Structural prediction and materials design : from high throughput to global minima optimization methods

In this thesis we use high-throughput techniques and global structure prediction algorithms to predict the crystal structure of different materials under different conditions. We start by investigating the modi cations on the structure of carbon nanotubes under hydrostatic pressure. Afterwards, we explore a subset of ternary silicon clathrates searching for new thermodynamically stable phases. Then, we screen the periodic table for new p−type transparent oxides of the form (Cu, Ag, Au, Ni)XO2 and CuXOS. Finally, we present a new approach for materials design in a pure ab initio way.


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