Global Materials Structure Search with Chemically Motivated Coordinates

Identification
of relevant reaction pathways in ever more complex
composite materials and nanostructures poses a central challenge to
computational materials discovery. Efficient global structure search,
tailored to identify chemically relevant intermediates, could provide
the necessary first-principles atomistic insight to enable a rational
process design. In this work we modify a common feature of global
geometry optimization schemes by employing automatically generated
collective curvilinear coordinates. The similarity of these coordinates
to molecular vibrations enhances the generation of chemically meaningful
trial structures for covalently bound systems. In the application
to hydrogenated Si clusters, we concomitantly observe a significantly
increased efficiency in identifying low-energy structures and exploit
it for an extensive sampling of potential products of silicon-cluster
soft landing on Si(001) surfaces.