A DFT+U study of acetylene selective hydrogenation on oxygen defective anatase (101) and rutile (110) TiO2 supported Pd4 clusterWe have studied the stoichiometric (annealed in oxygen), the slightly oxygen-deficient (annealed in vacuum), and the highly defective (sputtered with Ar + ) Ti0 2 ( Ito) surfaces and their reactivities to molecular oxygen, molecular water, and 50-eV hydrogen ions using x-ray photoelectron spectroscopy (XPS) and low-energy ion scattering spectroscopy (LEIS). The use of isotopically labeled I KO enables us to distinguish adsorbed oxygen from lattice oxygen, and the concentration of surface oxygen vacancies is titrated by 18 0 2 adsorption. LEIS (l-keV He' ) is used to analyze the chemical composition of the outermost surface layer before and after 18 0 2 and H 2 1K O exposure. Water adsorbs on both stoichiometric and slightly O-deficient surfaces [with oxygeil vacancies -0 and 0.08 monolayer (ML), respectively] at room temperature. There is little or no dependence of saturation water coverage (lower limit of -0.07 ML for both surfaces) on the concentration of surface oxygen vacancies. On the highly defective surfaces, the saturation water coverage increases to a lower limit of 0.1 5 ML and the saturation 18 0 coverage increases to 0.4 ML. The interaction of hydrogen with the stoichiometric surface creates defect states that can be observed by XPS and by subsequent adsorption of 18 0.
We present a dipole-dipole interaction model for polar molecules vertically adsorbed on a idealized metal surface in an approximate analytic form suitable for estimating the coverage dependence of the work function, binding energies, and thermal desorption activation energies. In contrast to previous treatments, we have included all contributions to the interaction energy within the dipole model, such as the internal polarization energy and the coverage dependence of the self-image interaction with the metal. We show that these can contribute significantly to the total interaction energy. We present formulae for both point and extended 'dipole cases. ')Pacific Northwest Laboratory is a mUltiprogram national laboratory operated by Battelle Memorial Institute for the Department of Energy under Contract No. DE-AC06-76LO-1830.
For salmon populations in the Columbia River and Snake River basins, many of which are listed under the U.S. Endangered Species Act of 1973, reliable estimates of the proportion of hatchery‐origin adults in spawning areas (p) are needed to assess population status and the genetic and demographic interactions of hatchery‐ and natural‐origin fish. Some hatchery fish receive visible marks, coded wire tags (CWTs), parentage‐based tags (PBTs), or all three. This allows one to identify whether fish recovered after release are of hatchery origin. Parentage‐based tagging involves genotyping hatchery broodstock and uses parentage assignments as “tags” that identify the origin and brood year of their progeny. We derived a maximum likelihood estimator of p and applied it to the 2012 and 2013 carcass survey data for spring–summer Chinook Salmon Oncorhynchus tshawytscha in the South Fork Salmon River, Idaho. Maximum likelihood estimation was also applied to CWT data and, for investigating the importance of expected tag recoveries on precision, to simulated PBT data for fall Chinook Salmon spawning in the Hanford Reach of the Columbia River. Precision of p from maximum likelihood estimation increased with the expected number of tag recoveries in a carcass survey, whether CWTs or PBTs. In the South Fork Salmon River application, there were 340% more PBT recoveries than CWT recoveries, leading to greater precision in release‐specific values of p from maximum likelihood estimation. The maximum likelihood estimation procedure provides fisheries managers a method to design a tagging and sampling program aimed at estimating p, a valuable measure of the potential for interaction of wild‐ and hatchery‐origin fish on the spawning grounds. To design a program for estimating p, we recommend selecting a target level of precision and then choosing a tagging fraction and sampling rate that delivers that precision in the most cost‐effective way.
Received August 21, 2015; accepted January 19, 2016 Published online April 27, 2016
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