Global geometry optimization of clusters guided by N-dependent model potentials

A new global geometry optimization strategy for use on ab initio potential energy surfaces is presented. Aided by a continuously adapted model potential, this method minimizes the number of ab initio points needed but still retains global convergence. The power of the strategy is demonstrated by the discovery of flaws in a complicated empirical potential for silicon clusters.