杂合型全局优化法优化水分子团簇结构

Global Geometry Optimization of Water Clusters Using Fast Hybrid Global Optimization Algorithm

基于遗传算法、快速模拟退火及共轭梯度方法提出了一种快速的杂合型全局优化方法(fasthybridglobaloptimizationalgorithm,FHGOA),并将这一方法应用于TIP3P和TIPS2模型水分子团簇(H2O)n结构的优化.在进行TIP3P模型水分子团簇结构的优化过程中,发现了能量比文献值更低的团簇结构,且执行效率有较大提高.把该方法应用到优化TIPS2模型的水分子团簇,发现最优结构和采用TTM2-F模型优化的水分子团簇结构在n<17时完全相同,为全表面结构;而在n=17、19、22时为单中心水分子笼状结构;在n=25、27时为双中心水分子笼状结构.说明随着团簇中水分子个数的增加,采用TIPS2和TTM2-F势能函数优化的团簇最优结构有相同的变化趋势.

By combining the genetic algorithm, fast simulated annealing and conjugated gradient algorithm, a novel global optimization method, termed as fast hybrid global optimized algorithm (FHGOA), was proposed and applied to global geometry optimization of water clusters (H2O)(n). In the case of TIP3P, we found lower energy water clusters compared with those reported in literature and the computational efficiency by using FHGOA has been greatly improved. In the case of TIPS2, the global optimized geometries of water clusters (H2O) (n) in the size range of 2 to 27 were found. The water clusters are all-surface structures when n < 17, and the cage structure with one interior water molecule and two interior water molecules appear when n = 17 and n = 25, respectively. This transformation from all-surface structure to the cage structure with one interior water molecule and then to the cage structure with two interior water molecules is in agreement with the case of TTM2-F. The results of this work show that TIPS2 has the ability of modeling large water clusters and is a suitable potential function for MD and MC simulation.