Ab initio pseudopotential calculation of the photo-response of metal clusters A massively parallel ab initio computer code, which uses Gaussian bases, pseudopotentials, and the local density approximation, permits the study of transition-metal systems with literally hundreds of atoms. We present total energies and relaxed geometries for Ru, Pd, and Ag clusters with Nϭ55, 135, and 140 atoms. The Nϭ55 and 135 clusters were chosen because of simultaneous cubo-octahedral ͑fcc͒ and icosahedral ͑icos͒ subshell closings, and we find icos geometries are preferred. Remarkably large compressions of the central atoms are observed for the icos structures ͑up to 6% compared with bulk interatomic spacings͒, while small core compressions (ϳ1%) are found for the fcc geometry. In contrast, large surface compressive relaxations are found for the fcc clusters (ϳ2%-3% in average nearest neighbor spacing͒, while the icos surface displays small compressions (ϳ1%). Energy differences between icos and fcc are smallest for Pd, and for all systems the single-particle densities of states closely resembles bulk results. Calculations with Nϭ134 suggest slow changes in relative energy with N. Noting that the 135-atom fcc has a much more open surface than the icos, we also compare Nϭ140 icos and fcc, the latter forming an octahedron with close packed facets. These icos and fcc clusters have identical average coordinations and the octahedron is found to be preferred for Ru and Pd but not for Ag. Finally, we compare Harris functional and LDA energy differences on the Nϭ140 clusters, and find fair agreement only for Ag. ͓S0021-9606͑97͒00305-X͔
This paper summarizes our efforts to develop fast algorithms for density
functional theory (DFT) calculations of inhomogeneous fluids. Our goal is to
apply DFTs to a variety of problems in nanotechnology and biology. To this
end we have developed DFT codes to treat both atomic fluid models
and polymeric fluids. We have developed both three-dimensional real
space and Fourier space algorithms. The former rely on a matrix-based
Newton’s method while the latter couple fast Fourier transforms with a
matrix-free Newton’s method. Efficient computation of phase diagrams and
investigation of multiple solutions is facilitated with phase transition tracking
algorithms and arclength continuation algorithms. We have explored the
performance that can be obtained by application of massively parallel
computing, and have begun application of the codes to a variety of two-and
three-dimensional systems. In this paper, we summarize our algorithm
development work as well as briefly discuss a few applications including
adsorption and transport in ion channel proteins, capillary condensation in
disordered porous media and confinement effects in a diblock copolymer fluid.
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