Structure prediction of clusters based on the exploration & characterization of their energy landscapes

The study of energy landscapes based on the electronic structure of materials is a fast growing field aided by the rapid advancements of both computational resources and the formulation of
new efficient algorithms. Many properties of materials can now be determined directly from simulations based on electronic structure calculations. The study of energy landscapes is
turning out to be the key of resolving many important problems in chemical physics and material science. In the field of innovation of new materials for technological advancement, computational
structure prediction methods are becoming a time efficient and economical choice before taking decision of experimental synthesis. In this dissertation we present the application
of a structure prediction method, Minima Hopping, to the exploration of energy landscapes of atomic clusters made of different elements. In addition to the reporting of several new stable clusters,
the work goes beyond mere structure prediction, and answers several basic questions regarding the behavior of different clusters by studying their energy landscapes.