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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Catalysis letters 25 (1994), S. 105-113 
    ISSN: 1572-879X
    Keywords: Hydrogenation of CO ; direct hydrogenation of CO ; intermediates of CO hydrogenation ; Ni(100)
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Abstract A trace amount of oxygen in H2 promotes a new type of direct hydrogenation reaction of adsorbed CO on Ni(100) surface. The formation of HxCOy was suggested by high resolution electron energy loss spectroscopy (HREELS) and thermal desorption spectroscopy (TDS). HREEL spectra showed the formation of surface hydroxyl (OH) and the C-H bonds of HiCOy species but no carbonyl (C=O) loss peak was detected although thermal desorption yielded large amount of CO. The H x CO y undergoes the decomposition at 400–450 K on the hex-OH Ni(100) surface, which yielded CO, CO2, H2 and H2CO. It was confirmed that no C-H bond formation occurs on c(2 × 2)-O, p(2 × 2)-O Ni(100) and hex-OH Ni(100) as well as on clean Ni(100) surfaces. This fact indicates that the gas phase oxygen may induce the direct hydrogenation of CO to form H x CO y , which is analogous to the hydrogenation of O to form hex-OH onNi(100).
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Landscape ecology 15 (2000), S. 591-601 
    ISSN: 1572-9761
    Keywords: adjacency probability ; aggregation index ; AI ; contagion index ; landscape indices ; map resolution ; measurement resolution ; shape index ; spatial pattern
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract There is often need to measure aggregation levels of spatial patterns within a single map class in landscape ecological studies. The contagion index (CI), shape index (SI), and probability of adjacency of the same class (Qi), all have certain limits when measuring aggregation of spatial patterns. We have developed an aggregation index (AI) that is class specific and independent of landscape composition. AI assumes that a class with the highest level of aggregation (AI =1) is comprised of pixels sharing the most possible edges. A class whose pixels share no edges (completely disaggregated) has the lowest level of aggregation (AI =0). AI is similar to SI and Qi, but it calculates aggregation more precisely than the latter two. We have evaluated the performance of AI under varied levels of (1) aggregation, (2) number of patches, (3) spatial resolutions, and (4) real species distribution maps at various spatial scales. AI was able to produce reasonable results under all these circumstances. Since it is class specific, it is more precise than CI, which measures overall landscape aggregation. Thus, AI provides a quantitative basis to correlate the spatial pattern of a class with a specific process. Since AI is a ratio variable, map units do not affect the calculation. It can be compared between classes from the same or different landscapes, or even the same classes from the same landscape under different resolutions.
    Type of Medium: Electronic Resource
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