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In this manuscript we report helium atom scattering (HAS) measurements of the structure of the first H2O layer on Au(111). The interaction between H2O and Au(111) is believed to be particularly weak and conflicting evidence from several indirect stud ies has suggested that water either grows as 3D ice crystals or as an amorphous wetting layer. In contrast, our measurements show that between 110K and 130K, H2O grows as highly commensurate well ordered islands which only partially wet the gold surface. The islands produce a clear (sqrt3Xsqrt3)R30 diffraction pattern and are characterized by a well defined height of ~ 5 Angstrom with respect to the surface gold atoms. These findings provide support for a unique double bilayer model which has recently been suggested for this surface.
Diffusion studies of adsorbates moving on a surface are often analyzed using 2D Langevin simulations. These simulations are computationally cheap and offer valuable insight into the dynamics, however, they simplify the complex interactions between th e substrate and adsorbate atoms, neglecting correlations in the motion of the two species. The effect of this simplification on the accuracy of observables extracted using Langevin simulations was previously unquantified. Here we report a numerical study aimed at assessing the validity of this approach. We compared experimentally accessible observables which were calculated using a Langevin simulation with those obtained from explicit molecular dynamics simulations. Our results show that within the range of parameters we explored Langevin simulations provide a good alternative for calculating the diffusion procress, i.e. the effect of correlations is too small to be observed within the numerical accuracy of this study and most likely would not have a significant effect on the interpretation of experimental data. Our comparison of the two numerical approaches also demonstrates the effect temperature dependent friction has on the calculated observables, illustrating the importance of accounting for such a temperature dependence when interpreting experimental data.
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