Structural optimization of molecular clusters with density functional theory combined with basin hopping
Identifying the energy minima of molecular clusters is a challenging problem. Traditionally, search algorithms such as simulated annealing, genetic algorithms, or basin hopping are usually used in conjunction with empirical force fields. We have implemented a basin hopping search algorithm combined with density functional theory to enable the optimization of molecular clusters without the need for empirical force fields. This approach can be applied to systems where empirical potentials are not available or may not be sufficiently accurate. We illustrate the effectiveness of the method with studies on water, methanol, and water + methanol clusters as well as protonated water and methanol clusters at the B3LYP+D/6-31+G* level of theory. A new lowest energy structure for H+(H2O)7 is predicted at the B3LYP+D/6-31+G* level. In all of the protonated mixed water and methanol clusters, we find that H+ prefers to combine with methanol rather than water in the lowest-energy structures.