The prediction of structure at the atomic level is one of the most fundamental challenges in
condensed matter science. Here we survey the current status of the field and consider recent …

The tremendous interest in nanoscale structures such as quantum dots (zero-dimension)
and wires (quasi-one-dimension) stems from their size-dependent properties. One …

We propose a scheme for global optimization with first-principles energy expressions of
atomistic structure. While unfolding its search, the method actively learns a surrogate model …

The effect of the nanostructure on the photochemistry of TiO2 is an active field of research
owing to its applications in photocatalysis and photovoltaics. Despite this interest, little is …

We review the growing role of computational techniques in modelling the structures and
properties of nano-particulate oxides and sulphides. We describe the main methods …

Bottom-up and top-down derived nanoparticle structures refined by accurate ab initio
calculations are used to investigate the size dependent emergence of crystallinity in titania …

Suggestions for improving the Basin-Hopping Monte Carlo (BHMC) algorithm for unbiased
global optimization of clusters and nanoparticles are presented. The traditional basin …

Understanding the properties of solid-state materials at the nanoscale is a crucial scientific
endeavor in the pursuit of a sustainable energy future. Since magnesium hydride is the most …

Global optimization with first-principles energy expressions (GOFEE) is an efficient method
for identifying low-energy structures in computationally expensive energy landscapes such …

We report the stable and low energy metastable structures of zinc oxide clusters,(ZnO) n, n=
1− 32, found using an evolutionary algorithm with polarizable shell interatomic potentials …