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.

中文翻译：

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遗传算法的方法来全维势能面的全局优化在氢原子的fcc -金属表面

我们已经开发了一种基于多维势能面参数化的遗传算法方法，该方法基于有效介质理论得出的能量的解析表达式，将其拟合到DFT数据中。这种方法对于许多fcc金属表面（Al，Ag，Au，Cu，Ni，Pd，Pt和Rh）的H原子相互作用能产生一致的结果，并且为几乎任何系统几何形状（包括各个方面）提供合理的能量值。