Eduard-Zintl-Institut für Anorganische und Physikalische Chemie, Technische Universität Darmstadt, Petersenstrasse 20, 64287 Darmstadt, Germany.
Nanoscale. 2012 Feb 21;4(4):1109-15. doi: 10.1039/c1nr11053e. Epub 2011 Oct 19.
A genetic algorithm (GA) coupled with density functional theory (DFT) calculations is used to perform global optimisations for all compositions of 8-atom Au-Ag bimetallic clusters. The performance of this novel GA-DFT approach for bimetallic nanoparticles is tested for structures reported in the literature. New global minimum structures for various compositions are predicted and the 2D-3D transition is located. Results are explained with the aid of an analysis of the electronic density of states. The chemical ordering of the predicted lowest energy isomers are explained via a detailed analysis of the charge separation and mixing energies of the bimetallic clusters. Finally, dielectric properties are computed and the composition and dimensionality dependence of the electronic polarizability and dipole moment is discussed, enabling predictions to be made for future electric beam deflection experiments.
遗传算法(GA)与密度泛函理论(DFT)计算相结合,用于对所有 8 原子金-银双金属团簇的所有组成进行全局优化。该新型 GA-DFT 方法对文献中报道的双金属纳米粒子的性能进行了测试。预测了各种组成的新的全局最小结构,并定位了 2D-3D 转变。通过分析电子态密度来解释结果。通过对双金属团簇的电荷分离和混合能的详细分析,解释了预测的最低能量异构体的化学有序性。最后,计算了介电性能,并讨论了电子极化率和偶极矩的组成和维度依赖性,从而能够对未来的电子束偏转实验进行预测。