semilocal counterparts (PBE, TPSS, M06L) regarding average bond distances and binding energies per atom for a series of octahedral model clusters Mn (M = Ni, Pd, Pt; n = 13, 38, 55, 79, 116). With application to large particles in mind, we extrapolated the results to their respective bulk limits and compared them to experimental values. In some cases, average nearest-neighbor distances are notably overestimated by the PBE0 and M06 hybrid functionals. Results on energies allow a grouping of the tested functionals into sets of similar behavior for the three metals studied. Among the methods examined, the TPSSh hybrid density functional shows the best overall performance.

The performance of eight generalized gradient approximation exchange-correlation (xc) functionals is assessed by a series of scalar relativistic all-electron calculations on octahedral palladium model clusters Pd(n) with n = 13, 19, 38, 55, 79, 147 and the analogous clusters Au(n) (for n up through 79). For these model systems, we determined the cohesive energies and average bond lengths of the optimized octahedral structures. We extrapolate these values to the bulk limits and compare with the corresponding experimental values. While the well-established functionals BP, PBE, and PW91 are the most accurate at predicting energies, the more recent forms PBEsol, VMTsol, and VT{84}sol significantly improve the accuracy of geometries. The observed trends are largely similar for both Pd and Au. In the same spirit, we also studied the scalability of the ionization potentials and electron affinities of the Pd clusters, and extrapolated those quantities to estimates of the work function. Overall, the xc functionals can be classified into four distinct groups according to the accuracy of the computed parameters. These results allow a judicious selection of xc approximations for treating transition metal clusters.

Semi-local DFT approximations are well-known for their difficulty with describing the correct site preference for the adsorption of CO molecules on (111) surfaces of several late transition metals. To address this problem originating from a residual self-interaction in the CO LUMO, we present the DFT+Umol approach which generalizes the empirical DFT+U correction to fragment molecular orbitals. This correction is applied to examine CO adsorption energies at various sites on the (111) facets of cuboctahedral clusters Ptm(CO)8 (m = 79, 140, 225). The DFT+Umol correction leaves the electronic ground state of metal clusters, in particular their d-band structure, essentially unchanged, affecting almost exclusively the energy of the CO LUMO. As a result, that correction is significantly stronger for complexes at hollow sites, hence increases the propensity for adsorption at top sites. We also analyze competing edge effects on the (111) facets of the cluster models.

We present a substantial update to the PyFrag 2008 program, which was originally designed to perform a fragment‐based activation strain analysis along a provided potential energy surface. The original PyFrag 2008 workflow facilitated the characterization of reaction mechanisms in terms of the intrinsic properties, such as strain and interaction, of the reactants. The new PyFrag 2019 program has automated and reduced the time‐consuming and laborious task of setting up, running, analyzing, and visualizing computational data from reaction mechanism studies to a single job. PyFrag 2019 resolves three main challenges associated with the automated computational exploration of reaction mechanisms: it (1) computes the reaction path by carrying out multiple parallel calculations using initial coordinates provided by the user; (2) monitors the entire workflow process; and (3) tabulates and visualizes the final data in a clear way. The activation strain and canonical energy decomposition results that are generated relate the characteristics of the reaction profile in terms of intrinsic properties (strain, interaction, orbital overlaps, orbital energies, populations) of the reactant species. © 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.