GOAT: A Global Optimization Algorithm for Molecules and Atomic Clusters.

In this work, we propose a new Global Optimization Algorithm (GOAT) for molecules and clusters of atoms and show how it can find the global energy minima for both systems without resorting to molecular dynamics (MD). This avoids the potential millions of time-consuming gradient calculations required by a long MD run. Because of that, it can be used with any regular quantum chemical method, even with the costlier hybrid DFT. We showcase its accuracy by running it on various systems, from organic molecules to water clusters, metal complexes, and metal nanoparticles, comparing it with state-of-the-art methods such as the Conformer-Rotamer Ensemble Sampling Tool (CREST). We also discuss its underlying theory and mechanisms for succeeding in challenging cases. GOAT is, in general, more efficient and accurate than previous algorithms in finding global minima and succeeds in cases where others cannot due to the free choice for the Potential Energy Surface (PES).