从头算
分子轨道
锂(药物)
能量(信号处理)
理论(学习稳定性)
性格(数学)
计算化学
物理
化学
材料科学
结晶学
原子物理学
分子物理学
分子
计算机科学
数学
量子力学
几何学
生物
机器学习
内分泌学
作者
Anastassia N. Alexandrova,Alexander I. Boldyrev
摘要
We report the study of small lithium clusters Lin(0/+1/)(-)(1) (n = 5-7), performed via the novel Gradient Embedded Genetic Algorithm (GEGA) technique and molecular orbital analysis. GEGA was developed for searching of the lowest-energy structures of clusters. Results of our search, obtained using this program, have been compared with the previous ab initio calculations, and the efficiency of the developed GEGA method has thus been confirmed. The molecular orbital analysis of the found Lin(0/+1/)(-)(1) (n = 5-7) clusters showed the presence of multiple (σ and π) aromatic character in their chemical bonding, which governs their preferable shapes and special stability.
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