A genetic algorithm for first principles global structure optimization of supported nano structures.

We present a newly developed publicly available genetic algorithm (GA) for global structure optimisation within atomic scale modeling. The GA is focused on optimizations using first principles calculations, but it works equally well with empirical potentials. The implementation is described and benchmarked through a detailed statistical analysis employing averages across many independent runs of the GA. This analysis focuses on the practical use of GA's with a description of optimal parameters to use. New results for the adsorption of M8 clusters (M = Ru, Rh, Pd, Ag, Pt, Au) on the stoichiometric rutile TiO2(110) surface are presented showing the power of automated structure prediction and highlighting the diversity of metal cluster geometries at the atomic scale.

Interfacial oxygen under TiO2 supported Au clusters revealed by a genetic algorithm search.

We present a density functional theory study of the oxidation of 1D periodic rods supported along the [001] direction on the rutile TiO2(110) surface. The study shows evidence for an oxidation of the interface between the supported Au and the TiO2 crystal. The added O atoms adsorb at the 5f-Ti atoms in the through under the Au rod and are stabilized by charge transfer from the nearest Au atoms. Despite an extensive search, we find no low energy barrier pathways for CO oxidation involving CO adsorbed on Au and O at the perimeter of the Au/TiO2 interface. This is in part attributed the weak adsorption of CO on cationic Au at the perimeter.

Structure and mobility of metal clusters in MOFs: Au, Pd, and AuPd clusters in MOF-74.

Understanding the adsorption and mobility of metal-organic framework (MOF)-supported metal nanoclusters is critical to the development of these catalytic materials. We present the first theoretical investigation of Au-, Pd-, and AuPd-supported clusters in a MOF, namely MOF-74. We combine density functional theory (DFT) calculations with a genetic algorithm (GA) to reliably predict the structure of the adsorbed clusters. This approach allows comparison of hundreds of adsorbed configurations for each cluster. From the investigation of Au(8), Pd(8), and Au(4)Pd(4) we find that the organic part of the MOF is just as important for nanocluster adsorption as open Zn or Mg metal sites. Using the large number of clusters generated by the GA, we developed a systematic method for predicting the mobility of adsorbed clusters. Through the investigation of diffusion paths a relationship between the cluster's adsorption energy and diffusion barrier is established, confirming that Au clusters are highly mobile in the MOF-74 framework and Pd clusters are less mobile.

Systematic study of Au6 to Au12 gold clusters on MgO(100) F centers using density-functional theory.

We present an optimized genetic algorithm used in conjunction with density-functional theory in the search for stable gold clusters and O2 adsorption ensembles in F centers at MgO(100). For Au8 the method recovers known structures and identifies several more stable ones. When O2 adsorption is investigated, the genetic algorithm is used to imitate structural fluxionality, increasing the O2 bond strength by up to 1 eV. Extending the method to Au(6,10,12), strong O2 adsorption configurations are found for all sizes. However, the effect of fluxionality appears to wear off with increasing cluster size.

The atomic simulation environment-a Python library for working with atoms.

The atomic simulation environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simulations. In ASE, tasks are fully scripted in Python. The powerful syntax of Python combined with the NumPy array library make it possible to perform very complex simulation tasks. For example, a sequence of calculations may be performed with the use of a simple 'for-loop' construction. Calculations of energy, forces, stresses and other quantities are performed through interfaces to many external electronic structure codes or force fields using a uniform interface. On top of this calculator interface, ASE provides modules for performing many standard simulation tasks such as structure optimization, molecular dynamics, handling of constraints and performing nudged elastic band calculations.

Thermodynamics of Pore Filling Metal Clusters in Metal Organic Frameworks: Pd in UiO-66.

Metal organic frameworks (MOFs) have experimentally been demonstrated to be capable of supporting isolated transition-metal clusters, but the stability of these clusters with respect to aggregation is unclear. In this letter we use a genetic algorithm together with density functional theory calculations to predict the structure of Pd clusters in UiO-66. The cluster sizes examined are far larger than those in any previous modeling studies of metal clusters in MOFs and allow us to test the hypothesis that the physically separated cavities in UiO-66 could stabilize isolated Pd clusters. Our calculations show that Pd clusters in UiO-66 are, at best, metastable and will aggregate into connected pore filling structures at equilibrium.