Converged properties of clean metal surfaces by all-electron first-principles calculations

All-electron full-potential linearized augmented plane-wave calculations of the surface energy, work function, and interlayer spacings of close-packed metal surfaces are presented, in particular, for the free-electron-like metal surfaces, Mg(0 0 0 1) and Al(1 1 1), and for the transition metal surfaces, Ti(0 0 0 1), Cu(1 1 1), Pd(1 1 1), and Pt(1 1 1). We investigate the convergence of the surface energy as a function of the number of layers in the slab, using the Cu(1 1 1) surface as an example. The results show that the surface energy, as obtained using total energies of the slab and bulk from separate calculations, converges well with respect to the number of layers in the slab. Obviously, it is necessary that bulk and surface calculations are performed with the same high accuracy. Furthermore, we discuss the performance of the local-density and generalized gradient approximations for the exchange-correlation functional in describing the various surface properties.     

Low-temperature hydride furnace modified for the atomic absorption spectrometric determination of metals with low appearance temperatures

The sample is vaporized from tungsten filament coils (150 W) and transported by an argon stream to the cell of a modified hydride furnace for atomic absorption spectrometry (a.a.s.). The system provides almost the same sensitivity for elements with low appearance temperatures (e.g., Bi, Cd, Pb, Tl, Zn) as graphite-furnace a.a.s. The detection limits are between 0.1 and 5 ng ml^?1, depending on the element.     

The structure of an Fe monolayer on the Ni (111) surface. A density-functional study using the generalized gradient approximation

Using a density-functional method that employs linear combinations of atomic orbitals as basis sets, nonlocal norm-conserving pseudopotentials and the generalized gradient approximation for exchange and correlation, we found that at 0 K the atoms of an Fe monolayer on the Ni (111) surface occupy hcp rather than fcc sites, in keeping with previous predictions made using the ab initio all-electron full-potential linearized augmented plane wave method with the local spin density approximation.     

Nonparametric Density Estimation in Hidden Markov Models

Let { X n} be a Markov chain that is either f -mixing or satisfies the Poisson equation.In this note we obtain the convergence rate under L 1 -criterion for bounded functions of the X k 's. And in the hidden Markov model setup { (X n ,Y n ) }we study the kernel estimate of the density of the observed variables { Y n }when a 'stable' status is reached.     

Interference of circularly polarized light: contrast and application in fabrication of three-dimensional periodic microstructures

The contrast of interference pattern formed by two circularly polarized waves and by a linearly polarized wave and a circularly polarized one is discussed. The results are compared with that by two linear beams. It shows that the use of circular light in holographic fabrication of three-dimensional periodic microstructures may remove the necessity of beam ratio and polarization optimization needed in the interference of three linear noncoplanar beams and improve the uniform contrast of resultant pattern simultaneously.     

Photochemically generated carotenoid radicals on Nafion film and silica gel: an EPR and ENDOR study

Carotenoid cation radicals have been observed at 120 K, by EPR and proton ENDOR measurements, to be formed upon 77 K photolysis of thin films of Nafion or silica gel coated with the carotenoids, β-carotene and canthaxanthin. The powder ENDOR spectra consist of resolvable lines due to couplings larger than 2.8 MHz but smaller than 17 MHz assigned to the methyl protons of the carotenoid cation radical and to an -proton of the planar polyene chain.     

Pure adaptive search in monte carlo optimization

Pure adaptive search constructs a sequence of points uniformly distributed within a corresponding sequence of nested regions of the feasible space. At any stage, the next point in the sequence is chosen uniformly distributed over the region of feasible space containing all points that are equal or superior in value to the previous points in the sequence. We show that for convex programs the number of iterations required to achieve a given accuracy of solution increases at most linearly in the dimension of the problem. This compares to exponential growth in iterations required for pure random search.