The DFT+Umol method and its application to the adsorption of CO on platinum model clusters

Size-dependent properties of transition metal clusters: from molecules to crystals and surfaces--computational studies with the program ParaGauss

In the so-called scalable regime the size-dependent behavior of the physical and chemical properties of transition metal clusters is described by scaling relationships. For most quantities this scalable regime is reached for cluster sizes between a few tens and a few hundreds of atoms, hence for systems for which an accurate treatment by density functional theory is still feasible. Thus, by invoking scaling relations one is able to obtain properties of very large nanoparticles and even the bulk limit from the results of a series of smaller cluster models. In this invited review we illustrate this strategy by exploiting results from computational studies that mostly were carried out with the density functional theory software ParaGauss. We address mainly the size-dependent behavior of the properties of transition metal clusters. To this end, we first present benchmark studies probing various approximations that are used in such density functional calculations. Subsequently we show how physical insight may be gained by exploring less understood types of systems. These applications range from bare clusters to nanoislands and nanoalloys to adsorption complexes.

Kinetic modelling of heterogeneous catalytic systems

The importance of heterogeneous catalysis in modern life is evidenced by the fact that numerous products and technologies routinely used nowadays involve catalysts in their synthesis or function. The discovery of catalytic materials is, however, a non-trivial procedure, requiring tedious trial-and-error experimentation. First-principles-based kinetic modelling methods have recently emerged as a promising way to understand catalytic function and aid in materials discovery. In particular, kinetic Monte Carlo (KMC) simulation is increasingly becoming more popular, as it can integrate several sources of complexity encountered in catalytic systems, and has already been used to successfully unravel the underlying physics of several systems of interest. After a short discussion of the different scales involved in catalysis, we summarize the theory behind KMC simulation, and present the latest KMC computational implementations in the field. Early achievements that transformed the way we think about catalysts are subsequently reviewed in connection to latest studies of realistic systems, in an attempt to highlight how the field has evolved over the last few decades. Present challenges and future directions and opportunities in computational catalysis are finally discussed.