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Coverage Dependent Reactivity

For samples with PUe and Ptn 36 the hydrogen evolution eventually reaches a saturation level at higher cluster coverages. For the Ptn 36 samples this level is reached for coverages higher than 0.04 e/nm, for Pt samples above 0.07 e/nm. The maximum average hydrogen production rates are of 2.8 x 10 7/2/h for PUe and [Pg.175]

Averaged hydrogen production per hour and the resulting ML QE of Pt22 and Pt4(, decorated and Ptn 36 as a function of cluster coverage is shown in Fig. 5.28. When considering the ML QE, the previous trend is preserved and even more pronounced. Error bars are calculated from standard deviations of multiple measurements on samples with identical coverage (Fig. 5.27b). [Pg.175]

The presence of a saturation value, evidences that a threshold value exists. Thus, additional Pt clusters per NR seems to have no effect on the photochemical process any more. This observation is tentatively interpreted by means of photo generated electrons being distributed among more and more Pt clusters for increasing coverage. The threshold for saturation is expected for distances between the Pt clusters comparable to the spatial extent of the electronic wave functions. In the present case, this allows for estimating this distance to 5 to 8nm [31]. [Pg.175]

The threshold for saturation is expected for distances between the Pt clusters comparable to the spatial extent of the electronic wave functions. In the present case, this allows for estimating this distance to 5 to 8nm [31]. [Pg.175]


Fig. 6. General representations of heterogeneous oscillatory mechanisms, (a) Buffer-step model (b) coverage-dependent activation energy (c) empty-site model (d) Sales-TUrner-Maple model (e) Pt(lOO) phase transition model (f) Dagonnier model (g) blocking/ reactivation model (h) bulk-phase transition model. Fig. 6. General representations of heterogeneous oscillatory mechanisms, (a) Buffer-step model (b) coverage-dependent activation energy (c) empty-site model (d) Sales-TUrner-Maple model (e) Pt(lOO) phase transition model (f) Dagonnier model (g) blocking/ reactivation model (h) bulk-phase transition model.
Because the bond between Pt and CO is much stronger than that between Pt and H, CO can block the active Pt sites for H adsorption and also competitively displace the adsorbed H from Pt. The preferential adsorption of CO molecules at the active sites on a platinum surface also lowers the reactivity of the remaining uncovered sites through dipole interactions and electron capture. Therefore, any factors that can promote CO coverage will also promote CO poisoning of the Pt surface [6,28]. CO coverage depends on the catalyst surface state (surface roughness) and fhe afmosphere of the electrode/ electrolyte interface. [Pg.57]

The main problem in SIMS is quantification, because of the dependence of relative and absolute secondary-ion yields on matrix effects, on surface coverage by reactive elements (oxygen for instance), on background pressure in the sample chamber, on the effect of crystal orientation with respect to the directions of the primary- and secondary-ion beams, singular effects, etc. (see also Chapter 6). [Pg.282]

FIG. 4 Qualitative phase diagram close to a first-order irreversible phase transition. The solid line shows the dependence of the coverage of A species ( a) on the partial pressure (Ta). Just at the critical point F2a one has a discontinuity in (dashed line) which indicates coexistence between a reactive state with no large A clusters and an A rich phase (hkely a large A cluster). The dotted fine shows a metastability loop where Fas and F s are the upper and lower spinodal points, respectively. Between F2A and Fas the reactive state is unstable and is displaced by the A rich phase. In contrast, between F s and F2A the reactive state displaces the A rich phase. [Pg.396]

Table 10.4 lists the rate parameters for the elementary steps of the CO + NO reaction in the limit of zero coverage. Parameters such as those listed in Tab. 10.4 form the highly desirable input for modeling overall reaction mechanisms. In addition, elementary rate parameters can be compared to calculations on the basis of the theories outlined in Chapters 3 and 6. In this way the kinetic parameters of elementary reaction steps provide, through spectroscopy and computational chemistry, a link between the intramolecular properties of adsorbed reactants and their reactivity Statistical thermodynamics furnishes the theoretical framework to describe how equilibrium constants and reaction rate constants depend on the partition functions of vibration and rotation. Thus, spectroscopy studies of adsorbed reactants and intermediates provide the input for computing equilibrium constants, while calculations on the transition states of reaction pathways, starting from structurally, electronically and vibrationally well-characterized ground states, enable the prediction of kinetic parameters. [Pg.389]

The problems associated with route B also have something to do with steric hindrance. Here the critical point is the steric demand of both monomer and chain end. Incoming monomer will only be connected to the chain end, if steric hindrance is not too high. Otherwise this process will be slowed down or even rendered impossible. Depending on the kind of polyreaction applied, this may lead to termination of the reactive chain end and/or to side reactions of the monomer, like loss of coupling functionality as in some polycondensations or auto-initiation specifically in radical polymerizations. From this discussion it can be extracted that the basic problems for both routes are incomplete coverage (route A) and low molecular weight dendronized polymer (route B). [Pg.177]


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Coverage dependence

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