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Genetic algorithm approach to global optimization of the full-dimensional potential energy surface for hydrogen atom at fcc-metal surfaces.

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Kammler,  M.
Department of Dynamics at Surfaces, MPI for Biophysical Chemistry, Max Planck Society;

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Janke,  S. M.
Department of Dynamics at Surfaces, MPI for Biophysical Chemistry, Max Planck Society;

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Kandratsenka,  A.
Department of Dynamics at Surfaces, MPI for Biophysical Chemistry, Max Planck Society;

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Wodtke,  A. M.
Department of Dynamics at Surfaces, MPI for Biophysical Chemistry, Max Planck Society;

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Citation

Kammler, M., Janke, S. M., Kandratsenka, A., & Wodtke, A. M. (2017). Genetic algorithm approach to global optimization of the full-dimensional potential energy surface for hydrogen atom at fcc-metal surfaces. Chemical Physics Letters, 683, 286-290. doi:10.1016/j.cplett.2017.03.086.


Cite as: http://hdl.handle.net/11858/00-001M-0000-002D-B900-8
Abstract
We have developed a genetic algorithm approach for the parametrization of a multi-dimensional potential energy surface based on the analytical expression for energy derived from Effective Medium Theory by fitting it to DFT data. This approach yields consistent results for the H-atom interaction energy with a number of fcc-metal surfaces (Al, Ag, Au, Cu, Ni, Pd, Pt and Rh) and provides reasonable energy values for virtually any system geometry including various facets. (C) 2017 Elsevier B. V. All rights reserved.