The dissociation of NO and CO has been studied on cluster models representing the copper(100) and -(111) single-crystal faces using density functional quantum calculations. For each surface, several possible reaction paths are proposed, for which we fully optimized the reactant, product, and transition states at the local density level (LDA). Nonlocal density functional calculations (NLDA) were then performed on these optimized geometries. The clusters we used, varying in size between 13 and 31 atoms, produced dissociation barriers and energies that were reasonably well converged with cluster size. Classical transition-state theory was used to calculate the rates of dissociation and recombination on the basis of computed frequencies of the predicted transition state and the reactant and product states. The transition states for NO and CO dissociation on all surfaces can be described as "tight" transition states corresponding to preexponentials for dissociation in the range 10 10 -10 13 s -1 . The dissociation barrier for NO is significantly lower than that for CO. In addition, the more open Cu(100) surface is more reactive toward dissociation than the close-packed Cu (111) surface. Nonlocal corrections to the LDA functional were found to have a small effect on dissociation barrier height, but the effect was found to be more profound on the recombination barrier and overall dissociation energies.

No abstract

Density functional theory provides a first-principles approach for computing the geometric and electronic structures, and a wealth of corresponding properties, of a wide range of materials types and compositions, including bulk solids, surfaces, defects and clusters of molecules. Parallel advances in hardware performance, implementation strategies and algorithms have all contributed to a rapid growth in the number of important applications. Recent developments under each of these themes are outlined and the breadth of current applications is illustrated by typical examples. Issues associated with the implementation and performance of density functional methods on parallel computer architectures are discussed.

No abstract