  We propose a scheme for global optimization with first-principles energy
expressions (GOFEE) of atomistic structure. While unfolding its search, the
method actively learns a surrogate model of the potential energy landscape on
which it performs a number of local relaxations (exploitation) and further
structural searches (exploration). Assuming Gaussian Processes, an acquisition
function is used to decide on which of the resulting structures is the more
promising. Subsequently, a single point first-principles energy calculation is
conducted for that structure. The method is demonstrated to outperform by two
orders of magnitude a well established first-principles based evolutionary
algorithm in finding surface reconstructions. Finally, GOFEE is utilized to
identify initial stages of the edge oxidation and oxygen intercalation of
graphene sheets on the Ir(111) surface.
