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Site-specific reactivity of molecules with surface defects—the case of H2 dissociation on Pt

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Science  11 Jan 2019:
Vol. 363, Issue 6423, pp. 155-157
DOI: 10.1126/science.aau6716

Broken on impact

Two competing models have been proposed for the adsorption of molecular hydrogen on platinum surfaces. Both invoke dissociation at surface defects but differ on whether hydrogen molecules diffuse along the surface before encountering a defect or adsorb only if they initially impact a defect site. Van Lent et al. studied the sticking of hydrogen molecules from a molecular beam scanned across a curved platinum single-crystal surface that varied in the density and type of defects exposed. Modeling of the results was consistent only with the second model invoking direct impact.

Science, this issue p. 155

Abstract

The classic system that describes weakly activated dissociation in heterogeneous catalysis has been explained by two dynamical models that are fundamentally at odds. Whereas one model for hydrogen dissociation on platinum(111) invokes a preequilibrium and diffusion toward defects, the other is based on direct and local reaction. We resolve this dispute by quantifying site-specific reactivity using a curved platinum single-crystal surface. Reactivity is step-type dependent and varies linearly with step density. Only the model that relies on localized dissociation is consistent with our results. Our approach provides absolute, site-specific reaction cross sections.

At the heart of any chemical transformation lie the dynamical events associated with elementary reactions. In gas-phase reactions, reactant energy is redistributed over the limited degrees of freedom available in the products. For gas-surface collisions, the bulk provides a massive sink for energy dissipation. This makes mechanistic problems for gas-surface reactions quite challenging, as exemplified by ongoing discussion regarding the role of phonons and electron-hole pairs in surface reactions (1, 2). In addition, surface heterogeneity may cause site-specific reactions to dominate overall kinetics in catalysis. For example, CO oxidation was recently shown to be site-specific on both Pt and Pd (3, 4).

The prototypical system in heterogeneous catalysis is H2 dissociation on Pt, which is essential to the development of chemically accurate theoretical modeling of gas-surface interactions (5). H2 dissociation occurs through dynamical processes (6, 7). However, after four decades of research, two opposing dynamical models describing H2 dissociation prevail in the literature. The fundamental discrepancy between the models lies in the assumed fate of kinetic energy of incident molecules. In the first model, the energy is conserved in the collision, and incident molecules elastically scatter into a precursor state. In the second model, incident kinetic energy is not conserved. Depending on the exact point of impact, it couples directly to the dissociation coordinate or is dissipated, for example, by excitation of a frustrated rotation.

The two models for H2 dissociation on Pt surfaces are illustrated in Fig. 1. Model 1, schematically shown in Fig. 1A, was proposed by Poelsema, Lenz, and Comsa (7, 8). Scattering experiments have previously shown that atoms and molecules may diffract into a physisorbed state (9, 10). In their model, the elastic collision only leads to dissociation when an H2 molecule also encounters a defect during friction-free diffusion across the surface. The model is summarized by:

Fig. 1 Dynamical H2 dissociation mechanisms.

(A) Model 1: mobile precursor mechanism. (B) Model 2: direct activated dissociation at (111) terraces. (C) Model 2: trapping-mediated dissociation at step edges. (D) Model 2: direct dissociation at step edges. A- and B-type steps are shown in blue and red, respectively. (C) and (D) can take place at either step type, but relative contributions may vary.

Embedded Image(1)

The rate constant for adsorption (kads) depends on the probability to resonantly scatter into the physisorbed state (S0,nL). The rates at which physisorbed molecules desorb (kdes) or encounter defects (kdefect) depend on their velocity (v), residence time (τ), and the average distance between defects (Ld). The model predicts a dissociation probability on the clean surface, S0:

Embedded Image(2)

For large distances between defects, reactivity is rather sensitive to Ld. For short distances—i.e., higher defect densities—this sensitivity is lost. The transition occurs when the mean free path of the physisorbed molecule (i.e., vτ) is comparable to the distance between defects.

In model 2, Baerends (11), Hayden (12), and Somorjai (13) propose parallel dynamical mechanisms for different surface sites, e.g., terraces and steps. None of these mechanisms contains a long-lived, diffusing precursor state. Dissociation is adequately represented as elementary:

Embedded Image(3)

The observed reactivity represents an average (Embedded Image) from site-specific contributions. Terraces contribute by direct dissociation, as illustrated in Fig. 1B. Incident kinetic energy is used to surmount activation barriers that vary with exact location and molecular orientation. Steps contribute by the two mechanisms illustrated in Fig. 1, C and D. The first occurs at the cusp and is responsible for the initial negative correlation of reactivity with incident kinetic energy (Embedded Image) (12, 14). Dynamical calculations suggest that kinetic energy is converted to molecular rotation. Dissociation occurs when the dynamically trapped molecule senses the upper edge of the step (11). The second contribution by steps is barrier-free dissociation at the upper edge (11, 12, 1416). Kinetic energy flows into the reaction coordinate and is quickly lost to the substrate. The reactivity constant in this model can be represented as the weighted average of site-specific reactivities, Embedded Image,

Embedded Image(4)

In contrast to the previous one, this second model predicts a strictly linear relation between reactivity and the fractional occurrence of each type of reactive site, Embedded Image. Whereas the first model also did not discriminate between defects, this model does allow for varying contributions by, e.g., the A- and B-type step edges depicted in Fig. 1.

A new approach allows us to test both models on a single sample. The step density along a curved Pt surface has been shown to vary smoothly from “defect-free” (111) to highly stepped surfaces (17). By combining a curved surface approach and supersonic molecular beam methods (18) with highly improved spatial resolution, we resolve that H2 dissociation does not require physisorption and diffusion to defect sites. In addition, we quantify site-specific reactivities for both {100} (A-type) and {110} (B-type) step types.

A schematic illustration of the experiment is shown in Fig. 2, A to E. Our Pt single crystal is a 31° section of a cylinder along the Embedded Image rotational axis. The (111) surface appears at the apex (19). The macroscopic curvature of the crystal is a direct result of monatomic steps (17). Consequently, the local surface structure on our crystal varies smoothly from Pt(335) via Pt(111) to Pt(553) (19). As both A- and B-type steps are spatially separated by the (111) surface, their influence on reactivity can be probed independently. We measure initial sticking probabilities (Embedded Image) by using the King and Wells approach (20). The molecular beam is incident on the surface along the [111] vector. We measure Embedded Image as a function of step density by translating the single-crystal surface with respect to our rectangular-shaped supersonic molecular beam (0.126 mm by 6.0 mm). Figure 2D illustrates the relative sizes of the crystal and the beam. Figure 2E quantifies the convolution of the narrow molecular beam with step density. Near (111), the probed step density is limited to 0.01 nm−1. Our measurements are limited to step densities of 0.8 nm−1 as a result of narrowing of the crystal at high step densities in combination with the 6-mm width of our beam.

Fig. 2 Curved crystal reactivity measurement.

(A) Bird’s-eye view of the curved Pt single crystal. (B) Side view along the Embedded Image vector. (C) Side view showing the surface structure and surface planes of Pt(335) (A-type steps), Pt(111), and Pt(553) (B-type steps) in blue, gray, and red, respectively. (D) Top view with the molecular beam size in red. (E) Step density probed by the molecular beam at the position relative to the (111) surface. (F) Embedded Image (D2) at Embedded Image= 155 K as a function of step density. Results from A- and B-type step edges are depicted in blue and red, respectively. Circles and squares represent Embedded Image= 9.3 meV and Embedded Image= 100 meV. Lines are least-squares fits to the data. Error bars represent the standard deviation in Embedded Image.

Figure 2F shows Embedded Image at a surface temperature (Embedded Image) of 155 K as a function of step density and step type for Embedded Image = 9.3 meV and 100 meV. These energies are produced by (anti)seeding D2 beams and estimated from measurements of time of flight. At the lower Embedded Image, Embedded Image starts at 0.01 ± 0.05 for the (111) surface and increases linearly with step density. Embedded Image for B-type step edges are consistently higher than A-type step edges at similar step density. At the higher Embedded Image, the influence of steps has disappeared, and Embedded Image is approximately constant over the entire step density range. This energy dependence is consistent with all previous King and Wells studies of H2 dissociation on flat and stepped single-crystal surfaces (12, 1416, 21, 22).

For the lower Embedded Image, for which steps are the dominant source of dissociation, Fig. 3 compares Embedded Image as a function of step density for Embedded Image= 155 K and 300 K. Results are only shown for B-type steps, but the trend is identical for A-type steps. Also shown as dashed lines are predictions for Embedded Image by model 1 (8), as described in the supporting materials. The curvature in the predicted step density dependence is a logical consequence of model 1. When the mean free path of the physisorbed state approaches or exceeds the distance between defects, increasing defect density becomes less effective in increasing Embedded Image. Only at high defect density does Embedded Image become proportional to step density.

Our results are clearly at odds with the predictions by this model. Not only is Embedded Image underestimated over the entire defect density range, but also two crucial dependencies are not reproduced in the experiment. First, predicted curvature in the Embedded Image dependence on step density near the (111) surface is absent. Second, the Embedded Image dependence opposes the predicted trend. Whereas model 1 clearly reduces Embedded Image with increasing Embedded Image because of the diminishing residence time in a physisorbed state, we find that Embedded Image generally increases or is hardly affected. An attempt to improve the model by incorporating Debye-Waller attenuation, reducing the probability of scattering into the resonant state, would increase this discrepancy. In addition to these erroneous dependencies, the site-specific reactivity of Embedded Image seen in Fig. 2F is not captured in model 1. Finally, it also does not capture the observed step density independence at the higher Embedded Image.

In contrast, our results are in agreement with the two underlying assumptions of model 2. Terrace and step sites contributing proportionally to their abundance and the absence of a freely diffusing precursor require a strictly linear dependence of Embedded Image on step density. Least-squares fitting yields a residual reactivity because of dissociation on the Pt(111) surface. Individual fits to A- and B-type steps for lower-incident energy yield 0.023 ± 0.009 and 0.040 ± 0.008. This is in good agreement with previous results (21, 22) for Pt(111), even with experimental results for the clean “defect-free” surface (7) on which model 1 is based. This residual reactivity of the “defect-free” Pt(111) surface is explained by recent dynamical calculations for D2 dissociation (23). Select impact geometries show barrier-free dissociation on the Pt(111) surface.

The slope of the linear fits in Fig. 2F reflect the summed contributions of direct barrier-free and trapping-mediated dissociation at step edges, as shown in Fig. 1, C and D. Multiplying the slope of each linear fit with the width of the unit cell yields the reaction cross section for H2 dissociation at the step edge (16). For our low-Embedded Image data at Embedded Image = 155 K, these are 0.108 ± 0.007 and 0.157 ± 0.007 nm2 for A- and B-type steps, respectively. The reaction cross section for A-type steps agrees quantitatively with theoretical results that show the surface area of the Pt(211) unit cell where impact at the step results in dissociation (11). We previously showed that the direct contribution at the upper edge, shown in Fig. 1D, amounts to 0.043 nm2 (16). The trapping-mediated mechanism in Fig. 1C is then responsible for the 0.065-nm2 difference at A-type steps. As the local structure at the upper edge is identical, the larger cross section for B-type steps compared with A-type steps suggests larger and/or deeper molecular chemisorption wells at its cusp.

In summary, the model ascribing H2 dissociation on Pt mostly to a highly mobile precursor fails to predict the reactivity dependence on step density and surface temperature. In addition to a lack of site specificity, the model erroneously assumes that the perfect Pt(111) surface only exhibits activated adsorption (23). As reactivity in this model is fully ascribed to defects, the model’s parameters and other conjectures must reflect this overestimate. We believe this to be represented by the unphysical assumption that all scattering occurs into the ground vibrational level of the physisorbed state. Furthermore, whereas the model’s parameters are based on a fit to experimental data by using dissociation from a bulb gas at room temperature, the known complex angular dependence to dissociation (21, 24) is not taken into account. More assumptions may contribute to its failure—e.g., that no other possible outcome than dissociation exists when physisorbed molecules encounter a defect.

Simultaneously, our data support that dissociation is dominated by impulsive interactions at the impact site. In the relevant regime, there is no significant surface temperature dependence, and at low kinetic energy, dissociation is strictly linear with step density. At incident energies exceeding most barriers to dissociation on the terrace, the contribution of steps becomes indiscernible; reactivity becomes independent of step density. From our low kinetic energy data, we extract site-specific reaction cross sections for A- and B-type step edges in a chemical reaction. The reaction cross section of B-type steps is significantly larger than that of A-type steps, suggesting a larger molecular chemisorption well with more efficient kinetic energy dissipation. These results present benchmarks for future construction of high dimensional potential energy surfaces and guide dynamical studies aiming to understand the kinetics of this prototypical system. In particular, the origin of the significantly larger cross section for dissociation at B-type step edges may be extracted from calculation of the potential energy surface of H2/Pt(221). Additional (quantum) dynamical calculations, similar to those performed by Baerends and co-workers (11, 25), could confirm the dominant contributions of the three parallel dynamical mechanisms captured by model 2.

Fig. 3 Temperature and B-type step density reactivity dependences.

Circles are measured data for Ekin = 9.3 meV. Solid lines are fits to the data. Dashed lines are predicted results from model 1. Red and black represent Embedded Image = 155 K and 300 K, respectively. Error bars represent the standard deviation in Embedded Image.

Supplementary Materials

www.sciencemag.org/content/363/6423/155/suppl/DC1

Materials and Methods

Supplementary Text

Figs. S1 and S2

References (26, 27)

References and Notes

Acknowledgments: We thank T. Hoogenboom and P. J. van Veldhuizen for technical support. Funding: This work is part of the CO2 neutral fuels research program, which is financed by the Netherlands Organization of Scientific Research (NWO). Author contributions: All the authors contributed substantially to this work. Competing interests: The authors declare no competing interests. Data and materials availability: All data supporting the conclusions are available in the published work or supporting materials.
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