期刊
SURFACE SCIENCE
卷 606, 期 3-4, 页码 233-238出版社
ELSEVIER
DOI: 10.1016/j.susc.2011.09.024
关键词
Density functional theory; Water; Platinum; Terrace; Step surface; Kink surface; Adsorption; Diffusion
资金
- Office of Naval Research
- National Science Foundation
- EC MC-RTN
- U.S. Department of Energy's Office of Biological and Environmental Research at the Pacific Northwest National Laboratory
Surface diffusion of water monomer, dimer, and trimer on the (111) terrace, (221) and (322) stepped, and (763) and (854) kinked surfaces of platinum was studied by density functional theory using the PW91 approximation to the energy functional. Monomer diffusion on the terrace is facile, with an activation barrier of 020 eV, while dimer and trimer diffusions are restricted due to their high activation barriers of 0.43 and 0.48 eV, respectively. During monomer diffusion on the terrace the O-Pt distance increases by 0.54 angstrom, about 23% of the initial distance of 2.34 angstrom. The calculated rate of monomer diffusion hops is in good agreement with the onset temperature of diffusion measurements of Daschbach et al., J. Chem. Phys., 120 (2004) 1516. Alternative monomer diffusion pathways, in which the molecule rolls or flips, were also found. These pathways have diffusion barriers of 0.22 eV. During dimer diffusion on the terrace, the donor molecule rises 0.4 angstrom at the saddle point, while the acceptor rises by only 0.03 angstrom. Monomer diffusion up to steps and kinks, with activation barriers of 0.11-0.13 eV, facilitate chain formation on top of step edges. The energy landscape of monomer diffusion from terrace to step to kink sites is downhill with a maximum activation barrier of 0.26 eV. A model for water adsorption is presented in which monomer diffusion leads to concurrent formation of terrace clusters and population of steps/kinks, the latter consistent with the STM measurements of Morgenstern et al., Phys. Rev. Lett., 77 (1996) 703. (C) 2011 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据