Abstract
The activation of alkanes on metal catalysts may involve a precursor-mediated mechanism, in which impinging molecules are first trapped on the catalyst surface to form an adsorbed precursor and may undergo extensive excursion on the surface in search of an active site. A characteristic feature of such a mechanism is an increasing initial sticking probability (S(0)) with decreasing incidence energy at low incidence energies. Indeed, such "negative activation" was observed on the reconstructed Pt(110)-(2 × 1) surface with a missing row structure. In this paper, we describe an extensive theoretical investigation of methane dissociation on Pt(110)-(2 × 1) using a machine-learned high-dimensional potential energy surface (PES) based on a first-principles training data set. Quasi-classical trajectories (QCTs) are calculated on the PES to simulate the dissociation of both CH(4) and CHD(3) at various incidence energies. The agreement with the measured initial sticking probabilities is shown to be substantially improved for high incidence energies when compared to previous theoretical studies, indicating a better characterization of the dissociation barrier. Additional QCT calculations have been carried out for the trapping and diffusion of CHD(3) under experimental conditions at low incidence energies. The trapping probability is shown to increase with decreasing incidence energy, consistent with the experimentally observed "negative activation" below 10 kJ/mol. The reactivity of the trapped methane is attributed to the combined effect of its nonthermal diffusion across the surface Pt rows and the lowered barrier reached by surface thermal fluctuation. These simulations shed valuable light on the microscopic dynamics of the initial and often rate-limiting step in heterogeneous catalytic processes involving alkanes.