  Linear scaling methods for density-functional theory (DFT) simulations are
formulated in terms of localised orbitals in real-space, rather than the
delocalised eigenstates of conventional approaches. In local-orbital methods,
relative to conventional DFT, desirable properties can be lost to some extent,
such as the translational invariance of the total energy of a system with
respect to small displacements and the smoothness of the potential energy
surface. This has repercussions for calculating accurate ionic forces and
geometries. In this work we present results from \textsc{onetep}, our linear
scaling method based on localised orbitals in real-space. The use of psinc
functions for the underlying basis set and on-the-fly optimisation of the
localised orbitals results in smooth potential energy surfaces that are
consistent with ionic forces calculated using the Hellmann-Feynman theorem.
This enables accurate geometry optimisation to be performed. Results for
surface reconstructions in silicon are presented, along with three example
systems demonstrating the performance of a quasi-Newton geometry optimisation
algorithm: an organic zwitterion, a point defect in an ionic crystal, and a
semiconductor nanostructure.
