The nature of stability and adsorption interactions of binary Au-Li clusters with bridge adsorption structures

Earlier findings have confirmed that CO molecules have propensities to adsorb on low-coordinated gold atoms (top sites) of Au-based clusters, which can be treated by the Blyholder model wherein the σ donation and π-back donation take place. Here, the structural features and stability of (AuLi)_n (n = 1-9) clusters were first analyzed using the GA-DFT method. The new adsorption modes, vibration frequencies and electronic interactions for Au-Li clusters with CO were investigated in detail. More excitingly, we found that CO prefers to adsorb on the bridge sites of the Au-Li clusters rather than on the top sites, which are much lower in energies than the top adsorptions, and the C-O stretching frequencies are also red-shifted. AIMD simulations show that the adsorption structures still have good thermal stability at 500 K. The density of states reveals that the electronic structures of Au-Li clusters have excellent stability for the bridge adsorptions of CO molecules. The ETS-NOCV analysis and NPA charges show that the direction of charge flow is from Au-Li clusters → CO. Our study provides an idea to elucidate the new adsorption mechanism on Au-Li clusters and the connection between the geometries and reaction properties.

Reliability of semiempirical and DFTB methods for the global optimization of the structures of nanoclusters

In this work, we explore the possibility of using computationally inexpensive electronic structure methods, such as semiempirical and DFTB calculations, for the search of the global minimum (GM) structure of chemical systems. The basic prerequisite that these inexpensive methods will need to fulfill is that their lowest energy structures can be used as starting point for a subsequent local optimization at a benchmark level that will yield its GM. If this is possible, one could bypass the global optimization at the expensive method, which is currently impossible except for very small molecules. Specifically, we test our methods with clusters of second row elements including systems of several bonding types, such as alkali, metal, and covalent clusters. The results reveal that the DFTB3 method yields reasonable results and is a potential candidate for this type of applications. Even though the DFTB2 approach using standard parameters is proven to yield poor results, we show that a re-parametrization of only its repulsive part is enough to achieve excellent results, even when applied to larger systems outside the training set.

A method for predicting basins in the global optimization of nanoclusters with applications to AlxCuy alloys

The problem of obtaining the geometrical configuration of a molecule that minimizes its potential energy is a very complicated one for a series of applications, ranging from determining the structure of biological macromolecules to nanoclusters of atoms. Global optimization tools are available for this task, and many of them are based in performing successive local optimizations, where the starting geometries for these steps are determined by an intelligent algorithm. Here we develop a method to save computing time in the optimization of nanoclusters by predicting if a given minimum has been previously visited during local optimization steps. Our application to Cu-Al nanoalloys indicates that it is possible to save a substantial amount of computational cost. The application also reveals new promising Al_xCu_y clusters and explain their stabilities in terms of the jellium model.

An ab initio investigation of the adsorption properties of water on binary AlSi clusters

Nanoalloys represent potential catalysts for the water splitting reaction. The water–cluster interaction is a key aspect of the process, but is not fully understood. This work provides an in-depth study and insights into the AlxSiy·H₂O case.