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 simula- tions. 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

Identification of the Catalytic Site at the Interface Perimeter of Au Clusters on Rutile TiO₂(110)

We present a density functional theory study of the CO oxidation reaction at a Au₂₄ cluster supported on a rutile TiO₂(110) slab. The global minimum structure of the Au₂₄ cluster is found using a genetic algorithm search. Catalytic sites are found at the perimeter of the Au–TiO₂ interface but with strong dependence on the surface direction. It is shown how the CO oxidation reaction only happens along the [11̅0] direction of the support and not along the [001] direction. This effect is attributed to a too weak CO binding energy along the [001] direction caused by the charge state and Au–Au coordination of the Au atoms along this direction

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

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 Au₈, Pd₈, and Au₄Pd₄ 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

Reduction of CO₂ with Water on Pt-Loaded Rutile TiO₂(110) Modeled with Density Functional Theory

Photoreduction of CO₂ for fuel production is considered to be an ultimate solution to today’s energy crisis. Platinum (Pt) particles are known to promote photocatalysis reactions when loaded on the surface of titanium dioxide (TiO₂). In this study, we investigate the initial step of the reduction process of CO₂ with water, i.e., the formation of formate, HCOO^–, from surface bound CO₂ and H₂O on rutile TiO₂(110) in terms of energetics of initial and final states using density functional theory calculations. To understand the role of a Pt cocatalyst, chemisorption energies of HCOO and OH on TiO₂(110) are investigated with and without a Pt cluster. It is revealed that free electrons provided by the Pt cluster dramatically decrease the chemisorption energy thanks to the electron transfer from high-lying Pt states to unoccupied valence states induced by the adsorbates, which facilitates ionization of HCOO^– and OH^– on the TiO₂ surface near the Pt cluster. Direct adsorption of HCOO and OH on the surface of the Pt cluster is also energetically favored

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